Overview

Dataset statistics

Number of variables35
Number of observations10000
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory2.8 MiB
Average record size in memory294.0 B

Variable types

Categorical6
Numeric4
Text25

Dataset

Description기준일ID,시간대구분,행정동코드,생활인구순위,대도시권거주지코드,총생활인구수,남자10세부터14세생활인구수,남자15세부터19세생활인구수,남자20세부터24세생활인구수,남자25세부터29세생활인구수,남자30세부터34세생활인구수,남자35세부터39세생활인구수,남자40세부터44세생활인구수,남자45세부터49세생활인구수,남자50세부터54세생활인구수,남자55세부터59세생활인구수,남자60세부터64세생활인구수,남자65세부터69세생활인구수,남자70세부터74세생활인구수,남자70세부터79세생활인구수,여자10세부터14세생활인구수,여자15세부터19세생활인구수,여자20세부터24세생활인구수,여자25세부터29세생활인구수,여자30세부터34세생활인구수,여자35세부터39세생활인구수,여자40세부터44세생활인구수,여자45세부터49세생활인구수,여자50세부터54세생활인구수,여자55세부터59세생활인구수,여자60세부터64세생활인구수,여자65세부터69세생활인구수,여자70세부터74세생활인구수,여자75세부터79세생활인구수,장기체류외국인수
Author서울특별시
URLhttps://data.seoul.go.kr/dataList/OA-14981/S/1/datasetView.do

Alerts

기준일ID has constant value ""Constant
남자70세부터74세생활인구수 is highly imbalanced (98.9%)Imbalance
남자70세부터79세생활인구수 is highly imbalanced (99.1%)Imbalance
여자10세부터14세생활인구수 is highly imbalanced (98.8%)Imbalance
여자70세부터74세생활인구수 is highly imbalanced (98.9%)Imbalance
총생활인구수 is highly skewed (γ1 = 23.48022391)Skewed

Reproduction

Analysis started2024-04-29 17:02:44.480078
Analysis finished2024-04-29 17:02:45.664364
Duration1.18 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

기준일ID
Categorical

CONSTANT 

Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
20240422
10000 

Length

Max length8
Median length8
Mean length8
Min length8

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row20240422
2nd row20240422
3rd row20240422
4th row20240422
5th row20240422

Common Values

ValueCountFrequency (%)
20240422 10000
100.0%

Length

2024-04-30T02:02:45.730348image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-30T02:02:45.806093image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
20240422 10000
100.0%

시간대구분
Categorical

Distinct3
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
1
4063 
0
4039 
2
1898 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row2
2nd row0
3rd row2
4th row0
5th row0

Common Values

ValueCountFrequency (%)
1 4063
40.6%
0 4039
40.4%
2 1898
19.0%

Length

2024-04-30T02:02:45.898192image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-30T02:02:45.979169image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
1 4063
40.6%
0 4039
40.4%
2 1898
19.0%

행정동코드
Real number (ℝ)

Distinct424
Distinct (%)4.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean11407927
Minimum11110515
Maximum11740700
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-04-30T02:02:46.073567image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum11110515
5-th percentile11140550
Q111230730
median11380570
Q311560700
95-th percentile11710647
Maximum11740700
Range630185
Interquartile range (IQR)329970

Descriptive statistics

Standard deviation189668.74
Coefficient of variation (CV)0.016626048
Kurtosis-1.2070574
Mean11407927
Median Absolute Deviation (MAD)164740
Skewness0.20388268
Sum1.1407927 × 1011
Variance3.5974231 × 1010
MonotonicityNot monotonic
2024-04-30T02:02:46.218862image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
11290600 43
 
0.4%
11215847 42
 
0.4%
11380690 42
 
0.4%
11410565 42
 
0.4%
11350695 42
 
0.4%
11110615 41
 
0.4%
11320512 41
 
0.4%
11380570 41
 
0.4%
11260565 38
 
0.4%
11230600 38
 
0.4%
Other values (414) 9590
95.9%
ValueCountFrequency (%)
11110515 25
0.2%
11110530 33
0.3%
11110540 21
0.2%
11110550 15
 
