Overview

Dataset statistics

Number of variables35
Number of observations109
Missing cells427
Missing cells (%)11.2%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory29.9 KiB
Average record size in memory281.2 B

Variable types

DateTime1
Categorical29
Numeric3
Unsupported2

Alerts

Score has constant value "0" Constant
ท่านให้ความยินยอมในการตอบแบบสอบถาม has constant value "ยินยอมและเริ่มตอบแบบสอบถาม" Constant
ฉันได้อ่าน และทำความเข้าใจกับคำแนะนำข้างต้นนี้แล้ว has constant value "ใช่" Constant
Email Address has a high cardinality: 108 distinct values High cardinality
ชื่อเล่น has a high cardinality: 104 distinct values High cardinality
วันเกิด has a high cardinality: 70 distinct values High cardinality
กับการเริ่มต้นเรียนในปีการศึกษา 2565 .. ภาพฝันของเรา 1 ปีต่อจากนี้เป็นอย่างไร ? บอกได้เต็มที่เลยนะ has a high cardinality: 108 distinct values High cardinality
เบอร์ติดต่อ (เช่น 0991234567 หรือ 028546685 เป็นต้น) has a high cardinality: 108 distinct values High cardinality
ในปีการศึกษา 2565 นี้ ฉันกำลังเรียนอยู่ในระดับห้อง is highly correlated with ในปีการศึกษา 2565 นี้ ฉันกำลังเรียนอยู่ในระดับชั้น and 10 other fieldsHigh correlation
เลขประจำตัวนักเรียน is highly correlated with ในปีการศึกษา 2565 นี้ ฉันกำลังเรียนอยู่ในระดับชั้น and 7 other fieldsHigh correlation
Q16 is highly correlated with ในปีการศึกษา 2565 นี้ ฉันกำลังเรียนอยู่ในระดับห้อง and 14 other fieldsHigh correlation
Q9 is highly correlated with วันเกิด and 15 other fieldsHigh correlation
Score is highly correlated with Q16 and 23 other fieldsHigh correlation
เพศ is highly correlated with วันเกิด and 3 other fieldsHigh correlation
Q13 is highly correlated with เลขประจำตัวนักเรียน and 18 other fieldsHigh correlation
Q3 is highly correlated with อ.ที่ปรึกษาคนที่ 1 and 14 other fieldsHigh correlation
อุปกรณ์ที่ใช้ในการทำโฮมรูมครั้งนี้ is highly correlated with วันเกิด and 1 other fieldsHigh correlation
Q14 is highly correlated with Q1 and 14 other fieldsHigh correlation
Q11 is highly correlated with เลขประจำตัวนักเรียน and 15 other fieldsHigh correlation
ท่านให้ความยินยอมในการตอบแบบสอบถาม is highly correlated with Q16 and 23 other fieldsHigh correlation
Q5 is highly correlated with ในปีการศึกษา 2565 นี้ ฉันกำลังเรียนอยู่ในระดับห้อง and 14 other fieldsHigh correlation
Q1 is highly correlated with วันเกิด and 16 other fieldsHigh correlation
ฉันได้อ่าน และทำความเข้าใจกับคำแนะนำข้างต้นนี้แล้ว is highly correlated with Q16 and 23 other fieldsHigh correlation
Q15 is highly correlated with ในปีการศึกษา 2565 นี้ ฉันกำลังเรียนอยู่ในระดับห้อง and 16 other fieldsHigh correlation
ในปีการศึกษา 2565 นี้ ฉันกำลังเรียนอยู่ในระดับชั้น is highly correlated with ในปีการศึกษา 2565 นี้ ฉันกำลังเรียนอยู่ในระดับห้อง and 4 other fieldsHigh correlation
อ.ที่ปรึกษาคนที่ 2 is highly correlated with ในปีการศึกษา 2565 นี้ ฉันกำลังเรียนอยู่ในระดับชั้น and 13 other fieldsHigh correlation
Q7 is highly correlated with ในปีการศึกษา 2565 นี้ ฉันกำลังเรียนอยู่ในระดับห้อง and 15 other fieldsHigh correlation
Q4 is highly correlated with วันเกิด and 15 other fieldsHigh correlation
Q8 is highly correlated with Q1 and 9 other fieldsHigh correlation
วันเกิด is highly correlated with ในปีการศึกษา 2565 นี้ ฉันกำลังเรียนอยู่ในระดับชั้น and 12 other fieldsHigh correlation
อ.ที่ปรึกษาคนที่ 1 is highly correlated with ในปีการศึกษา 2565 นี้ ฉันกำลังเรียนอยู่ในระดับชั้น and 11 other fieldsHigh correlation
Q12 is highly correlated with ในปีการศึกษา 2565 นี้ ฉันกำลังเรียนอยู่ในระดับห้อง and 17 other fieldsHigh correlation
Q10 is highly correlated with ในปีการศึกษา 2565 นี้ ฉันกำลังเรียนอยู่ในระดับห้อง and 18 other fieldsHigh correlation
Q2 is highly correlated with อ.ที่ปรึกษาคนที่ 1 and 15 other fieldsHigh correlation
Q6 is highly correlated with ในปีการศึกษา 2565 นี้ ฉันกำลังเรียนอยู่ในระดับห้อง and 16 other fieldsHigh correlation
เลขบัตรประชาชน has 59 (54.1%) missing values Missing
วันเกิด has 32 (29.4%) missing values Missing
อ.ที่ปรึกษาคนที่ 1 has 59 (54.1%) missing values Missing
อ.ที่ปรึกษาคนที่ 2 has 59 (54.1%) missing values Missing
กรุณาแจ้งเหตุผลที่ไม่ยินยอมตอบแบบสอบถาม has 109 (100.0%) missing values Missing
Quilgo Submission ID (do not edit) has 109 (100.0%) missing values Missing
Email Address is uniformly distributed Uniform
ชื่อเล่น is uniformly distributed Uniform
วันเกิด is uniformly distributed Uniform
กับการเริ่มต้นเรียนในปีการศึกษา 2565 .. ภาพฝันของเรา 1 ปีต่อจากนี้เป็นอย่างไร ? บอกได้เต็มที่เลยนะ is uniformly distributed Uniform
เบอร์ติดต่อ (เช่น 0991234567 หรือ 028546685 เป็นต้น) is uniformly distributed Uniform
Timestamp has unique values Unique
กรุณาแจ้งเหตุผลที่ไม่ยินยอมตอบแบบสอบถาม is an unsupported type, check if it needs cleaning or further analysis Unsupported
Quilgo Submission ID (do not edit) is an unsupported type, check if it needs cleaning or further analysis Unsupported

Reproduction

Analysis started2022-10-04 10:50:54.837585
Analysis finished2022-10-04 10:51:26.972596
Duration32.14 seconds
Software versionpandas-profiling v3.3.0
Download configurationconfig.json

Variables

Timestamp
Date

UNIQUE

Distinct109
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size1000.0 B
Minimum2022-09-13 13:20:53.204000
Maximum2022-09-28 09:59:37.818000
2022-10-04T17:51:27.276140image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-10-04T17:51:27.737623image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

Email Address
Categorical

HIGH CARDINALITY
UNIFORM

Distinct108
Distinct (%)99.1%
Missing0
Missing (%)0.0%
Memory size1000.0 B
std28601@mwk.ac.th
 
2
std28620@mwk.ac.th
 
1
suphatcha.peemai@gmail.com
 
1
stdd30496@mwk.ac.th
 
1
std27529@mwk.ac.th
 
1
Other values (103)
103 

Length

Max length26
Median length18
Mean length18.69724771
Min length18

Characters and Unicode

Total characters2038
Distinct characters35
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique107 ?
Unique (%)98.2%

Sample

1st rowstd27506@mwk.ac.th
2nd rowstd27513@mwk.ac.th
3rd rowstd27514@mwk.ac.th
4th rowstd27516@mwk.ac.th
5th rowstd27518@mwk.ac.th

Common Values

ValueCountFrequency (%)
std28601@mwk.ac.th2
 
1.8%
std28620@mwk.ac.th1
 
0.9%
suphatcha.peemai@gmail.com1
 
0.9%
stdd30496@mwk.ac.th1
 
0.9%
std27529@mwk.ac.th1
 
0.9%
stdd28587@mwk.ac.th1
 
0.9%
std27535@mwk.ac.th1
 
0.9%
stdd30512@mwk.ac.th1
 
0.9%
std27518@mwk.ac.th1
 
0.9%
std30312@gmail.com1
 
0.9%
Other values (98)98
89.9%

Length

2022-10-04T17:51:28.218622image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
std28601@mwk.ac.th2
 
1.8%
stdd28521@mwk.ac.th1
 
0.9%
std27530@mwk.ac.th1
 
0.9%
std29034@mwk.ac.th1
 
0.9%
std28655@mwk.ac.th1
 
0.9%
std27600@mwk.ac.th1
 
0.9%
stdd28827@mwk.ac.th1
 
0.9%
std27594@mwk.ac.th1
 
0.9%
stdd30485@mwk.ac.th1
 
0.9%
std27520@mwk.ac.th1
 
0.9%
Other values (98)98
89.9%

Most occurring characters

ValueCountFrequency (%)
.210
 
10.3%
t206
 
10.1%
d145
 
7.1%
m124
 
6.1%
a119
 
5.8%
2116
 
5.7%
c111
 
5.4%
@109
 
5.3%
s109
 
5.3%
k102
 
5.0%
Other values (25)687
33.7%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter1186
58.2%
Decimal Number533
26.2%
Other Punctuation319
 
15.7%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
t206
17.4%
d145
12.2%
m124
10.5%
a119
10.0%
c111
9.4%
s109
9.2%
k102
8.6%
h101
8.5%
w99
8.3%
i16
 
1.3%
Other values (13)54
 
4.6%
Decimal Number
ValueCountFrequency (%)
2116
21.8%
369
12.9%
868
12.8%
567
12.6%
058
10.9%
750
9.4%
632
 
6.0%
126
 
4.9%
924
 
4.5%
423
 
4.3%
Other Punctuation
ValueCountFrequency (%)
.210
65.8%
@109
34.2%

Most occurring scripts

ValueCountFrequency (%)
Latin1186
58.2%
Common852
41.8%

Most frequent character per script

Latin
ValueCountFrequency (%)
t206
17.4%
d145
12.2%
m124
10.5%
a119
10.0%
c111
9.4%
s109
9.2%
k102
8.6%
h101
8.5%
w99
8.3%
i16
 
1.3%
Other values (13)54
 
4.6%
Common
ValueCountFrequency (%)
.210
24.6%
2116
13.6%
@109
12.8%
369
 
8.1%
868
 
8.0%
567
 
7.9%
058
 
6.8%
750
 
5.9%
632
 
3.8%
126
 
3.1%
Other values (2)47
 
5.5%

Most occurring blocks

ValueCountFrequency (%)
ASCII2038
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
.210
 
10.3%
t206
 
10.1%
d145
 
7.1%
m124
 
6.1%
a119
 
5.8%
2116
 
5.7%
c111
 
5.4%
@109
 
5.3%
s109
 
5.3%
k102
 
5.0%
Other values (25)687
33.7%

Score
Categorical

CONSTANT
HIGH CORRELATION
REJECTED

Distinct1
Distinct (%)0.9%
Missing0
Missing (%)0.0%
Memory size1000.0 B
0
109 

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters109
Distinct characters1
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0109
100.0%

Length

2022-10-04T17:51:28.529138image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
Histogram of lengths of the category

Category Frequency Plot

2022-10-04T17:51:28.862826image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
ValueCountFrequency (%)
0109
100.0%

Most occurring characters

ValueCountFrequency (%)
0109
100.0%

Most occurring categories

ValueCountFrequency (%)
Decimal Number109
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0109
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common109
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0109
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII109
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0109
100.0%

ท่านให้ความยินยอมในการตอบแบบสอบถาม
Categorical

CONSTANT
HIGH CORRELATION
REJECTED

Distinct1
Distinct (%)0.9%
Missing0
Missing (%)0.0%
Memory size1000.0 B
ยินยอมและเริ่มตอบแบบสอบถาม
109 

Length

Max length26
Median length26
Mean length26
Min length26

Characters and Unicode

Total characters2834
Distinct characters16
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowยินยอมและเริ่มตอบแบบสอบถาม
2nd rowยินยอมและเริ่มตอบแบบสอบถาม
3rd rowยินยอมและเริ่มตอบแบบสอบถาม
4th rowยินยอมและเริ่มตอบแบบสอบถาม
5th rowยินยอมและเริ่มตอบแบบสอบถาม

Common Values

ValueCountFrequency (%)
ยินยอมและเริ่มตอบแบบสอบถาม109
100.0%

Length

2022-10-04T17:51:29.144285image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
Histogram of lengths of the category

Category Frequency Plot

2022-10-04T17:51:29.440433image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
ValueCountFrequency (%)
ยินยอมและเริ่มตอบแบบสอบถาม109
100.0%

Most occurring characters

ValueCountFrequency (%)
บ436
15.4%
อ327
11.5%
ม327
11.5%
ย218
 
7.7%
ิ218
 
7.7%
แ218
 
7.7%
น109
 
3.8%
ล109
 
3.8%
ะ109
 
3.8%
เ109
 
3.8%
Other values (6)654
23.1%

Most occurring categories

ValueCountFrequency (%)
Other Letter2507
88.5%
Nonspacing Mark327
 
11.5%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
บ436
17.4%
อ327
13.0%
ม327
13.0%
ย218
8.7%
แ218
8.7%
น109
 
4.3%
ล109
 
4.3%
ะ109
 
4.3%
เ109
 
4.3%
ร109
 
4.3%
Other values (4)436
17.4%
Nonspacing Mark
ValueCountFrequency (%)
ิ218
66.7%
่109
33.3%

Most occurring scripts

ValueCountFrequency (%)
Thai2834
100.0%

Most frequent character per script

Thai
ValueCountFrequency (%)
บ436
15.4%
อ327
11.5%
ม327
11.5%
ย218
 
7.7%
ิ218
 
7.7%
แ218
 
7.7%
น109
 
3.8%
ล109
 
3.8%
ะ109
 
3.8%
เ109
 
3.8%
Other values (6)654
23.1%

Most occurring blocks

ValueCountFrequency (%)
Thai2834
100.0%

Most frequent character per block

Thai
ValueCountFrequency (%)
บ436
15.4%
อ327
11.5%
ม327
11.5%
ย218
 
7.7%
ิ218
 
7.7%
แ218
 
7.7%
น109
 
3.8%
ล109
 
3.8%
ะ109
 
3.8%
เ109
 
3.8%
Other values (6)654
23.1%

ฉันได้อ่าน และทำความเข้าใจกับคำแนะนำข้างต้นนี้แล้ว
Categorical

CONSTANT
HIGH CORRELATION
REJECTED

Distinct1
Distinct (%)0.9%
Missing0
Missing (%)0.0%
Memory size1000.0 B
ใช่
109 

Length

Max length3
Median length3
Mean length3
Min length3

Characters and Unicode

Total characters327
Distinct characters3
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowใช่
2nd rowใช่
3rd rowใช่
4th rowใช่
5th rowใช่

Common Values

ValueCountFrequency (%)
ใช่109
100.0%

Length

2022-10-04T17:51:29.744104image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
Histogram of lengths of the category

Category Frequency Plot

2022-10-04T17:51:30.079358image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
ValueCountFrequency (%)
ใช่109
100.0%

Most occurring characters

ValueCountFrequency (%)
ใ109
33.3%
ช109
33.3%
่109
33.3%

Most occurring categories

ValueCountFrequency (%)
Other Letter218
66.7%
Nonspacing Mark109
33.3%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
ใ109
50.0%
ช109
50.0%
Nonspacing Mark
ValueCountFrequency (%)
่109
100.0%

Most occurring scripts

ValueCountFrequency (%)
Thai327
100.0%

Most frequent character per script

Thai
ValueCountFrequency (%)
ใ109
33.3%
ช109
33.3%
่109
33.3%

Most occurring blocks

ValueCountFrequency (%)
Thai327
100.0%

Most frequent character per block

Thai
ValueCountFrequency (%)
ใ109
33.3%
ช109
33.3%
่109
33.3%

ในปีการศึกษา 2565 นี้ ฉันกำลังเรียนอยู่ในระดับชั้น
Categorical

HIGH CORRELATION

Distinct3
Distinct (%)2.8%
Missing0
Missing (%)0.0%
Memory size1000.0 B
ม. 4
61 
ม. 6
25 
ม. 1
23 

Length

Max length4
Median length4
Mean length4
Min length4

Characters and Unicode

Total characters436
Distinct characters6
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowม. 6
2nd rowม. 6
3rd rowม. 6
4th rowม. 6
5th rowม. 6

Common Values

ValueCountFrequency (%)
ม. 461
56.0%
ม. 625
22.9%
ม. 123
 
21.1%

Length

2022-10-04T17:51:30.329029image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
Histogram of lengths of the category

Category Frequency Plot

2022-10-04T17:51:30.612603image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
ValueCountFrequency (%)
ม109
50.0%
461
28.0%
625
 
11.5%
123
 
10.6%

Most occurring characters

ValueCountFrequency (%)
ม109
25.0%
.109
25.0%
109
25.0%
461
14.0%
625
 
5.7%
123
 
5.3%

Most occurring categories

ValueCountFrequency (%)
Other Letter109
25.0%
Other Punctuation109
25.0%
Space Separator109
25.0%
Decimal Number109
25.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
461
56.0%
625
22.9%
123
 
21.1%
Other Letter
ValueCountFrequency (%)
ม109
100.0%
Other Punctuation
ValueCountFrequency (%)
.109
100.0%
Space Separator
ValueCountFrequency (%)
109
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common327
75.0%
Thai109
 
25.0%

Most frequent character per script

Common
ValueCountFrequency (%)
.109
33.3%
109
33.3%
461
18.7%
625
 
7.6%
123
 
7.0%
Thai
ValueCountFrequency (%)
ม109
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII327
75.0%
Thai109
 
25.0%

Most frequent character per block

Thai
ValueCountFrequency (%)
ม109
100.0%
ASCII
ValueCountFrequency (%)
.109
33.3%
109
33.3%
461
18.7%
625
 
7.6%
123
 
7.0%

ในปีการศึกษา 2565 นี้ ฉันกำลังเรียนอยู่ในระดับห้อง
Real number (ℝ≥0)

HIGH CORRELATION

Distinct6
Distinct (%)5.5%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2.770642202
Minimum1
Maximum9
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1000.0 B
2022-10-04T17:51:30.938371image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q11
median3
Q33
95-th percentile6
Maximum9
Range8
Interquartile range (IQR)2

Descriptive statistics

Standard deviation2.016749436
Coefficient of variation (CV)0.7278996309
Kurtosis-0.425516766
Mean2.770642202
Median Absolute Deviation (MAD)2
Skewness0.8584781614
Sum302
Variance4.067278287
MonotonicityNot monotonic
2022-10-04T17:51:31.178455image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
Histogram with fixed size bins (bins=6)
ValueCountFrequency (%)
149
45.0%
330
27.5%
623
21.1%
24
 
3.7%
42
 
1.8%
91
 
0.9%
ValueCountFrequency (%)
149
45.0%
24
 
3.7%
330
27.5%
42
 
1.8%
623
21.1%
91
 
0.9%
ValueCountFrequency (%)
91
 
0.9%
623
21.1%
42
 
1.8%
330
27.5%
24
 
3.7%
149
45.0%

เลขประจำตัวนักเรียน
Real number (ℝ≥0)

HIGH CORRELATION

Distinct108
Distinct (%)99.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean28974.21101
Minimum27506
Maximum30707
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1000.0 B
2022-10-04T17:51:31.481725image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/

Quantile statistics

Minimum27506
5-th percentile27522
Q128529
median28607
Q330286
95-th percentile30510.2
Maximum30707
Range3201
Interquartile range (IQR)1757

Descriptive statistics

Standard deviation1049.278836
Coefficient of variation (CV)0.03621423326
Kurtosis-1.253129386
Mean28974.21101
Median Absolute Deviation (MAD)981
Skewness0.2487280882
Sum3158189
Variance1100986.075
MonotonicityNot monotonic
2022-10-04T17:51:31.867033image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
286012
 
1.8%
286731
 
0.9%
275351
 
0.9%
285781
 
0.9%
285441
 
0.9%
278081
 
0.9%
278061
 
0.9%
285731
 
0.9%
285721
 
0.9%
288271
 
0.9%
Other values (98)98
89.9%
ValueCountFrequency (%)
275061
0.9%
275131
0.9%
275141
0.9%
275161
0.9%
275181
0.9%
275201
0.9%
275251
0.9%
275261
0.9%
275271
0.9%
275281
0.9%
ValueCountFrequency (%)
307071
0.9%
306731
0.9%
305141
0.9%
305131
0.9%
305121
0.9%
305111
0.9%
305091
0.9%
304961
0.9%
304871
0.9%
304861
0.9%

เลขบัตรประชาชน
Real number (ℝ≥0)

MISSING

Distinct50
Distinct (%)100.0%
Missing59
Missing (%)54.1%
Infinite0
Infinite (%)0.0%
Mean1.963778879 × 1012
Minimum1.100801518 × 1012
Maximum8.571576078 × 1012
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1000.0 B
2022-10-04T17:51:32.263135image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/

Quantile statistics

Minimum1.100801518 × 1012
5-th percentile1.104035366 × 1012
Q11.578800026 × 1012
median1.578800037 × 1012
Q31.579901097 × 1012
95-th percentile5.557115244 × 1012
Maximum8.571576078 × 1012
Range7.47077456 × 1012
Interquartile range (IQR)1101070731

Descriptive statistics

Standard deviation1.686412003 × 1012
Coefficient of variation (CV)0.8587586011
Kurtosis12.89724701
Mean1.963778879 × 1012
Median Absolute Deviation (MAD)300012483.5
Skewness3.773337111
Sum9.818894395 × 1013
Variance2.843985444 × 1024
MonotonicityNot monotonic
2022-10-04T17:51:32.564134image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1.578800028 × 10121
 
0.9%
1.578500023 × 10121
 
0.9%
1.579901106 × 10121
 
0.9%
1.578800048 × 10121
 
0.9%
8.571576078 × 10121
 
0.9%
1.578500025 × 10121
 
0.9%
1.57990121 × 10121
 
0.9%
1.578500015 × 10121
 
0.9%
1.510101497 × 10121
 
0.9%
1.509300004 × 10121
 
0.9%
Other values (40)40
36.7%
(Missing)59
54.1%
ValueCountFrequency (%)
1.100801518 × 10121
0.9%
1.103704138 × 10121
0.9%
1.103900223 × 10121
0.9%
1.10420054 × 10121
0.9%
1.509300004 × 10121
0.9%
1.510101497 × 10121
0.9%
1.570901168 × 10121
0.9%
1.578500015 × 10121
0.9%
1.578500016 × 10121
0.9%
1.578500023 × 10121
0.9%
ValueCountFrequency (%)
8.571576078 × 10121
0.9%
8.571573027 × 10121
0.9%
8.500373 × 10121
0.9%
1.959800209 × 10121
0.9%
1.579901224 × 10121
0.9%
1.579901217 × 10121
0.9%
1.579901212 × 10121
0.9%
1.57990121 × 10121
0.9%
1.579901209 × 10121
0.9%
1.579901116 × 10121
0.9%

ชื่อเล่น
Categorical

HIGH CARDINALITY
UNIFORM

Distinct104
Distinct (%)95.4%
Missing0
Missing (%)0.0%
Memory size1000.0 B
ฟ้อนต์
 
2
ปีใหม่
 
2
หมิว
 
2
ฟ้า
 
2
พลอย
 
2
Other values (99)
99 

Length

Max length10
Median length9
Mean length4.458715596
Min length1

Characters and Unicode

Total characters486
Distinct characters49
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique99 ?
Unique (%)90.8%

Sample

1st rowคาโย
2nd rowคริสเตียน
3rd rowรัชพล
4th rowเบสท์
5th rowบิว

Common Values

ValueCountFrequency (%)
ฟ้อนต์2
 
1.8%
ปีใหม่2
 
1.8%
หมิว2
 
1.8%
ฟ้า2
 
1.8%
พลอย2
 
1.8%
ปาย1
 
0.9%
โมเม1
 
0.9%
ออน1
 
0.9%
แท็ค1
 
0.9%
วิว1
 
0.9%
Other values (94)94
86.2%

Length

2022-10-04T17:51:32.875130image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
ฟ้อนต์2
 
1.8%
หมิว2
 
1.8%
ฟ้า2
 
1.8%
พลอย2
 
1.8%
ปีใหม่2
 
1.8%
จารัส1
 
0.9%
สิงห์1
 
0.9%
ปลื้ม1
 
0.9%
เบน1
 
0.9%
หนึ่ง1
 
0.9%
Other values (94)94
86.2%

Most occurring characters

ValueCountFrequency (%)
น37
 
7.6%
ิ30
 
6.2%
ม28
 
5.8%
เ27
 
5.6%
อ22
 
4.5%
้22
 
4.5%
์21
 
4.3%
ว19
 
3.9%
า18
 
3.7%
ร15
 
3.1%
Other values (39)247
50.8%

Most occurring categories

ValueCountFrequency (%)
Other Letter364
74.9%
Nonspacing Mark121
 
24.9%
Dash Punctuation1
 
0.2%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
น37
 
10.2%
ม28
 
7.7%
เ27
 
7.4%
อ22
 
6.0%
ว19
 
5.2%
า18
 
4.9%
ร15
 
4.1%
ก15
 
4.1%
ป14
 
3.8%
ย14
 
3.8%
Other values (24)155
42.6%
Nonspacing Mark
ValueCountFrequency (%)
ิ30
24.8%
้22
18.2%
์21
17.4%
่10
 