0.1%
11110560 34
0.3%
11110570 9
 
0.1%
11110580 19
0.2%
11110600 21
0.2%
11110615 41
0.4%
11110630 27
0.3%
ValueCountFrequency (%)
11740700 12
0.1%
11740690 16
0.2%
11740685 24
0.2%
11740660 24
0.2%
11740650 21
0.2%
11740640 17
0.2%
11740620 19
0.2%
11740610 25
0.2%
11740600 16
0.2%
11740590 21
0.2%

생활인구순위
Real number (ℝ)

Distinct67
Distinct (%)0.7%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean27.713
Minimum1
Maximum67
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-04-30T02:02:46.349116image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile3
Q114
median27
Q341
95-th percentile54
Maximum67
Range66
Interquartile range (IQR)27

Descriptive statistics

Standard deviation16.111294
Coefficient of variation (CV)0.58136231
Kurtosis-1.0031994
Mean27.713
Median Absolute Deviation (MAD)13
Skewness0.14344369
Sum277130
Variance259.57379
MonotonicityNot monotonic
2024-04-30T02:02:46.476916image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
10 213
 
2.1%
25 209
 
2.1%
39 208
 
2.1%
30 199
 
2.0%
31 199
 
2.0%
16 197
 
2.0%
1 196
 
2.0%
21 195
 
1.9%
20 194
 
1.9%
34 194
 
1.9%
Other values (57) 7996
80.0%
ValueCountFrequency (%)
1 196
2.0%
2 182
1.8%
3 170
1.7%
4 185
1.8%
5 181
1.8%
6 184
1.8%
7 175
1.8%
8 185
1.8%
9 187
1.9%
10 213
2.1%
ValueCountFrequency (%)
67 1
 
< 0.1%
66 4
 
< 0.1%
65 7
 
0.1%
64 12
 
0.1%
63 16
 
0.2%
62 24
0.2%
61 35
0.4%
60 57
0.6%
59 55
0.5%
58 59
0.6%
Distinct68
Distinct (%)0.7%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean39521.004
Minimum26000
Maximum52000
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-04-30T02:02:46.607691image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum26000
5-th percentile28140
Q141115
median41287
Q341590
95-th percentile50000
Maximum52000
Range26000
Interquartile range (IQR)475

Descriptive statistics

Standard deviation6256.6086
Coefficient of variation (CV)0.15831097
Kurtosis-0.0080544074
Mean39521.004
Median Absolute Deviation (MAD)283
Skewness-0.73376394
Sum3.9521004 × 108
Variance39145151
MonotonicityNot monotonic
2024-04-30T02:02:46.728872image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
41360 199
 
2.0%
30000 199
 
2.0%
41480 198
 
2.0%
52000 197
 
2.0%
41590 195
 
1.9%
41220 194
 
1.9%
28260 190
 
1.9%
29000 190
 
1.9%
43000 187
 
1.9%
44000 185
 
1.8%
Other values (58) 8066
80.7%
ValueCountFrequency (%)
26000 178
1.8%
27000 169
1.7%
28110 152
1.5%
28140 13
 
0.1%
28177 129
1.3%
28185 163
1.6%
28200 137
1.4%
28237 149
1.5%
28245 123
1.2%
28260 190
1.9%
ValueCountFrequency (%)
52000 197
2.0%
51000 179
1.8%
50000 179
1.8%
48000 170
1.7%
47000 183
1.8%
46000 165
1.7%
44000 185
1.8%
43000 187
1.9%
41830 156
1.6%
41820 116
1.2%

총생활인구수
Real number (ℝ)

SKEWED 

Distinct9476
Distinct (%)94.8%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean10.961593
Minimum0
Maximum988.4184
Zeros10
Zeros (%)0.1%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-04-30T02:02:46.858034image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0.13889
Q12.903625
median6.2533
Q312.926075
95-th percentile34.71118
Maximum988.4184
Range988.4184
Interquartile range (IQR)10.02245

Descriptive statistics

Standard deviation24.418321
Coefficient of variation (CV)2.2276253
Kurtosis784.52648
Mean10.961593
Median Absolute Deviation (MAD)3.90195
Skewness23.480224
Sum109615.93
Variance596.25441
MonotonicityNot monotonic
2024-04-30T02:02:47.007593image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.0001 11
 
0.1%
0.0 10
 
0.1%
0.0008 9
 
0.1%
0.0002999999999999 7
 
0.1%
0.0006999999999999 6
 
0.1%
0.0025999999999999 6
 
0.1%
0.0016999999999999 6
 
0.1%
0.0004 6
 
0.1%
0.0027 5
 
0.1%
0.0025 5
 
0.1%
Other values (9466) 9929
99.3%
ValueCountFrequency (%)
0.0 10
0.1%
0.0001 11
0.1%
0.0002 5
0.1%
0.0002999999999999 7
0.1%
0.0004 6
0.1%
0.0005 5
0.1%
0.0005999999999999 2
 
< 0.1%
0.0006999999999999 6
0.1%
0.0008 9
0.1%
0.0008999999999999 1
 
< 0.1%
ValueCountFrequency (%)
988.4184 1
< 0.1%
938.5958 1
< 0.1%
777.9462 1
< 0.1%
773.089 1
< 0.1%
769.6799999999998 1
< 0.1%
548.4741 1
< 0.1%
406.3589 1
< 0.1%
316.6039 1
< 0.1%
222.4863 1
< 0.1%
214.0251 1
< 0.1%
Distinct64
Distinct (%)0.6%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
2024-04-30T02:02:47.179396image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length7
Median length1
Mean length1.0351
Min length1

Characters and Unicode

Total characters10351
Distinct characters12
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

Unique57 ?
Unique (%)0.6%

Sample

1st row5.5019
2nd row*
3rd row*
4th row*
5th row*
ValueCountFrequency (%)
9930
99.3%
5.6157 3
 
< 0.1%
5.8288 2
 
< 0.1%
5.508 2
 
< 0.1%
5.5229 2
 
< 0.1%
5.5085 2
 
< 0.1%
5.4482 2
 
< 0.1%
5.511 1
 
< 0.1%
6.9581 1
 
< 0.1%
5.4042 1
 
< 0.1%
Other values (54) 54
 
0.5%
2024-04-30T02:02:47.479859image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
* 9930
95.9%
5 89
 
0.9%
. 70
 
0.7%
4 41
 
0.4%
6 35
 
0.3%
8 35
 
0.3%
2 34
 
0.3%
1 27
 
0.3%
7 23
 
0.2%
0 23
 
0.2%
Other values (2) 44
 
0.4%

Most occurring categories

ValueCountFrequency (%)
Other Punctuation 10000
96.6%
Decimal Number 351
 
3.4%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
5 89
25.4%
4 41
11.7%
6 35
 
10.0%
8 35
 
10.0%
2 34
 
9.7%
1 27
 
7.7%
7 23
 
6.6%
0 23
 
6.6%
9 22
 
6.3%
3 22
 
6.3%
Other Punctuation
ValueCountFrequency (%)
* 9930
99.3%
. 70
 
0.7%

Most occurring scripts

ValueCountFrequency (%)
Common 10351
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
* 9930
95.9%
5 89
 
0.9%
. 70
 
0.7%
4 41
 
0.4%
6 35
 
0.3%
8 35
 
0.3%
2 34
 
0.3%
1 27
 
0.3%
7 23
 
0.2%
0 23
 
0.2%
Other values (2) 44
 
0.4%

Most occurring blocks

ValueCountFrequency (%)
ASCII 10351
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
* 9930
95.9%
5 89
 
0.9%
. 70
 
0.7%
4 41
 
0.4%
6 35
 
0.3%
8 35
 
0.3%
2 34
 
0.3%
1 27
 
0.3%
7 23
 
0.2%
0 23
 
0.2%
Other values (2) 44
 
0.4%
Distinct246
Distinct (%)2.5%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
2024-04-30T02:02:47.800919image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length7
Median length1
Mean length1.1741
Min length1

Characters and Unicode

Total characters11741
Distinct characters12
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

Unique190 ?
Unique (%)1.9%

Sample

1st row*
2nd row*
3rd row*
4th row*
5th row*
ValueCountFrequency (%)
9650
96.5%
5.4709 7
 