8.3%
ี9
 
7.4%
ุ7
 
5.8%
ั7
 
5.8%
๊5
 
4.1%
ู3
 
2.5%
็2
 
1.7%
Other values (4)5
 
4.1%
Dash Punctuation
ValueCountFrequency (%)
-1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Thai485
99.8%
Common1
 
0.2%

Most frequent character per script

Thai
ValueCountFrequency (%)
น37
 
7.6%
ิ30
 
6.2%
ม28
 
5.8%
เ27
 
5.6%
อ22
 
4.5%
้22
 
4.5%
์21
 
4.3%
ว19
 
3.9%
า18
 
3.7%
ร15
 
3.1%
Other values (38)246
50.7%
Common
ValueCountFrequency (%)
-1
100.0%

Most occurring blocks

ValueCountFrequency (%)
Thai485
99.8%
ASCII1
 
0.2%

Most frequent character per block

Thai
ValueCountFrequency (%)
น37
 
7.6%
ิ30
 
6.2%
ม28
 
5.8%
เ27
 
5.6%
อ22
 
4.5%
้22
 
4.5%
์21
 
4.3%
ว19
 
3.9%
า18
 
3.7%
ร15
 
3.1%
Other values (38)246
50.7%
ASCII
ValueCountFrequency (%)
-1
100.0%

อุปกรณ์ที่ใช้ในการทำโฮมรูมครั้งนี้
Categorical

HIGH CORRELATION

Distinct3
Distinct (%)2.8%
Missing0
Missing (%)0.0%
Memory size1000.0 B
โทรศัพท์มือถือ
106 
แท็ปเล็ต
 
2
คอมพิวเตอร์ตั้งโต๊ะที่บ้าน
 
1

Length

Max length26
Median length14
Mean length14
Min length8

Characters and Unicode

Total characters1526
Distinct characters29
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1 ?
Unique (%)0.9%

Sample

1st rowโทรศัพท์มือถือ
2nd rowโทรศัพท์มือถือ
3rd rowโทรศัพท์มือถือ
4th rowโทรศัพท์มือถือ
5th rowโทรศัพท์มือถือ

Common Values

ValueCountFrequency (%)
โทรศัพท์มือถือ106
97.2%
แท็ปเล็ต2
 
1.8%
คอมพิวเตอร์ตั้งโต๊ะที่บ้าน1
 
0.9%

Length

2022-10-04T17:51:33.144131image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
Histogram of lengths of the category

Category Frequency Plot

2022-10-04T17:51:33.508950image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
ValueCountFrequency (%)
โทรศัพท์มือถือ106
97.2%
แท็ปเล็ต2
 
1.8%
คอมพิวเตอร์ตั้งโต๊ะที่บ้าน1
 
0.9%

Most occurring characters

ValueCountFrequency (%)
ท215
14.1%
อ214
14.0%
ื212
13.9%
โ107
7.0%
ร107
7.0%
ั107
7.0%
พ107
7.0%
์107
7.0%
ม107
7.0%
ศ106
6.9%
Other values (19)137
9.0%

Most occurring categories

ValueCountFrequency (%)
Other Letter1090
71.4%
Nonspacing Mark436
 
28.6%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
ท215
19.7%
อ214
19.6%
โ107
9.8%
ร107
9.8%
พ107
9.8%
ม107
9.8%
ศ106
9.7%
ถ106
9.7%
ต5
 
0.5%
เ3
 
0.3%
Other values (10)13
 
1.2%
Nonspacing Mark
ValueCountFrequency (%)
ื212
48.6%
ั107
24.5%
์107
24.5%
็4
 
0.9%
้2
 
0.5%
ิ1
 
0.2%
๊1
 
0.2%
ี1
 
0.2%
่1
 
0.2%

Most occurring scripts

ValueCountFrequency (%)
Thai1526
100.0%

Most frequent character per script

Thai
ValueCountFrequency (%)
ท215
14.1%
อ214
14.0%
ื212
13.9%
โ107
7.0%
ร107
7.0%
ั107
7.0%
พ107
7.0%
์107
7.0%
ม107
7.0%
ศ106
6.9%
Other values (19)137
9.0%

Most occurring blocks

ValueCountFrequency (%)
Thai1526
100.0%

Most frequent character per block

Thai
ValueCountFrequency (%)
ท215
14.1%
อ214
14.0%
ื212
13.9%
โ107
7.0%
ร107
7.0%
ั107
7.0%
พ107
7.0%
์107
7.0%
ม107
7.0%
ศ106
6.9%
Other values (19)137
9.0%

วันเกิด
Categorical

HIGH CARDINALITY
HIGH CORRELATION
MISSING
UNIFORM

Distinct70
Distinct (%)90.9%
Missing32
Missing (%)29.4%
Memory size1000.0 B
9/18/2549
 
2
11/21/2006
 
2
12/20/2547
 
2
12/26/2006
 
2
10/30/2004
 
2
Other values (65)
67 

Length

Max length10
Median length9
Mean length9.324675325
Min length9

Characters and Unicode

Total characters718
Distinct characters11
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique63 ?
Unique (%)81.8%

Sample

1st row4/24/2547
2nd row12/16/2004
3rd row12/20/2547
4th row11/22/2004
5th row6/28/2004

Common Values

ValueCountFrequency (%)
9/18/25492
 
1.8%
11/21/20062
 
1.8%
12/20/25472
 
1.8%
12/26/20062
 
1.8%
10/30/20042
 
1.8%
5/19/20092
 
1.8%
11/18/20062
 
1.8%
6/20/00491
 
0.9%
11/15/20061
 
0.9%
8/30/25471
 
0.9%
Other values (60)60
55.0%
(Missing)32
29.4%

Length

2022-10-04T17:51:33.782015image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
9/18/25492
 
2.6%
12/20/25472
 
2.6%
12/26/20062
 
2.6%
10/30/20042
 
2.6%
5/19/20092
 
2.6%
11/18/20062
 
2.6%
11/21/20062
 
2.6%
9/16/20221
 
1.3%
8/19/20061
 
1.3%
8/13/20061
 
1.3%
Other values (60)60
77.9%

Most occurring characters

ValueCountFrequency (%)
/154
21.4%
2139
19.4%
0130
18.1%
183
11.6%
444
 
6.1%
939
 
5.4%
539
 
5.4%
633
 
4.6%
723
 
3.2%
319
 
2.6%

Most occurring categories

ValueCountFrequency (%)
Decimal Number564
78.6%
Other Punctuation154
 
21.4%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
2139
24.6%
0130
23.0%
183
14.7%
444
 
7.8%
939
 
6.9%
539
 
6.9%
633
 
5.9%
723
 
4.1%
319
 
3.4%
815
 
2.7%
Other Punctuation
ValueCountFrequency (%)
/154
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common718
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
/154
21.4%
2139
19.4%
0130
18.1%
183
11.6%
444
 
6.1%
939
 
5.4%
539
 
5.4%
633
 
4.6%
723
 
3.2%
319
 
2.6%

Most occurring blocks

ValueCountFrequency (%)
ASCII718
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
/154
21.4%
2139
19.4%
0130
18.1%
183
11.6%
444
 
6.1%
939
 
5.4%
539
 
5.4%
633
 
4.6%
723
 
3.2%
319
 
2.6%

อ.ที่ปรึกษาคนที่ 1
Categorical

HIGH CORRELATION
MISSING

Distinct23
Distinct (%)46.0%
Missing59
Missing (%)54.1%
Memory size1000.0 B
ครูกานดา ช่วงชัย
9 
ครูไพวุฒิ ขุนซาง
4 
บุณณดา ยอดแก้ว
4 
ครูบุณณดา ยอดแก้ว
3 
ครู ไพวุฒิ ขุนซาง
3 
Other values (18)
27 

Length

Max length19
Median length18
Mean length15.68
Min length4

Characters and Unicode

Total characters784
Distinct characters34
Distinct categories5 ?
Distinct scripts2 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique12 ?
Unique (%)24.0%

Sample

1st rowครูกานดา ช่วงชัย
2nd rowครูกานดา
3rd rowนางเกศินี ทองอ่ำ
4th rowคุณครูเกศินี ทองอ่ำ
5th rowครูเกศินี ทองอ่ำ

Common Values

ValueCountFrequency (%)
ครูกานดา ช่วงชัย9
 
8.3%
ครูไพวุฒิ ขุนซาง4
 
3.7%
บุณณดา ยอดแก้ว4
 
3.7%
ครูบุณณดา ยอดแก้ว3
 
2.8%
ครู ไพวุฒิ ขุนซาง3
 
2.8%
ครู กานดา ช่วงชัย3
 
2.8%
ไพวุฒิ ขุนซาง3
 
2.8%
ครูเกศินี ทองอ่ำ3
 
2.8%
นางเกศินี ทองอ่ำ2
 
1.8%
ครู บุณณดา ยอดแก้ว2
 
1.8%
Other values (13)14
 
12.8%
(Missing)59
54.1%

Length

2022-10-04T17:51:34.042526image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
ช่วงชัย15
13.6%
ขุนซาง13
11.8%
ครู11
10.0%
ยอดแก้ว11
10.0%
ครูกานดา10
9.1%
บุณณดา8
7.3%
ไพวุฒิ7
 
6.4%
ทองอ่ำ7
 
6.4%
ครูไพวุฒิ5
 
4.5%
กานดา4
 
3.6%
Other values (13)19
17.3%

Most occurring characters

ValueCountFrequency (%)
า62
 
7.9%
62
 
7.9%
น42
 
5.4%
ด41
 
5.2%
ว40
 
5.1%
ง40
 
5.1%
ุ39
 
5.0%
ก36
 
4.6%
ค35
 
4.5%
ร35
 
4.5%
Other values (24)352
44.9%

Most occurring categories

ValueCountFrequency (%)
Other Letter567
72.3%
Nonspacing Mark152
 
19.4%
Space Separator62
 
7.9%
Other Punctuation2
 
0.3%
Format1
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
า62
 
10.9%
น42
 
7.4%
ด41
 
7.2%
ว40
 
7.1%
ง40
 
7.1%
ก36
 
6.3%
ค35
 
6.2%
ร35
 
6.2%
ช30
 
5.3%
อ30
 
5.3%
Other values (14)176
31.0%
Nonspacing Mark
ValueCountFrequency (%)
ุ39
25.7%
ู34
22.4%
่22
14.5%
ิ21
13.8%
ั15
 
9.9%
้12
 
7.9%
ี9
 
5.9%
Space Separator
ValueCountFrequency (%)
62
100.0%
Other Punctuation
ValueCountFrequency (%)
.2
100.0%
Format
ValueCountFrequency (%)
​1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Thai719
91.7%
Common65
 
8.3%

Most frequent character per script

Thai
ValueCountFrequency (%)
า62
 
8.6%
น42
 
5.8%
ด41
 
5.7%
ว40
 
5.6%
ง40
 
5.6%
ุ39
 
5.4%
ก36
 
5.0%
ค35
 
4.9%
ร35
 
4.9%
ู34
 
4.7%
Other values (21)315
43.8%
Common
ValueCountFrequency (%)
62
95.4%
.2
 
3.1%
​1
 
1.5%

Most occurring blocks

ValueCountFrequency (%)
Thai719
91.7%
ASCII64
 
8.2%
Punctuation1
 
0.1%

Most frequent character per block

Thai
ValueCountFrequency (%)
า62
 
8.6%
น42
 
5.8%
ด41
 
5.7%
ว40
 
5.6%
ง40
 
5.6%
ุ39
 
5.4%
ก36
 
5.0%
ค35
 
4.9%
ร35
 
4.9%
ู34
 
4.7%
Other values (21)315
43.8%
ASCII
ValueCountFrequency (%)
62
96.9%
.2
 
3.1%
Punctuation
ValueCountFrequency (%)
​1
100.0%

อ.ที่ปรึกษาคนที่ 2
Categorical

HIGH CORRELATION
MISSING

Distinct24
Distinct (%)48.0%
Missing59
Missing (%)54.1%
Memory size1000.0 B
ครูเกศินี ทองอ่ำ
8 
ครูกานดา ช่วงชัย
4 
ครูบุณณดา ยอดแก้ว
4 
บุณณดา ยอดแก้ว
3 
ครู ไพวุฒิ ขุนซาง
3 
Other values (19)
28 

Length

Max length22
Median length19
Mean length15.78
Min length4

Characters and Unicode

Total characters789
Distinct characters34
Distinct categories5 ?
Distinct scripts2 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique13 ?
Unique (%)26.0%

Sample

1st rowครูเกศนี ทองอ่ำ
2nd rowครูเกศินี
3rd rowนางกานดา ช่วงชัย
4th rowครูกานดา ช่วงชัย
5th rowครูกานดา ช่วงชัย