0.1%
5.4923 6
 
0.1%
5.5253 6
 
0.1%
5.5851 6
 
0.1%
5.4023 5
 
< 0.1%
5.4266 5
 
< 0.1%
5.5308 4
 
< 0.1%
5.3634 4
 
< 0.1%
5.5314 4
 
< 0.1%
Other values (236) 303
 
3.0%
2024-04-30T02:02:48.243440image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
* 9650
82.2%
5 432
 
3.7%
. 350
 
3.0%
4 217
 
1.8%
3 203
 
1.7%
1 152
 
1.3%
2 141
 
1.2%
9 139
 
1.2%
7 121
 
1.0%
6 121
 
1.0%
Other values (2) 215
 
1.8%

Most occurring categories

ValueCountFrequency (%)
Other Punctuation 10000
85.2%
Decimal Number 1741
 
14.8%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
5 432
24.8%
4 217
12.5%
3 203
11.7%
1 152
 
8.7%
2 141
 
8.1%
9 139
 
8.0%
7 121
 
7.0%
6 121
 
7.0%
8 118
 
6.8%
0 97
 
5.6%
Other Punctuation
ValueCountFrequency (%)
* 9650
96.5%
. 350
 
3.5%

Most occurring scripts

ValueCountFrequency (%)
Common 11741
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
* 9650
82.2%
5 432
 
3.7%
. 350
 
3.0%
4 217
 
1.8%
3 203
 
1.7%
1 152
 
1.3%
2 141
 
1.2%
9 139
 
1.2%
7 121
 
1.0%
6 121
 
1.0%
Other values (2) 215
 
1.8%

Most occurring blocks

ValueCountFrequency (%)
ASCII 11741
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
* 9650
82.2%
5 432
 
3.7%
. 350
 
3.0%
4 217
 
1.8%
3 203
 
1.7%
1 152
 
1.3%
2 141
 
1.2%
9 139
 
1.2%
7 121
 
1.0%
6 121
 
1.0%
Other values (2) 215
 
1.8%
Distinct411
Distinct (%)4.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
2024-04-30T02:02:48.589628image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length7
Median length1
Mean length1.2231
Min length1

Characters and Unicode

Total characters12231
Distinct characters12
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

Unique387 ?
Unique (%)3.9%

Sample

1st row*
2nd row*
3rd row*
4th row*
5th row*
ValueCountFrequency (%)
9561
95.6%
4.0022 4
 
< 0.1%
4.0034 4
 
< 0.1%
7.9113 3
 
< 0.1%
7.8638 3
 
< 0.1%
7.9194 2
 
< 0.1%
4.0041 2
 
< 0.1%
7.8985 2
 
< 0.1%
4.0039 2
 
< 0.1%
4.0139 2
 
< 0.1%
Other values (401) 415
 
4.2%
2024-04-30T02:02:49.024498image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
* 9561
78.2%
. 439
 
3.6%
4 305
 
2.5%
7 305
 
2.5%
1 267
 
2.2%
0 221
 
1.8%
9 215
 
1.8%
5 206
 
1.7%
8 205
 
1.7%
2 174
 
1.4%
Other values (2) 333
 
2.7%

Most occurring categories

ValueCountFrequency (%)
Other Punctuation 10000
81.8%
Decimal Number 2231
 
18.2%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
4 305
13.7%
7 305
13.7%
1 267
12.0%
0 221
9.9%
9 215
9.6%
5 206
9.2%
8 205
9.2%
2 174
7.8%
3 172
7.7%
6 161
7.2%
Other Punctuation
ValueCountFrequency (%)
* 9561
95.6%
. 439
 
4.4%

Most occurring scripts

ValueCountFrequency (%)
Common 12231
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
* 9561
78.2%
. 439
 
3.6%
4 305
 
2.5%
7 305
 
2.5%
1 267
 
2.2%
0 221
 
1.8%
9 215
 
1.8%
5 206
 
1.7%
8 205
 
1.7%
2 174
 
1.4%
Other values (2) 333
 
2.7%

Most occurring blocks

ValueCountFrequency (%)
ASCII 12231
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
* 9561
78.2%
. 439
 