Common Values

ValueCountFrequency (%)
ครูเกศินี ทองอ่ำ8
 
7.3%
ครูกานดา ช่วงชัย4
 
3.7%
ครูบุณณดา ยอดแก้ว4
 
3.7%
บุณณดา ยอดแก้ว3
 
2.8%
ครู ไพวุฒิ ขุนซาง3
 
2.8%
ไพวุฒิ ขุนซาง3
 
2.8%
ครู เกศินี ทองอ่ำ3
 
2.8%
ครู บุณณดา ยอดแก้ว3
 
2.8%
นางเกศินี ทองอ่ำ2
 
1.8%
นางกานดา ช่วงชัย2
 
1.8%
Other values (14)15
 
13.8%
(Missing)59
54.1%

Length

2022-10-04T17:51:34.326529image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
ทองอ่ำ15
13.6%
ยอดแก้ว12
10.9%
ขุนซาง12
10.9%
ครู11
10.0%
ครูเกศินี9
8.2%
ช่วงชัย8
 
7.3%
บุณณดา7
 
6.4%
ไพวุฒิ6
 
5.5%
ครูบุณณดา5
 
4.5%
ครูกานดา4
 
3.6%
Other values (15)21
19.1%

Most occurring characters

ValueCountFrequency (%)
62
 
7.9%
า47
 
6.0%
อ45
 
5.7%
น41
 
5.2%
ง40
 
5.1%
ุ39
 
4.9%
ก37
 
4.7%
ร36
 
4.6%
ว35
 
4.4%
ค34
 
4.3%
Other values (24)373
47.3%

Most occurring categories

ValueCountFrequency (%)
Other Letter563
71.4%
Nonspacing Mark161
 
20.4%
Space Separator62
 
7.9%
Other Punctuation2
 
0.3%
Format1
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
า47
 
8.3%
อ45
 
8.0%
น41
 
7.3%
ง40
 
7.1%
ก37
 
6.6%
ร36
 
6.4%
ว35
 
6.2%
ค34
 
6.0%
ด34
 
6.0%
ณ26
 
4.6%
Other values (14)188
33.4%
Nonspacing Mark
ValueCountFrequency (%)
ุ39
24.2%
ู34
21.1%
ิ28
17.4%
่23
14.3%
ี16
9.9%
้13
 
8.1%
ั8
 
5.0%
Space Separator
ValueCountFrequency (%)
62
100.0%
Other Punctuation
ValueCountFrequency (%)
.2
100.0%
Format
ValueCountFrequency (%)
​1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Thai724
91.8%
Common65
 
8.2%

Most frequent character per script

Thai
ValueCountFrequency (%)
า47
 
6.5%
อ45
 
6.2%
น41
 
5.7%
ง40
 
5.5%
ุ39
 
5.4%
ก37
 
5.1%
ร36
 
5.0%
ว35
 
4.8%
ค34
 
4.7%
ู34
 
4.7%
Other values (21)336
46.4%
Common
ValueCountFrequency (%)
62
95.4%
.2
 
3.1%
​1
 
1.5%

Most occurring blocks

ValueCountFrequency (%)
Thai724
91.8%
ASCII64
 
8.1%
Punctuation1
 
0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
62
96.9%
.2
 
3.1%
Thai
ValueCountFrequency (%)
า47
 
6.5%
อ45
 
6.2%
น41
 
5.7%
ง40
 
5.5%
ุ39
 
5.4%
ก37
 
5.1%
ร36
 
5.0%
ว35
 
4.8%
ค34
 
4.7%
ู34
 
4.7%
Other values (21)336
46.4%
Punctuation
ValueCountFrequency (%)
​1
100.0%

Q1
Categorical

HIGH CORRELATION

Distinct9
Distinct (%)8.3%
Missing0
Missing (%)0.0%
Memory size1000.0 B
K
54 
V
30 
A
19 
K, V, A
 
1
A, K
 
1
Other values (4)
 
4

Length

Max length7
Median length1
Mean length1.220183486
Min length1

Characters and Unicode

Total characters133
Distinct characters6
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique6 ?
Unique (%)5.5%

Sample

1st rowV
2nd rowK
3rd rowV
4th rowV
5th rowA

Common Values

ValueCountFrequency (%)
K54
49.5%
V30
27.5%
A19
 
17.4%
K, V, A1
 
0.9%
A, K1
 
0.9%
K, V1
 
0.9%
V, A, K1
 
0.9%
V, K1
 
0.9%
R, K1
 
0.9%

Length

2022-10-04T17:51:34.610527image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
Histogram of lengths of the category

Category Frequency Plot

2022-10-04T17:51:34.956061image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
ValueCountFrequency (%)
k60
51.3%
v34
29.1%
a22
 
18.8%
r1
 
0.9%

Most occurring characters

ValueCountFrequency (%)
K60
45.1%
V34
25.6%
A22
 
16.5%
,8
 
6.0%
8
 
6.0%
R1
 
0.8%

Most occurring categories

ValueCountFrequency (%)
Uppercase Letter117
88.0%
Other Punctuation8
 
6.0%
Space Separator8
 
6.0%

Most frequent character per category

Uppercase Letter
ValueCountFrequency (%)
K60
51.3%
V34
29.1%
A22
 
18.8%
R1
 
0.9%
Other Punctuation
ValueCountFrequency (%)
,8
100.0%
Space Separator
ValueCountFrequency (%)
8
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin117
88.0%
Common16
 
12.0%

Most frequent character per script

Latin
ValueCountFrequency (%)
K60
51.3%
V34
29.1%
A22
 
18.8%
R1
 
0.9%
Common
ValueCountFrequency (%)
,8
50.0%
8
50.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII133
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
K60
45.1%
V34
25.6%
A22
 
16.5%
,8
 
6.0%
8
 
6.0%
R1
 
0.8%

Q2
Categorical

HIGH CORRELATION

Distinct8
Distinct (%)7.3%
Missing0
Missing (%)0.0%
Memory size1000.0 B
R
60 
A
24 
V
14 
K
 
6
A, R
 
2
Other values (3)
 
3

Length

Max length4
Median length1
Mean length1.137614679
Min length1

Characters and Unicode

Total characters124
Distinct characters6
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique3 ?
Unique (%)2.8%

Sample

1st rowA
2nd rowA
3rd rowR
4th rowR
5th rowR

Common Values

ValueCountFrequency (%)
R60
55.0%
A24
 
22.0%
V14
 
12.8%
K6
 
5.5%
A, R2
 
1.8%
V, A1
 
0.9%
V, R1
 
0.9%
K, R1
 
0.9%

Length

2022-10-04T17:51:35.456936image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
Histogram of lengths of the category

Category Frequency Plot

2022-10-04T17:51:35.906565image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
ValueCountFrequency (%)
r64
56.1%
a27
23.7%
v16
 
14.0%
k7
 
6.1%

Most occurring characters

ValueCountFrequency (%)
R64
51.6%
A27
21.8%
V16
 
12.9%
K7
 
5.6%
,5
 
4.0%
5
 
4.0%

Most occurring categories

ValueCountFrequency (%)
Uppercase Letter114
91.9%
Other Punctuation5
 
4.0%
Space Separator5
 
4.0%

Most frequent character per category

Uppercase Letter
ValueCountFrequency (%)
R64
56.1%
A27
23.7%
V16
 
14.0%
K7
 
6.1%
Other Punctuation
ValueCountFrequency (%)
,5
100.0%
Space Separator
ValueCountFrequency (%)
5
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin114
91.9%
Common10
 
8.1%

Most frequent character per script

Latin
ValueCountFrequency (%)
R64
56.1%
A27
23.7%
V16
 
14.0%
K7
 
6.1%
Common
ValueCountFrequency (%)
,5
50.0%
5
50.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII124
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
R64
51.6%
A27
21.8%
V16
 
12.9%
K7
 
5.6%
,5
 
4.0%
5
 
4.0%

Q3
Categorical

HIGH CORRELATION

Distinct8
Distinct (%)7.3%
Missing0
Missing (%)0.0%
Memory size1000.0 B
K
47 
V
29 
A
23 
V, A
 
3
A, K
 
3
Other values (3)
 
4

Length

Max length7
Median length1
Mean length1.247706422
Min length1

Characters and Unicode

Total characters136
Distinct characters6
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique2 ?
Unique (%)1.8%

Sample

1st rowA
2nd rowK
3rd rowK
4th rowV
5th rowA

Common Values

ValueCountFrequency (%)
K47
43.1%
V29
26.6%
A23
21.1%
V, A3
 
2.8%
A, K3
 
2.8%
R2
 
1.8%
V, A, K1
 
0.9%
V, K1
 
0.9%

Length

2022-10-04T17:51:36.195093image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
Histogram of lengths of the category

Category Frequency Plot

2022-10-04T17:51:36.612368image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
ValueCountFrequency (%)
k52
44.1%
v34
28.8%
a30
25.4%
r2
 
1.7%

Most occurring characters

ValueCountFrequency (%)
K52
38.2%
V34
25.0%
A30
22.1%
,9
 
6.6%
9
 
6.6%
R2
 
1.5%

Most occurring categories

ValueCountFrequency (%)
Uppercase Letter118
86.8%
Other Punctuation9
 
6.6%
Space Separator9
 
6.6%

Most frequent character per category

Uppercase Letter
ValueCountFrequency (%)
K52
44.1%
V34
28.8%
A30
25.4%
R2
 
1.7%
Other Punctuation
ValueCountFrequency (%)
,9
100.0%
Space Separator
ValueCountFrequency (%)
9
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin118
86.8%
Common18
 
13.2%

Most frequent character per script

Latin
ValueCountFrequency (%)
K52
44.1%
V34
28.8%
A30
25.4%
R2
 
1.7%
Common
ValueCountFrequency (%)
,9
50.0%
9
50.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII136
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
K52
38.2%
V34
25.0%
A30
22.1%
,9
 
6.6%
9
 
6.6%
R2
 
1.5%

Q4
Categorical

HIGH CORRELATION

Distinct12
Distinct (%)11.0%
Missing0
Missing (%)0.0%
Memory size1000.0 B
R
58 
A
23 
K
14 
V
 
5
V, K
 
2
Other values (7)
7 

Length

Max length7
Median length1
Mean length1.302752294
Min length1

Characters and Unicode

Total characters142
Distinct characters6
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique7 ?
Unique (%)6.4%

Sample

1st rowR
2nd rowA
3rd rowR
4th rowR
5th rowR

Common Values

ValueCountFrequency (%)
R58
53.2%
A23
 
21.1%
K14
 
12.8%
V5
 
4.6%
V, K2
 
1.8%
A, R1
 
0.9%
K, V1
 
0.9%
V, A1
 
0.9%
V, R1
 
0.9%
A, K, R1
 
0.9%
Other values (2)2
 
1.8%

Length

2022-10-04T17:51:36.988369image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
r63
52.5%
a26
21.7%
k20
 
16.7%
v11
 
9.2%

Most occurring characters

ValueCountFrequency (%)
R63
44.4%
A26
18.3%
K20
 
14.1%
V11
 
7.7%
,11
 
7.7%
11
 
7.7%

Most occurring categories

ValueCountFrequency (%)
Uppercase Letter120
84.5%
Other Punctuation11
 
7.7%
Space Separator11
 
7.7%

Most frequent character per category

Uppercase Letter
ValueCountFrequency (%)
R63
52.5%
A26
21.7%
K20
 
16.7%
V11
 
9.2%
Other Punctuation
ValueCountFrequency (%)
,11
100.0%
Space Separator
ValueCountFrequency (%)
11
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin120
84.5%
Common22
 
15.5%

Most frequent character per script

Latin
ValueCountFrequency (%)
R63
52.5%
A26
21.7%
K20
 
16.7%
V11
 
9.2%
Common
ValueCountFrequency (%)
,11
50.0%
11
50.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII142
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
R63
44.4%
A26
18.3%
K20
 
14.1%
V11
 
7.7%
,11
 
7.7%
11
 
7.7%

Q5
Categorical

HIGH CORRELATION

Distinct10
Distinct (%)9.2%
Missing0
Missing (%)0.0%
Memory size1000.0 B
K
41 
R
23 
A
21 
V
15 
K, R
 
3
Other values (5)
6 

Length

Max length4
Median length1
Mean length1.247706422
Min length1

Characters and Unicode

Total characters136
Distinct characters6
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique4 ?
Unique (%)3.7%

Sample

1st rowK
2nd rowK
3rd rowR
4th rowA
5th rowR

Common Values

ValueCountFrequency (%)
K41
37.6%
R23
21.1%
A21
19.3%
V15
 
13.8%
K, R3
 
2.8%
V, A2
 
1.8%
K, V1
 
0.9%
A, K1
 
0.9%
V, K1
 
0.9%
A, V1
 
0.9%

Length

2022-10-04T17:51:37.289802image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
Histogram of lengths of the category

Category Frequency Plot

2022-10-04T17:51:37.706554image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
ValueCountFrequency (%)
k47
39.8%
r26
22.0%
a25
21.2%
v20
16.9%

Most occurring characters

ValueCountFrequency (%)
K47
34.6%
R26
19.1%
A25
18.4%
V20
14.7%
,9
 
6.6%
9
 
6.6%

Most occurring categories

ValueCountFrequency (%)
Uppercase Letter118
86.8%
Other Punctuation9
 
6.6%
Space Separator9
 
6.6%

Most frequent character per category

Uppercase Letter
ValueCountFrequency (%)
K47
39.8%
R26
22.0%
A25
21.2%
V20
16.9%
Other Punctuation
ValueCountFrequency (%)
,9
100.0%
Space Separator
ValueCountFrequency (%)
9
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin118
86.8%
Common18
 
13.2%

Most frequent character per script

Latin
ValueCountFrequency (%)
K47
39.8%
R26
22.0%
A25
21.2%
V20
16.9%
Common
ValueCountFrequency (%)
,9
50.0%
9
50.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII136
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
K47
34.6%
R26
19.1%
A25
18.4%
V20
14.7%
,9
 
6.6%
9
 
6.6%

Q6
Categorical

HIGH CORRELATION

Distinct12
Distinct (%)11.0%
Missing0
Missing (%)0.0%
Memory size1000.0 B
R
55 
K
19 
V
13 
A
7 
K, R
6 
Other values (7)
9 

Length

Max length10
Median length1
Mean length1.52293578
Min length1

Characters and Unicode

Total characters166
Distinct characters6
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique5 ?
Unique (%)4.6%

Sample

1st rowK
2nd rowV
3rd rowR
4th rowR
5th rowR

Common Values

ValueCountFrequency (%)
R55
50.5%
K19
 
17.4%
V13
 
11.9%
A7
 
6.4%
K, R6
 
5.5%
R, A2
 
1.8%
R, K2
 
1.8%
V, R1
 
0.9%
R, A, V1
 
0.9%
V, A, R1
 
0.9%
Other values (2)2
 
1.8%

Length

2022-10-04T17:51:38.084550image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
r69
53.9%
k29
22.7%
v18
 
14.1%
a12
 
9.4%

Most occurring characters

ValueCountFrequency (%)
R69
41.6%
K29
17.5%
,19
 
11.4%
19
 
11.4%
V18
 
10.8%
A12
 
7.2%

Most occurring categories

ValueCountFrequency (%)
Uppercase Letter128
77.1%
Other Punctuation19
 
11.4%
Space Separator19
 
11.4%

Most frequent character per category

Uppercase Letter
ValueCountFrequency (%)
R69
53.9%
K29
22.7%
V18
 
14.1%
A12
 
9.4%
Other Punctuation
ValueCountFrequency (%)
,19
100.0%
Space Separator
ValueCountFrequency (%)
19
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin128
77.1%
Common38
 
22.9%

Most frequent character per script

Latin
ValueCountFrequency (%)
R69
53.9%
K29
22.7%
V18
 
14.1%
A12
 
9.4%
Common
ValueCountFrequency (%)
,19
50.0%
19
50.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII166
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
R69
41.6%
K29
17.5%
,19
 
11.4%
19
 
11.4%
V18
 
10.8%
A12
 
7.2%

Q7
Categorical

HIGH CORRELATION

Distinct13
Distinct (%)11.9%
Missing0
Missing (%)0.0%
Memory size1000.0 B
R
61 
K
20 
V
11 
R, K
 
4
A
 
3
Other values (8)
10 

Length

Max length7
Median length1
Mean length1.412844037
Min length1

Characters and Unicode

Total characters154
Distinct characters6
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique7 ?
Unique (%)6.4%

Sample

1st rowR
2nd rowR
3rd rowR
4th rowR
5th rowK

Common Values

ValueCountFrequency (%)
R61
56.0%
K20
 
18.3%
V11
 
10.1%
R, K4
 
3.7%
A3
 
2.8%
K, R3
 
2.8%
R, A1
 
0.9%
V, A1
 
0.9%
R, V1
 
0.9%
V, K1
 
0.9%
Other values (3)3
 
2.8%

Length

2022-10-04T17:51:38.326550image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
r71
57.3%
k30
24.2%
v17
 
13.7%
a6
 
4.8%

Most occurring characters

ValueCountFrequency (%)
R71
46.1%
K30
19.5%
V17
 
11.0%
,15
 
9.7%
15
 
9.7%
A6
 
3.9%

Most occurring categories

ValueCountFrequency (%)
Uppercase Letter124
80.5%
Other Punctuation15
 
9.7%
Space Separator15
 
9.7%

Most frequent character per category

Uppercase Letter
ValueCountFrequency (%)
R71
57.3%
K30
24.2%
V17
 
13.7%
A6
 
4.8%
Other Punctuation
ValueCountFrequency (%)
,15
100.0%
Space Separator
ValueCountFrequency (%)
15
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin124
80.5%
Common30
 
19.5%

Most frequent character per script

Latin
ValueCountFrequency (%)
R71
57.3%
K30
24.2%
V17
 
13.7%
A6
 
4.8%
Common
ValueCountFrequency (%)
,15
50.0%
15
50.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII154
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
R71
46.1%
K30
19.5%
V17
 
11.0%
,15
 
9.7%
15
 
9.7%
A6
 
3.9%

Q8
Categorical

HIGH CORRELATION

Distinct11
Distinct (%)10.1%
Missing0
Missing (%)0.0%
Memory size1000.0 B
K
46 
V
33 
A
15 
R
6 
K, V
 
3
Other values (6)
6 

Length

Max length10
Median length1
Mean length1.357798165
Min length1

Characters and Unicode

Total characters148
Distinct characters6
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique6 ?
Unique (%)5.5%

Sample

1st rowK
2nd rowA
3rd rowK
4th rowV
5th rowV

Common Values

ValueCountFrequency (%)
K46
42.2%
V33
30.3%
A15
 
13.8%
R6
 
5.5%
K, V3
 
2.8%
K, A, R, V1
 
0.9%
V, A1
 
0.9%
R, K1
 
0.9%
A, R, K, V1
 
0.9%
K, A1
 
0.9%

Length

2022-10-04T17:51:38.572058image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
k53
43.4%
v39
32.0%
a20
 
16.4%
r10
 
8.2%

Most occurring characters

ValueCountFrequency (%)
K53
35.8%
V39
26.4%
A20
 
13.5%
,13
 
8.8%
13
 
8.8%
R10
 
6.8%

Most occurring categories

ValueCountFrequency (%)
Uppercase Letter122
82.4%
Other Punctuation13
 
8.8%
Space Separator13
 
8.8%

Most frequent character per category

Uppercase Letter
ValueCountFrequency (%)
K53
43.4%
V39
32.0%
A20
 
16.4%
R10
 
8.2%
Other Punctuation
ValueCountFrequency (%)
,13
100.0%
Space Separator
ValueCountFrequency (%)
13
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin122
82.4%
Common26
 
17.6%

Most frequent character per script

Latin
ValueCountFrequency (%)
K53
43.4%
V39
32.0%
A20
 
16.4%
R10
 
8.2%
Common
ValueCountFrequency (%)
,13
50.0%
13
50.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII148
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
K53
35.8%
V39
26.4%
A20
 
13.5%
,13
 
8.8%
13
 
8.8%
R10
 
6.8%

Q9
Categorical

HIGH CORRELATION

Distinct13
Distinct (%)11.9%
Missing0
Missing (%)0.0%
Memory size1000.0 B
R
60 
A
15 
K
12 
V
8 
V, R
 
3
Other values (8)
11 

Length

Max length10
Median length1
Mean length1.550458716
Min length1

Characters and Unicode

Total characters169
Distinct characters6
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique5 ?
Unique (%)4.6%

Sample

1st rowR
2nd rowK
3rd rowR
4th rowR
5th rowR

Common Values

ValueCountFrequency (%)
R60
55.0%
A15
 
13.8%
K12
 
11.0%
V8
 
7.3%
V, R3
 
2.8%
R, V2
 
1.8%
R, A2
 
1.8%
K, R2
 
1.8%
V, A, K, R1
 
0.9%
K, A, V, R1
 
0.9%
Other values (3)3
 
2.8%

Length

2022-10-04T17:51:38.858136image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
r74
57.4%
a19
 
14.7%
k19
 
14.7%
v17
 
13.2%

Most occurring characters

ValueCountFrequency (%)
R74
43.8%
,20
 
11.8%
20
 
11.8%
A19
 
11.2%
K19
 
11.2%
V17
 
10.1%

Most occurring categories

ValueCountFrequency (%)
Uppercase Letter129
76.3%
Other Punctuation20
 
11.8%
Space Separator20
 
11.8%

Most frequent character per category

Uppercase Letter
ValueCountFrequency (%)
R74
57.4%
A19
 
14.7%
K19
 
14.7%
V17
 
13.2%
Other Punctuation
ValueCountFrequency (%)
,20
100.0%
Space Separator
ValueCountFrequency (%)
20
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin129
76.3%
Common40
 
23.7%

Most frequent character per script

Latin
ValueCountFrequency (%)
R74
57.4%
A19
 
14.7%
K19
 
14.7%
V17
 
13.2%
Common
ValueCountFrequency (%)
,20
50.0%
20
50.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII169
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
R74
43.8%
,20
 
11.8%
20
 
11.8%
A19
 
11.2%
K19
 
11.2%
V17
 
10.1%

Q10
Categorical

HIGH CORRELATION

Distinct16
Distinct (%)14.7%
Missing0
Missing (%)0.0%
Memory size1000.0 B
V
45 
K
23 
A
17 
R
10 
A, K
 
2
Other values (11)
12 

Length

Max length10
Median length1
Mean length1.605504587
Min length1

Characters and Unicode

Total characters175
Distinct characters6
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique10 ?
Unique (%)9.2%

Sample

1st rowA
2nd rowV
3rd rowR
4th rowV
5th rowR

Common Values

ValueCountFrequency (%)
V45
41.3%
K23
21.1%
A17
 
15.6%
R10
 
9.2%
A, K2
 
1.8%
K, V2
 
1.8%
A, K, V1
 
0.9%
V, R, K, A1
 
0.9%
V, R, A1
 
0.9%
K, V, R, A1
 
0.9%
Other values (6)6
 
5.5%

Length

2022-10-04T17:51:39.078137image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
v54
41.2%
k33
25.2%
a27
20.6%
r17
 
13.0%

Most occurring characters

ValueCountFrequency (%)
V54
30.9%
K33
18.9%
A27
15.4%
,22
12.6%
22
12.6%
R17
 
9.7%

Most occurring categories

ValueCountFrequency (%)
Uppercase Letter131
74.9%
Other Punctuation22
 
12.6%
Space Separator22
 
12.6%

Most frequent character per category

Uppercase Letter
ValueCountFrequency (%)
V54
41.2%
K33
25.2%
A27
20.6%
R17
 
13.0%
Other Punctuation
ValueCountFrequency (%)
,22
100.0%
Space Separator
ValueCountFrequency (%)
22
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin131
74.9%
Common44
 
25.1%

Most frequent character per script

Latin
ValueCountFrequency (%)
V54
41.2%
K33
25.2%
A27
20.6%
R17
 
13.0%
Common
ValueCountFrequency (%)
,22
50.0%
22
50.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII175
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
V54
30.9%
K33
18.9%
A27
15.4%
,22
12.6%
22
12.6%
R17
 
9.7%

Q11
Categorical

HIGH CORRELATION

Distinct9
Distinct (%)8.3%
Missing0
Missing (%)0.0%
Memory size1000.0 B
A
51 
V
25 
R
12 
K
7 
A, V
 
5
Other values (4)
9 

Length

Max length4
Median length1
Mean length1.385321101
Min length1

Characters and Unicode

Total characters151
Distinct characters6
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1 ?
Unique (%)0.9%

Sample

1st rowA
2nd rowA
3rd rowA
4th rowV
5th rowV

Common Values

ValueCountFrequency (%)
A51
46.8%
V25
22.9%
R12
 
11.0%
K7
 
6.4%
A, V5
 
4.6%
A, R3
 
2.8%
V, A3
 
2.8%
R, A2
 
1.8%
K, A1
 
0.9%

Length

2022-10-04T17:51:39.295081image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
Histogram of lengths of the category

Category Frequency Plot

2022-10-04T17:51:40.163798image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
ValueCountFrequency (%)
a65
52.8%
v33
26.8%
r17
 
13.8%
k8
 
6.5%

Most occurring characters

ValueCountFrequency (%)
A65
43.0%
V33
21.9%
R17
 
11.3%
,14
 
9.3%
14
 
9.3%
K8
 
5.3%

Most occurring categories

ValueCountFrequency (%)
Uppercase Letter123
81.5%
Other Punctuation14
 
9.3%
Space Separator14
 
9.3%

Most frequent character per category

Uppercase Letter
ValueCountFrequency (%)
A65
52.8%
V33
26.8%
R17
 
13.8%
K8
 
6.5%
Other Punctuation
ValueCountFrequency (%)
,14
100.0%
Space Separator
ValueCountFrequency (%)
14
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin123
81.5%
Common28
 