3.6%
4 305
 
2.5%
7 305
 
2.5%
1 267
 
2.2%
0 221
 
1.8%
9 215
 
1.8%
5 206
 
1.7%
8 205
 
1.7%
2 174
 
1.4%
Other values (2) 333
 
2.7%
Distinct402
Distinct (%)4.0%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
2024-04-30T02:02:49.308200image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length7
Median length1
Mean length1.2139
Min length1

Characters and Unicode

Total characters12139
Distinct characters12
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

Unique382 ?
Unique (%)3.8%

Sample

1st row10.8669
2nd row*
3rd row*
4th row*
5th row*
ValueCountFrequency (%)
9572
95.7%
5.3973 4
 
< 0.1%
5.4091 4
 
< 0.1%
5.3817 3
 
< 0.1%
5.41 3
 
< 0.1%
5.3808 3
 
< 0.1%
5.4046 3
 
< 0.1%
5.4128 2
 
< 0.1%
5.3896 2
 
< 0.1%
5.3931 2
 
< 0.1%
Other values (392) 402
 
4.0%
2024-04-30T02:02:49.793399image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
* 9572
78.9%
. 428
 
3.5%
5 366
 
3.0%
4 307
 
2.5%
3 256
 
2.1%
1 221
 
1.8%
8 202
 
1.7%
9 176
 
1.4%
7 168
 
1.4%
6 165
 
1.4%
Other values (2) 278
 
2.3%

Most occurring categories

ValueCountFrequency (%)
Other Punctuation 10000
82.4%
Decimal Number 2139
 
17.6%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
5 366
17.1%
4 307
14.4%
3 256
12.0%
1 221
10.3%
8 202
9.4%
9 176
8.2%
7 168
7.9%
6 165
7.7%
0 143
 
6.7%
2 135
 
6.3%
Other Punctuation
ValueCountFrequency (%)
* 9572
95.7%
. 428
 
4.3%

Most occurring scripts

ValueCountFrequency (%)
Common 12139
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
* 9572
78.9%
. 428
 
3.5%
5 366
 
3.0%
4 307
 
2.5%
3 256
 
2.1%
1 221
 
1.8%
8 202
 
1.7%
9 176
 
1.4%
7 168
 
1.4%
6 165
 
1.4%
Other values (2) 278
 
2.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 12139
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
* 9572
78.9%
. 428
 
3.5%
5 366
 
3.0%
4 307
 
2.5%
3 256
 
2.1%
1 221
 
1.8%
8 202
 
1.7%
9 176
 
1.4%
7 168
 
1.4%
6 165
 
1.4%
Other values (2) 278
 
2.3%
Distinct328
Distinct (%)3.3%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
2024-04-30T02:02:50.055806image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length7
Median length1
Mean length1.1703
Min length1

Characters and Unicode

Total characters11703
Distinct characters12
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

Unique311 ?
Unique (%)3.1%

Sample

1st row4.8528
2nd row*
3rd row*
4th row4.893
5th row*
ValueCountFrequency (%)
9654
96.5%
4.8733 4
 
< 0.1%
4.8843 3
 
< 0.1%
4.8946 2
 
< 0.1%
4.8528 2
 
< 0.1%
4.8861 2
 
< 0.1%
4.9189 2
 
< 0.1%
4.9506 2
 
< 0.1%
4.879 2
 
< 0.1%
4.8962 2
 
< 0.1%
Other values (318) 325
 
3.2%
2024-04-30T02:02:50.448565image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
* 9654
82.5%
. 346
 
3.0%
4 322
 
2.8%
8 227
 
1.9%
9 189
 
1.6%
7 172
 
1.5%
6 146
 
1.2%
5 144
 
1.2%
1 134
 
1.1%
2 133
 
1.1%
Other values (2) 236
 
2.0%

Most occurring categories

ValueCountFrequency (%)
Other Punctuation 10000
85.4%
Decimal Number 1703
 
14.6%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
4 322
18.9%
8 227
13.3%
9 189
11.1%
7 172
10.1%
6 146
8.6%
5 144
8.5%
1 134
7.9%
2 133
7.8%
3 131
7.7%
0 105
 