18.5%

Most frequent character per script

Latin
ValueCountFrequency (%)
A65
52.8%
V33
26.8%
R17
 
13.8%
K8
 
6.5%
Common
ValueCountFrequency (%)
,14
50.0%
14
50.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII151
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
A65
43.0%
V33
21.9%
R17
 
11.3%
,14
 
9.3%
14
 
9.3%
K8
 
5.3%

Q12
Categorical

HIGH CORRELATION

Distinct13
Distinct (%)11.9%
Missing0
Missing (%)0.0%
Memory size1000.0 B
K
45 
R
27 
A
13 
V
10 
R, K
 
3
Other values (8)
11 

Length

Max length10
Median length1
Mean length1.495412844
Min length1

Characters and Unicode

Total characters163
Distinct characters6
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique5 ?
Unique (%)4.6%

Sample

1st rowR
2nd rowK
3rd rowR
4th rowA
5th rowA

Common Values

ValueCountFrequency (%)
K45
41.3%
R27
24.8%
A13
 
11.9%
V10
 
9.2%
R, K3
 
2.8%
R, K, V2
 
1.8%
K, R2
 
1.8%
K, A2
 
1.8%
A, K1
 
0.9%
V, A1
 
0.9%
Other values (3)3
 
2.8%

Length

2022-10-04T17:51:40.582128image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
k56
44.1%
r36
28.3%
a19
 
15.0%
v16
 
12.6%

Most occurring characters

ValueCountFrequency (%)
K56
34.4%
R36
22.1%
A19
 
11.7%
,18
 
11.0%
18
 
11.0%
V16
 
9.8%

Most occurring categories

ValueCountFrequency (%)
Uppercase Letter127
77.9%
Other Punctuation18
 
11.0%
Space Separator18
 
11.0%

Most frequent character per category

Uppercase Letter
ValueCountFrequency (%)
K56
44.1%
R36
28.3%
A19
 
15.0%
V16
 
12.6%
Other Punctuation
ValueCountFrequency (%)
,18
100.0%
Space Separator
ValueCountFrequency (%)
18
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin127
77.9%
Common36
 
22.1%

Most frequent character per script

Latin
ValueCountFrequency (%)
K56
44.1%
R36
28.3%
A19
 
15.0%
V16
 
12.6%
Common
ValueCountFrequency (%)
,18
50.0%
18
50.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII163
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
K56
34.4%
R36
22.1%
A19
 
11.7%
,18
 
11.0%
18
 
11.0%
V16
 
9.8%

Q13
Categorical

HIGH CORRELATION

Distinct10
Distinct (%)9.2%
Missing0
Missing (%)0.0%
Memory size1000.0 B
A
68 
​K
20 
A, ​K
 
5
R
 
5
V
 
5
Other values (5)
 
6

Length

Max length8
Median length1
Mean length1.623853211
Min length1

Characters and Unicode

Total characters177
Distinct characters7
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique4 ?
Unique (%)3.7%

Sample

1st row​K
2nd row​K
3rd row​K
4th rowA
5th rowA

Common Values

ValueCountFrequency (%)
A68
62.4%
​K20
 
18.3%
A, ​K5
 
4.6%
R5
 
4.6%
V5
 
4.6%
​K, A2
 
1.8%
A, R1
 
0.9%
​K, V, A1
 
0.9%
​K, A, V1
 
0.9%
V, A1
 
0.9%

Length

2022-10-04T17:51:40.964333image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
Histogram of lengths of the category

Category Frequency Plot

2022-10-04T17:51:41.523234image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
ValueCountFrequency (%)
a79
64.8%
​k29
 
23.8%
v8
 
6.6%
r6
 
4.9%

Most occurring characters

ValueCountFrequency (%)
A79
44.6%
​29
 
16.4%
K29
 
16.4%
,13
 
7.3%
13
 
7.3%
V8
 
4.5%
R6
 
3.4%

Most occurring categories

ValueCountFrequency (%)
Uppercase Letter122
68.9%
Format29
 
16.4%
Other Punctuation13
 
7.3%
Space Separator13
 
7.3%

Most frequent character per category

Uppercase Letter
ValueCountFrequency (%)
A79
64.8%
K29
 
23.8%
V8
 
6.6%
R6
 
4.9%
Format
ValueCountFrequency (%)
​29
100.0%
Other Punctuation
ValueCountFrequency (%)
,13
100.0%
Space Separator
ValueCountFrequency (%)
13
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin122
68.9%
Common55
31.1%

Most frequent character per script

Latin
ValueCountFrequency (%)
A79
64.8%
K29
 
23.8%
V8
 
6.6%
R6
 
4.9%
Common
ValueCountFrequency (%)
​29
52.7%
,13
23.6%
13
23.6%

Most occurring blocks

ValueCountFrequency (%)
ASCII148
83.6%
Punctuation29
 
16.4%

Most frequent character per block

ASCII
ValueCountFrequency (%)
A79
53.4%
K29
 
19.6%
,13
 
8.8%
13
 
8.8%
V8
 
5.4%
R6
 
4.1%
Punctuation
ValueCountFrequency (%)
​29
100.0%

Q14
Categorical

HIGH CORRELATION

Distinct9
Distinct (%)8.3%
Missing0
Missing (%)0.0%
Memory size1000.0 B
R
30 
K
29 
A
25 
V
17 
R, K
 
3
Other values (4)
5 

Length

Max length7
Median length1
Mean length1.275229358
Min length1

Characters and Unicode

Total characters139
Distinct characters6
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique3 ?
Unique (%)2.8%

Sample

1st rowK
2nd rowA
3rd rowR
4th rowK
5th rowA

Common Values

ValueCountFrequency (%)
R30
27.5%
K29
26.6%
A25
22.9%
V17
15.6%
R, K3
 
2.8%
R, V2
 
1.8%
K, R, A1
 
0.9%
R, V, K1
 
0.9%
A, V1
 
0.9%

Length

2022-10-04T17:51:41.959054image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
Histogram of lengths of the category

Category Frequency Plot

2022-10-04T17:51:42.251049image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
ValueCountFrequency (%)
r37
31.1%
k34
28.6%
a27
22.7%
v21
17.6%

Most occurring characters

ValueCountFrequency (%)
R37
26.6%
K34
24.5%
A27
19.4%
V21
15.1%
,10
 
7.2%
10
 
7.2%

Most occurring categories

ValueCountFrequency (%)
Uppercase Letter119
85.6%
Other Punctuation10
 
7.2%
Space Separator10
 
7.2%

Most frequent character per category

Uppercase Letter
ValueCountFrequency (%)
R37
31.1%
K34
28.6%
A27
22.7%
V21
17.6%
Other Punctuation
ValueCountFrequency (%)
,10
100.0%
Space Separator
ValueCountFrequency (%)
10
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin119
85.6%
Common20
 
14.4%

Most frequent character per script

Latin
ValueCountFrequency (%)
R37
31.1%
K34
28.6%
A27
22.7%
V21
17.6%
Common
ValueCountFrequency (%)
,10
50.0%
10
50.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII139
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
R37
26.6%
K34
24.5%
A27
19.4%
V21
15.1%
,10
 
7.2%
10
 
7.2%

Q15
Categorical

HIGH CORRELATION

Distinct12
Distinct (%)11.0%
Missing0
Missing (%)0.0%
Memory size1000.0 B
A
35 
K
32 
V
20 
R
10 
A, K
 
2
Other values (7)
10 

Length

Max length7
Median length1
Mean length1.385321101
Min length1

Characters and Unicode

Total characters151
Distinct characters6
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique4 ?
Unique (%)3.7%

Sample

1st rowA
2nd rowA
3rd rowK
4th rowV
5th rowV

Common Values

ValueCountFrequency (%)
A35
32.1%
K32
29.4%
V20
18.3%
R10
 
9.2%
A, K2
 
1.8%
K, A2
 
1.8%
V, K2
 
1.8%
A, V2
 
1.8%
K, V, R1
 
0.9%
V, A1
 
0.9%
Other values (2)2
 
1.8%

Length

2022-10-04T17:51:42.553048image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
a43
35.0%
k41
33.3%
v27
22.0%
r12
 
9.8%

Most occurring characters

ValueCountFrequency (%)
A43
28.5%
K41
27.2%
V27
17.9%
,14
 
9.3%
14
 
9.3%
R12
 
7.9%

Most occurring categories

ValueCountFrequency (%)
Uppercase Letter123
81.5%
Other Punctuation14
 
9.3%
Space Separator14
 
9.3%

Most frequent character per category

Uppercase Letter
ValueCountFrequency (%)
A43
35.0%
K41
33.3%
V27
22.0%
R12
 
9.8%
Other Punctuation
ValueCountFrequency (%)
,14
100.0%
Space Separator
ValueCountFrequency (%)
14
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin123
81.5%
Common28
 
18.5%

Most frequent character per script

Latin
ValueCountFrequency (%)
A43
35.0%
K41
33.3%
V27
22.0%
R12
 
9.8%
Common
ValueCountFrequency (%)
,14
50.0%
14
50.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII151
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
A43
28.5%
K41
27.2%
V27
17.9%
,14
 
9.3%
14
 
9.3%
R12
 
7.9%

Q16
Categorical

HIGH CORRELATION

Distinct10
Distinct (%)9.2%
Missing0
Missing (%)0.0%
Memory size1000.0 B
A
67 
V
18 
K
10 
R
 
6
A, V
 
3
Other values (5)
 
5

Length

Max length7
Median length1
Mean length1.247706422
Min length1

Characters and Unicode

Total characters136
Distinct characters6
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique5 ?
Unique (%)4.6%

Sample

1st rowA
2nd rowA
3rd rowA
4th rowA
5th rowA

Common Values

ValueCountFrequency (%)
A67
61.5%
V18
 
16.5%
K10
 
9.2%
R6
 
5.5%
A, V3
 
2.8%
A, R1
 
0.9%
V, A1
 
0.9%
A, K1
 
0.9%
R, V, A1
 
0.9%
R, A1
 
0.9%

Length

2022-10-04T17:51:42.817052image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
Histogram of lengths of the category

Category Frequency Plot

2022-10-04T17:51:43.121051image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
ValueCountFrequency (%)
a75
63.6%
v23
 
19.5%
k11
 
9.3%
r9
 
7.6%

Most occurring characters

ValueCountFrequency (%)
A75
55.1%
V23
 
16.9%
K11
 
8.1%
R9
 
6.6%
,9
 
6.6%
9
 
6.6%

Most occurring categories

ValueCountFrequency (%)
Uppercase Letter118
86.8%
Other Punctuation9
 
6.6%
Space Separator9
 
6.6%

Most frequent character per category

Uppercase Letter
ValueCountFrequency (%)
A75
63.6%
V23
 
19.5%
K11
 
9.3%
R9
 
7.6%
Other Punctuation
ValueCountFrequency (%)
,9
100.0%
Space Separator
ValueCountFrequency (%)
9
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin118
86.8%
Common18
 
13.2%

Most frequent character per script

Latin
ValueCountFrequency (%)
A75
63.6%
V23
 
19.5%
K11
 
9.3%
R9
 
7.6%
Common
ValueCountFrequency (%)
,9
50.0%
9
50.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII136
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
A75
55.1%
V23
 
16.9%
K11
 
8.1%
R9
 
6.6%
,9
 
6.6%
9
 
6.6%

กับการเริ่มต้นเรียนในปีการศึกษา 2565 .. ภาพฝันของเรา 1 ปีต่อจากนี้เป็นอย่างไร ? บอกได้เต็มที่เลยนะ
Categorical

HIGH CARDINALITY
UNIFORM

Distinct108
Distinct (%)99.1%
Missing0
Missing (%)0.0%
Memory size1000.0 B
-
 
2
ดีขึ้น
 
1
เรียนให้ประสบความสำเร็จดังใจหวัง
 
1
ขยันมากกว่านี้และใฝ่หาความรู้อยู่เสมอ
 
1
น่าจะดีกว่าเดิม
 
1
Other values (103)
103 

Length

Max length256
Median length79
Mean length48.30275229
Min length1

Characters and Unicode

Total characters5265
Distinct characters85
Distinct categories12 ?
Distinct scripts3 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique107 ?
Unique (%)98.2%

Sample

1st rowมีงานทำ โดยไม่รบกวนการเรียน
2nd rowดีขึ้นกว่าวันนี้
3rd row-
4th rowมีงานทำ ควบคู่กับการเรียน
5th rowอยากจะกลายเป็นนักเทรดที่สามารถวิเคราะห์กราฟและข้อมูลและทราบข่าวต่างๆได้ทันโลกโดยนำมาประกอบการเทรดและอยากจะมีเพื่อนร่วมทีมที่ชอบในด้านเดียวกันช่วยกันวิเคราะห์และไปถึงฝั่งฝันด้วยกัน