6.2%
Other Punctuation
ValueCountFrequency (%)
* 9654
96.5%
. 346
 
3.5%

Most occurring scripts

ValueCountFrequency (%)
Common 11703
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
* 9654
82.5%
. 346
 
3.0%
4 322
 
2.8%
8 227
 
1.9%
9 189
 
1.6%
7 172
 
1.5%
6 146
 
1.2%
5 144
 
1.2%
1 134
 
1.1%
2 133
 
1.1%
Other values (2) 236
 
2.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 11703
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
* 9654
82.5%
. 346
 
3.0%
4 322
 
2.8%
8 227
 
1.9%
9 189
 
1.6%
7 172
 
1.5%
6 146
 
1.2%
5 144
 
1.2%
1 134
 
1.1%
2 133
 
1.1%
Other values (2) 236
 
2.0%
Distinct200
Distinct (%)2.0%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
2024-04-30T02:02:50.753470image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length7
Median length1
Mean length1.1043
Min length1

Characters and Unicode

Total characters11043
Distinct characters12
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

Unique194 ?
Unique (%)1.9%

Sample

1st row*
2nd row*
3rd row*
4th row*
5th row*
ValueCountFrequency (%)
9795
98.0%
7.2128 3
 
< 0.1%
7.1861 2
 
< 0.1%
7.164 2
 
< 0.1%
10.8165 2
 
< 0.1%
7.2113 2
 
< 0.1%
6.6699 1
 
< 0.1%
7.2291 1
 
< 0.1%
7.1849 1
 
< 0.1%
6.7374 1
 
< 0.1%
Other values (190) 190
 
1.9%
2024-04-30T02:02:51.189703image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
* 9795
88.7%
. 205
 
1.9%
7 150
 
1.4%
1 145
 
1.3%
2 114
 
1.0%
6 109
 
1.0%
8 102
 
0.9%
4 102
 
0.9%
5 94
 
0.9%
9 83
 
0.8%
Other values (2) 144
 
1.3%

Most occurring categories

ValueCountFrequency (%)
Other Punctuation 10000
90.6%
Decimal Number 1043
 
9.4%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
7 150
14.4%
1 145
13.9%
2 114
10.9%
6 109
10.5%
8 102
9.8%
4 102
9.8%
5 94
9.0%
9 83
8.0%
0 72
6.9%
3 72
6.9%
Other Punctuation
ValueCountFrequency (%)
* 9795
98.0%
. 205
 
2.1%

Most occurring scripts

ValueCountFrequency (%)
Common 11043
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
* 9795
88.7%
. 205
 
1.9%
7 150
 
1.4%
1 145
 
1.3%
2 114
 
1.0%
6 109
 
1.0%
8 102
 
0.9%
4 102
 
0.9%
5 94
 
0.9%
9 83
 
0.8%
Other values (2) 144
 
1.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 11043
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
* 9795
88.7%
. 205
 
1.9%
7 150
 
1.4%
1 145
 
1.3%
2 114
 
1.0%
6 109
 
1.0%
8 102
 
0.9%
4 102
 
0.9%
5 94
 
0.9%
9 83
 
0.8%
Other values (2) 144
 
1.3%
Distinct208
Distinct (%)2.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
2024-04-30T02:02:51.458850image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length7
Median length1
Mean length1.1077
Min length1

Characters and Unicode

Total characters11077
Distinct characters12
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

Unique202 ?
Unique (%)2.0%

Sample

1st row15.7234
2nd row*
3rd row*
4th row*
5th row*
ValueCountFrequency (%)
9787
97.9%
6.305 3
 
< 0.1%
6.3228 2
 
< 0.1%
6.2244 2
 
< 0.1%
6.2801 2
 
< 0.1%
6.2619 2
 
< 0.1%
6.2579 1
 
< 0.1%
5.8744 1
 
< 0.1%
5.9572 1
 
< 0.1%
10.9821 1
 
< 0.1%
Other values (198) 198
 
2.0%
2024-04-30T02:02:52.003854image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
* 9787
88.4%
. 213
 