Common Values

ValueCountFrequency (%)
-2
 
1.8%
ดีขึ้น1
 
0.9%
เรียนให้ประสบความสำเร็จดังใจหวัง1
 
0.9%
ขยันมากกว่านี้และใฝ่หาความรู้อยู่เสมอ1
 
0.9%
น่าจะดีกว่าเดิม1
 
0.9%
มีเงินทำงานพร้อมเรียน1
 
0.9%
มีเป้าหมายเก็บเงินจากการทำงานเเล้วมาสร้างบ้านให้ปู่กับย่า1
 
0.9%
เหนื่อยมากๆ1
 
0.9%
การบ้านน้อย ให้อิสระในการเลือกที่จะเข้าแถวหรือไม่เข้าแถว ให้อิสระตัดสินใจ1
 
0.9%
จะมีการเรียนที่ดี1
 
0.9%
Other values (98)98
89.9%

Length

2022-10-04T17:51:43.561568image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
เรียนอย่างมีความสุข3
 
1.4%
2
 
0.9%
ก็ดีค่ะ2
 
0.9%
ติดมหาลัย2
 
0.9%
ร2
 
0.9%
มีงานทำ2
 
0.9%
เรียนดีขึ้น1
 
0.5%
การบ้านน้อยกว่านี้1
 
0.5%
มีเป้าหมายในชีวิต1
 
0.5%
ขอเเค่ให้ตัวเองเรียนจบอย่างมีความสุขเเละสบายใจ1
 
0.5%
Other values (201)201
92.2%

Most occurring characters

ValueCountFrequency (%)
า357
 
6.8%
น325
 
6.2%
เ268
 
5.1%
่260
 
4.9%
ร237
 
4.5%
ม234
 
4.4%
ก231
 
4.4%
ี229
 
4.3%
้229
 
4.3%
ย219
 
4.2%
Other values (75)2676
50.8%

Most occurring categories

ValueCountFrequency (%)
Other Letter3924
74.5%
Nonspacing Mark1145
 
21.7%
Space Separator114
 
2.2%
Lowercase Letter30
 
0.6%
Modifier Letter23
 
0.4%
Decimal Number14
 
0.3%
Control4
 
0.1%
Other Punctuation4
 
0.1%
Dash Punctuation3
 
0.1%
Modifier Symbol2
 
< 0.1%
Other values (2)2
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
า357
 
9.1%
น325
 
8.3%
เ268
 
6.8%
ร237
 
6.0%
ม234
 
6.0%
ก231
 
5.9%
ย219
 
5.6%
อ205
 
5.2%
ว159
 
4.1%
ด145
 
3.7%
Other values (35)1544
39.3%
Lowercase Letter
ValueCountFrequency (%)
o6
20.0%
t4
13.3%
e3
10.0%
l3
10.0%
k2
 
6.7%
p2
 
6.7%
i2
 
6.7%
h2
 
6.7%
m1
 
3.3%
f1
 
3.3%
Other values (4)4
13.3%
Nonspacing Mark
ValueCountFrequency (%)
่260
22.7%
ี229
20.0%
้229
20.0%
ั131
11.4%
ิ84
 
7.3%
็45
 
3.9%
ึ45
 
3.9%
ื39
 
3.4%
ู38
 
3.3%
ุ32
 
2.8%
Other values (2)13
 
1.1%
Decimal Number
ValueCountFrequency (%)
05
35.7%
43
21.4%
32
 
14.3%
12
 
14.3%
51
 
7.1%
61
 
7.1%
Space Separator
ValueCountFrequency (%)
114
100.0%
Modifier Letter
ValueCountFrequency (%)
ๆ23
100.0%
Control
ValueCountFrequency (%)
4
100.0%
Other Punctuation
ValueCountFrequency (%)
.4
100.0%
Dash Punctuation
ValueCountFrequency (%)
-3
100.0%
Modifier Symbol
ValueCountFrequency (%)
^2
100.0%
Format
ValueCountFrequency (%)
​1
100.0%
Uppercase Letter
ValueCountFrequency (%)
S1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Thai5092
96.7%
Common142
 
2.7%
Latin31
 
0.6%

Most frequent character per script

Thai
ValueCountFrequency (%)
า357
 
7.0%
น325
 
6.4%
เ268
 
5.3%
่260
 
5.1%
ร237
 
4.7%
ม234
 
4.6%
ก231
 
4.5%
ี229
 
4.5%
้229
 
4.5%
ย219
 
4.3%
Other values (48)2503
49.2%
Latin
ValueCountFrequency (%)
o6
19.4%
t4
12.9%
e3
9.7%
l3
9.7%
k2
 
6.5%
p2
 
6.5%
i2
 
6.5%
h2
 
6.5%
m1
 
3.2%
f1
 
3.2%
Other values (5)5
16.1%
Common
ValueCountFrequency (%)
114
80.3%
05
 
3.5%
4
 
2.8%
.4
 
2.8%
43
 
2.1%
-3
 
2.1%
32
 
1.4%
^2
 
1.4%
12
 
1.4%
51
 
0.7%
Other values (2)2
 
1.4%

Most occurring blocks

ValueCountFrequency (%)
Thai5092
96.7%
ASCII172
 
3.3%
Punctuation1
 
< 0.1%

Most frequent character per block

Thai
ValueCountFrequency (%)
า357
 
7.0%
น325
 
6.4%
เ268
 
5.3%
่260
 
5.1%
ร237
 
4.7%
ม234
 
4.6%
ก231
 
4.5%
ี229
 
4.5%
้229
 
4.5%
ย219
 
4.3%
Other values (48)2503
49.2%
ASCII
ValueCountFrequency (%)
114
66.3%
o6
 
3.5%
05
 
2.9%
t4
 
2.3%
4
 
2.3%
.4
 
2.3%
43
 
1.7%
e3
 
1.7%
l3
 
1.7%
-3
 
1.7%
Other values (16)23
 
13.4%
Punctuation
ValueCountFrequency (%)
​1
100.0%

กรุณาแจ้งเหตุผลที่ไม่ยินยอมตอบแบบสอบถาม
Unsupported

MISSING
REJECTED
UNSUPPORTED

Missing109
Missing (%)100.0%
Memory size1000.0 B

เบอร์ติดต่อ (เช่น 0991234567 หรือ 028546685 เป็นต้น)
Categorical

HIGH CARDINALITY
UNIFORM

Distinct108
Distinct (%)99.1%
Missing0
Missing (%)0.0%
Memory size1000.0 B
0645705956
 
2
0642906829
 
1
0957079434
 
1
0973034985
 
1
0956938489
 
1
Other values (103)
103 

Length

Max length11
Median length10
Mean length10.00917431
Min length10

Characters and Unicode

Total characters1091
Distinct characters11
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique107 ?
Unique (%)98.2%

Sample

1st row0809247235
2nd row0951432791
3rd row0808456537
4th row0622763798
5th row0867362518

Common Values

ValueCountFrequency (%)
06457059562
 
1.8%
06429068291
 
0.9%
09570794341
 
0.9%
09730349851
 
0.9%
09569384891
 
0.9%
06227637981
 
0.9%
09492986471
 
0.9%
08084565371
 
0.9%
08204875271
 
0.9%
06602713391
 
0.9%
Other values (98)98
89.9%

Length

2022-10-04T17:51:43.866084image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
06457059562
 
1.8%
09878031321
 
0.9%
08255830131
 
0.9%
09595383861
 
0.9%
08237936791
 
0.9%
09706378271
 
0.9%
09677230581
 
0.9%
06351212051
 
0.9%
09093023361
 
0.9%
06477569751
 
0.9%
Other values (98)98
89.9%

Most occurring characters

ValueCountFrequency (%)
0200
18.3%
9116
10.6%
6115
10.5%
8111
10.2%
3101
9.3%
797
8.9%
294
8.6%
590
8.2%
486
7.9%
180
 
7.3%

Most occurring categories

ValueCountFrequency (%)
Decimal Number1090
99.9%
Format1
 
0.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0200
18.3%
9116
10.6%
6115
10.6%
8111
10.2%
3101
9.3%
797
8.9%
294
8.6%
590
8.3%
486
7.9%
180
 
7.3%
Format
ValueCountFrequency (%)
​1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common1091
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0200
18.3%
9116
10.6%
6115
10.5%
8111
10.2%
3101
9.3%
797
8.9%
294
8.6%
590
8.2%
486
7.9%
180
 
7.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII1090
99.9%
Punctuation1
 
0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0200
18.3%
9116
10.6%
6115
10.6%
8111
10.2%
3101
9.3%
797
8.9%
294
8.6%
590
8.3%
486
7.9%
180
 
7.3%
Punctuation
ValueCountFrequency (%)
​1
100.0%

เพศ
Categorical

HIGH CORRELATION

Distinct2
Distinct (%)1.8%
Missing0
Missing (%)0.0%
Memory size1000.0 B
หญิง
69 
ชาย
40 

Length

Max length4
Median length4
Mean length3.633027523
Min length3

Characters and Unicode

Total characters396
Distinct characters7
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowชาย
2nd rowชาย
3rd rowชาย
4th rowชาย
5th rowชาย

Common Values

ValueCountFrequency (%)
หญิง69
63.3%
ชาย40
36.7%

Length

2022-10-04T17:51:44.115082image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
Histogram of lengths of the category

Category Frequency Plot

2022-10-04T17:51:44.392084image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
ValueCountFrequency (%)
หญิง69
63.3%
ชาย40
36.7%

Most occurring characters

ValueCountFrequency (%)
ห69
17.4%
ญ69
17.4%
ิ69
17.4%
ง69
17.4%
ช40
10.1%
า40
10.1%
ย40
10.1%

Most occurring categories

ValueCountFrequency (%)
Other Letter327
82.6%
Nonspacing Mark69
 
17.4%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
ห69
21.1%
ญ69
21.1%
ง69
21.1%
ช40
12.2%
า40
12.2%
ย40
12.2%
Nonspacing Mark
ValueCountFrequency (%)
ิ69
100.0%

Most occurring scripts

ValueCountFrequency (%)
Thai396
100.0%

Most frequent character per script

Thai
ValueCountFrequency (%)
ห69
17.4%
ญ69
17.4%
ิ69
17.4%
ง69
17.4%
ช40
10.1%
า40
10.1%
ย40
10.1%

Most occurring blocks

ValueCountFrequency (%)
Thai396
100.0%

Most frequent character per block

Thai
ValueCountFrequency (%)
ห69
17.4%
ญ69
17.4%
ิ69
17.4%
ง69
17.4%
ช40
10.1%
า40
10.1%
ย40
10.1%

Quilgo Submission ID (do not edit)
Unsupported

MISSING
REJECTED
UNSUPPORTED

Missing109
Missing (%)100.0%
Memory size1000.0 B

Interactions

2022-10-04T17:51:19.453841image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-10-04T17:51:16.580813image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-10-04T17:51:18.110479image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-10-04T17:51:19.810843image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-10-04T17:51:17.168792image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-10-04T17:51:18.589410image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-10-04T17:51:20.106075image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-10-04T17:51:17.685814image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-10-04T17:51:19.002940image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/

Correlations

2022-10-04T17:51:44.621085image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/

Spearman's ρ

The Spearman's rank correlation coefficient (ρ) is a measure of monotonic correlation between two variables, and is therefore better in catching nonlinear monotonic correlations than Pearson's r. It's value lies between -1 and +1, -1 indicating total negative monotonic correlation, 0 indicating no monotonic correlation and 1 indicating total positive monotonic correlation.

To calculate ρ for two variables X and Y, one divides the covariance of the rank variables of X and Y by the product of their standard deviations.
2022-10-04T17:51:45.184084image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/

Pearson's r

The Pearson's correlation coefficient (r) is a measure of linear correlation between two variables. It's value lies between -1 and +1, -1 indicating total negative linear correlation, 0 indicating no linear correlation and 1 indicating total positive linear correlation. Furthermore, r is invariant under separate changes in location and scale of the two variables, implying that for a linear function the angle to the x-axis does not affect r.

To calculate r for two variables X and Y, one divides the covariance of X and Y by the product of their standard deviations.
2022-10-04T17:51:45.724605image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/

Kendall's τ

Similarly to Spearman's rank correlation coefficient, the Kendall rank correlation coefficient (τ) measures ordinal association between two variables. It's value lies between -1 and +1, -1 indicating total negative correlation, 0 indicating no correlation and 1 indicating total positive correlation.

To calculate τ for two variables X and Y, one determines the number of concordant and discordant pairs of observations. τ is given by the number of concordant pairs minus the discordant pairs divided by the total number of pairs.
2022-10-04T17:51:46.287605image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/

Cramér's V (φc)

Cramér's V is an association measure for nominal random variables. The coefficient ranges from 0 to 1, with 0 indicating independence and 1 indicating perfect association. The empirical estimators used for Cramér's V have been proved to be biased, even for large samples. We use a bias-corrected measure that has been proposed by Bergsma in 2013 that can be found here.
2022-10-04T17:51:47.092604image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/

Phik (φk)

Phik (φk) is a new and practical correlation coefficient that works consistently between categorical, ordinal and interval variables, captures non-linear dependency and reverts to the Pearson correlation coefficient in case of a bivariate normal input distribution. There is extensive documentation available here.

Missing values

2022-10-04T17:51:20.796024image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
A simple visualization of nullity by column.
2022-10-04T17:51:24.766796image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
Nullity matrix is a data-dense display which lets you quickly visually pick out patterns in data completion.
2022-10-04T17:51:25.687297image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
The correlation heatmap measures nullity correlation: how strongly the presence or absence of one variable affects the presence of another.
2022-10-04T17:51:26.232213image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
The dendrogram allows you to more fully correlate variable completion, revealing trends deeper than the pairwise ones visible in the correlation heatmap.

Sample

First rows

TimestampEmail AddressScoreท่านให้ความยินยอมในการตอบแบบสอบถามฉันได้อ่าน และทำความเข้าใจกับคำแนะนำข้างต้นนี้แล้วในปีการศึกษา 2565 นี้ ฉันกำลังเรียนอยู่ในระดับชั้นในปีการศึกษา 2565 นี้ ฉันกำลังเรียนอยู่ในระดับห้องเลขประจำตัวนักเรียนเลขบัตรประชาชนชื่อเล่นอุปกรณ์ที่ใช้ในการทำโฮมรูมครั้งนี้วันเกิดอ.ที่ปรึกษาคนที่ 1อ.ที่ปรึกษาคนที่ 2Q1Q2Q3Q4Q5Q6Q7Q8Q9Q10Q11Q12Q13Q14Q15Q16กับการเริ่มต้นเรียนในปีการศึกษา 2565 .. ภาพฝันของเรา 1 ปีต่อจากนี้เป็นอย่างไร ? บอกได้เต็มที่เลยนะกรุณาแจ้งเหตุผลที่ไม่ยินยอมตอบแบบสอบถามเบอร์ติดต่อ (เช่น 0991234567 หรือ 028546685 เป็นต้น)เพศQuilgo Submission ID (do not edit)
02022-09-13 13:31:21.880std27506@mwk.ac.th0ยินยอมและเริ่มตอบแบบสอบถามใช่ม. 61275061.579901e+12คาโยโทรศัพท์มือถือ4/24/2547ครูกานดา ช่วงชัยครูเกศนี ทองอ่ำVAARKKRKRAAR​KKAAมีงานทำ โดยไม่รบกวนการเรียนNaN0809247235ชายNaN
12022-09-13 13:35:06.765std27513@mwk.ac.th0ยินยอมและเริ่มตอบแบบสอบถามใช่ม. 61275131.578800e+12คริสเตียนโทรศัพท์มือถือNaNครูกานดาครูเกศินีKAKAKVRAKVAK​KAAAดีขึ้นกว่าวันนี้NaN0951432791ชายNaN
22022-09-13 13:55:30.128std27514@mwk.ac.th0ยินยอมและเริ่มตอบแบบสอบถามใช่ม. 61275141.578500e+12รัชพลโทรศัพท์มือถือNaNนางเกศินี ทองอ่ำนางกานดา ช่วงชัยVRKRRRRKRRAR​KRKA-NaN0808456537ชายNaN
32022-09-13 13:32:57.257std27516@mwk.ac.th0ยินยอมและเริ่มตอบแบบสอบถามใช่ม. 61275161.578800e+12เบสท์โทรศัพท์มือถือ12/16/2004คุณครูเกศินี ทองอ่ำครูกานดา ช่วงชัยVRVRARRVRVVAAKVAมีงานทำ ควบคู่กับการเรียนNaN0622763798ชายNaN
42022-09-13 13:28:06.323std27518@mwk.ac.th0ยินยอมและเริ่มตอบแบบสอบถามใช่ม. 61275188.571573e+12บิวโทรศัพท์มือถือNaNครูเกศินี ทองอ่ำครูกานดา ช่วงชัยARARRRKVRRVAAAVAอยากจะกลายเป็นนักเทรดที่สามารถวิเคราะห์กราฟและข้อมูลและทราบข่าวต่างๆได้ทันโลกโดยนำมาประกอบการเทรดและอยากจะมีเพื่อนร่วมทีมที่ชอบในด้านเดียวกันช่วยกันวิเคราะห์และไปถึงฝั่งฝันด้วยกันNaN0867362518ชายNaN
52022-09-13 13:46:24.475std27520@mwk.ac.th0ยินยอมและเริ่มตอบแบบสอบถามใช่ม. 61275201.578800e+12อั้มโทรศัพท์มือถือ12/20/2547นางกานดา ช่วงชัยนางเกศินี ทองอ่ำKRKRRRKVAVVKARAAติดคณะที่อยากเข้าNaN0660271339หญิงNaN
62022-09-13 13:27:24.123std27525@mwk.ac.th0ยินยอมและเริ่มตอบแบบสอบถามใช่ม. 61275251.579901e+12ฟิล์มโทรศัพท์มือถือ11/22/2004ครูกานดา ช่วงชัยครูเกศินี ทองอ่ำKRKRKRRKAAAVAVAAการบ้านน้อย ให้อิสระในการเลือกที่จะเข้าแถวหรือไม่เข้าแถว ให้อิสระตัดสินใจNaN0910768719หญิงNaN
72022-09-13 13:20:53.204std27526@mwk.ac.th0ยินยอมและเริ่มตอบแบบสอบถามใช่ม. 61275261.578800e+12คูก้าโทรศัพท์มือถือ6/28/2004ครูกานดา ช่วงชัยครูเกศินี ทองอ่ำKRAKRRRVRVAKARAAเรียนต่อในมหาวิทยาลัยในคณะที่ตนเองชื่นชอบได้อย่างมีความสุขNaN0830781850หญิงNaN
82022-09-13 13:22:00.607std27527@mwk.ac.th0ยินยอมและเริ่มตอบแบบสอบถามใช่ม. 61275271.578800e+12โบว์โทรศัพท์มือถือ9/30/2004ครูกานดา ช่วงชัยครูเกศินี ทองอ่ำKRKRVRKVRVAKARKAเน้นการเตรียมตัวเข้ามหาลัย งานไม่เยอะจะได้มีเวลาอ่านหนังสือและทำ portfolio เรียนแบบได้ลงมือทำจะได้เข้าใจจริงๆNaN0803342456หญิงNaN
92022-09-13 13:26:19.748std27528@mwk.ac.th0ยินยอมและเริ่มตอบแบบสอบถามใช่ม. 61275281.578800e+12เฟิร์นโทรศัพท์มือถือNaNครูกานดา ช่วงชัยครูเกศินี ทองอ่ำARAKVKRAAAAKARKAได้เรียนคณะที่ชอบ ติดมหาลัย มีเพื่อนในมหาลัยที่ดีพากันเรียน มีความสุขไม่เครียด ตั้งใจอ่านหนังสือมากขึ้นNaN0656127504หญิงNaN

Last rows

TimestampEmail AddressScoreท่านให้ความยินยอมในการตอบแบบสอบถามฉันได้อ่าน และทำความเข้าใจกับคำแนะนำข้างต้นนี้แล้วในปีการศึกษา 2565 นี้ ฉันกำลังเรียนอยู่ในระดับชั้นในปีการศึกษา 2565 นี้ ฉันกำลังเรียนอยู่ในระดับห้องเลขประจำตัวนักเรียนเลขบัตรประชาชนชื่อเล่นอุปกรณ์ที่ใช้ในการทำโฮมรูมครั้งนี้วันเกิดอ.ที่ปรึกษาคนที่ 1อ.ที่ปรึกษาคนที่ 2Q1Q2Q3Q4Q5Q6Q7Q8Q9Q10Q11Q12Q13Q14Q15Q16กับการเริ่มต้นเรียนในปีการศึกษา 2565 .. ภาพฝันของเรา 1 ปีต่อจากนี้เป็นอย่างไร ? บอกได้เต็มที่เลยนะกรุณาแจ้งเหตุผลที่ไม่ยินยอมตอบแบบสอบถามเบอร์ติดต่อ (เช่น 0991234567 หรือ 028546685 เป็นต้น)เพศQuilgo Submission ID (do not edit)
992022-09-19 12:05:20.259stdd28719@mwk.ac.th0ยินยอมและเริ่มตอบแบบสอบถามใช่ม. 4328719NaNทีมโทรศัพท์มือถือ8/19/2006NaNNaNKV, AVK, VRK, RR, KR, KV, R, KK, R, AR, AA, KA, ​KR, KV, KA, VเรียนเยอะNaN0629490277ชายNaN
1002022-09-19 11:37:56.746stdd30496@mwk.ac.th0ยินยอมและเริ่มตอบแบบสอบถามใช่ม. 4230496NaNอ้อมโทรศัพท์มือถือNaNNaNNaNVA, RV, A, KR, V, KV, KV, A, RK, R, VK, VK, A, V, RV, R, AA, RR, V, A, K​K, V, AR, V, KA, R, KR, V, Aได้เรียนรู้อะไรหลายอย่างมากขึ้น ได้ประสบการณ์ต่างๆ สวยขึ้นฉลาดขึ้นNaN0961705425หญิงNaN
1012022-09-19 11:39:20.962stdd29533@mwk.ac.th0ยินยอมและเริ่มตอบแบบสอบถามใช่ม. 4329533NaNเพ้นท์โทรศัพท์มือถือ7/23/2006NaNNaNK, VRKAAKRKR, KK, V, R, AA, VVV, AR, VA, KA, RสนุกเเละเครียดในเวลาเดียวกันNaN0654270519ชายNaN
1022022-09-19 11:56:55.708stdd30509@mwk.ac.th0ยินยอมและเริ่มตอบแบบสอบถามใช่ม. 4330509NaNเอิร์นโทรศัพท์มือถือNaNNaNNaNVK, RA, KV, AV, AK, RV, KRR, AR, AV, AV, AAK, R, AK, AAการที่ได้มีเพื่อนข่วยเรียนNaN0842832245หญิงNaN
1032022-09-19 13:30:28.112stdd30511@mwk.ac.th0ยินยอมและเริ่มตอบแบบสอบถามใช่ม. 4330511NaNเบิร์ดโทรศัพท์มือถือ11/15/2006NaNNaNARVVKRAKKVVR​KVRRดูขยันมากขึ้นNaN0970637827ชายNaN
1042022-09-19 11:08:22.340stdd30512@mwk.ac.th0ยินยอมและเริ่มตอบแบบสอบถามใช่ม. 4330512NaNหลินเกี๊ยวโทรศัพท์มือถือ9/18/2549NaNNaNAVKAK, VK, RR, AARVV, AK, RA, ​KR, KKAจะเรียนวิชาที่เป็นแขนงวิทยาศาสตร์รู้เรื่อง เลือกคบเพื่อนที่ไม่บั่นทอนจิตใจNaN0909612132หญิงNaN
1052022-09-19 11:17:37.931suphatcha.peemai@gmail.com0ยินยอมและเริ่มตอบแบบสอบถามใช่ม. 4330513NaNปีใหม่โทรศัพท์มือถือNaNNaNNaNKRV, ARKRVK, VRKV, AA, VAR, VKAมีเป้าหมายเก็บเงินจากการทำงานเเล้วมาสร้างบ้านให้ปู่กับย่าNaN0825924703หญิงNaN
1062022-09-19 11:20:37.967stdd30514@mwk.ac.th0ยินยอมและเริ่มตอบแบบสอบถามใช่ม. 4330514NaNซันเดย์โทรศัพท์มือถือ11/19/2549NaNNaNVRKRVK, RRVRAA, RR​KKA, VV, Aอยากเป็นคนเก่ง เรียนดีNaN0802953875หญิงNaN
1072022-09-19 11:04:57.228stdd30673@mwk.ac.th0ยินยอมและเริ่มตอบแบบสอบถามใช่ม. 4230673NaNปรางค์โทรศัพท์มือถือ8/13/2006NaNNaNVRARRRRVRVARAKKVดีขึ้นNaN0909302336หญิงNaN
1082022-09-19 11:24:38.913stdd30707@mwk.ac.th0ยินยอมและเริ่มตอบแบบสอบถามใช่ม. 4330707NaNเหมยโทรศัพท์มือถือ5/22/2006NaNNaNKAVKKRRVRV, R, K, AA, RK, AAVAVเป็นแบบเรียนรู้สิ่งต่างได้อย่างเต็มที่และเปิดใจที่จะรับสิ่งใหม่และประสบการณ์ต่างๆมาพัฒนาปรับปรุงไปเรื่อยๆNaN0825583013หญิงNaN