1.9%
6 170
 
1.5%
2 126
 
1.1%
1 126
 
1.1%
4 121
 
1.1%
5 110
 
1.0%
3 102
 
0.9%
9 94
 
0.8%
8 86
 
0.8%
Other values (2) 142
 
1.3%

Most occurring categories

ValueCountFrequency (%)
Other Punctuation 10000
90.3%
Decimal Number 1077
 
9.7%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
6 170
15.8%
2 126
11.7%
1 126
11.7%
4 121
11.2%
5 110
10.2%
3 102
9.5%
9 94
8.7%
8 86
8.0%
7 76
7.1%
0 66
 
6.1%
Other Punctuation
ValueCountFrequency (%)
* 9787
97.9%
. 213
 
2.1%

Most occurring scripts

ValueCountFrequency (%)
Common 11077
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
* 9787
88.4%
. 213
 
1.9%
6 170
 
1.5%
2 126
 
1.1%
1 126
 
1.1%
4 121
 
1.1%
5 110
 
1.0%
3 102
 
0.9%
9 94
 
0.8%
8 86
 
0.8%
Other values (2) 142
 
1.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 11077
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
* 9787
88.4%
. 213
 
1.9%
6 170
 
1.5%
2 126
 
1.1%
1 126
 
1.1%
4 121
 
1.1%
5 110
 
1.0%
3 102
 
0.9%
9 94
 
0.8%
8 86
 
0.8%
Other values (2) 142
 
1.3%
Distinct421
Distinct (%)4.2%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
2024-04-30T02:02:52.252489image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length7
Median length1
Mean length1.2555
Min length1

Characters and Unicode

Total characters12555
Distinct characters12
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

Unique367 ?
Unique (%)3.7%

Sample

1st row*
2nd row*
3rd row*
4th row*
5th row*
ValueCountFrequency (%)
9487
94.9%
4.0283 10
 
0.1%
4.0004 6
 
0.1%
4.0273 6
 
0.1%
4.0234 4
 
< 0.1%
4.0103 4
 
< 0.1%
4.0751 4
 
< 0.1%
4.0657 4
 
< 0.1%
4.0095 4
 
< 0.1%
7.9839 4
 
< 0.1%
Other values (411) 467
 
4.7%
2024-04-30T02:02:52.588216image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
* 9487
75.6%
. 513
 
4.1%
4 480
 
3.8%
0 449
 
3.6%
7 259
 
2.1%
1 231
 
1.8%
8 221
 
1.8%
3 200
 
1.6%
2 195
 
1.6%
5 175
 
1.4%
Other values (2) 345
 
2.7%

Most occurring categories

ValueCountFrequency (%)
Other Punctuation 10000
79.6%
Decimal Number 2555
 
20.4%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
4 480
18.8%
0 449
17.6%
7 259
10.1%
1 231
9.0%
8 221
8.6%
3 200
7.8%
2 195
7.6%
5 175
 
6.8%
6 175
 
6.8%
9 170
 
6.7%
Other Punctuation
ValueCountFrequency (%)
* 9487
94.9%
. 513
 
5.1%

Most occurring scripts

ValueCountFrequency (%)
Common 12555
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
* 9487
75.6%
. 513
 
4.1%
4 480
 
3.8%
0 449
 
3.6%
7 259
 
2.1%
1 231
 
1.8%
8 221
 
1.8%
3 200
 
1.6%
2 195
 
1.6%
5 175
 
1.4%
Other values (2) 345
 
2.7%

Most occurring blocks

ValueCountFrequency (%)
ASCII 12555
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
* 9487
75.6%
. 513
 
4.1%
4 480
 
3.8%
0 449
 
3.6%
7 259
 
2.1%
1 231
 
1.8%
8 221
 
1.8%
3 200
 
1.6%
2 195
 
1.6%
5 175
 
1.4%
Other values (2) 345
 
2.7%
Distinct238
Distinct (%)2.4%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
2024-04-30T02:02:52.885668image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length7
Median length1
Mean length1.1202
Min length1

Characters and Unicode

Total characters11202
Distinct characters12
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

Unique231 ?
Unique (%)2.3%

Sample

1st row*
2nd row*
3rd row*
4th row*
5th row*
ValueCountFrequency (%)
9757
97.6%
5.064 2
 
< 0.1%
6.2358 2
 
< 0.1%
6.3278 2
 
< 0.1%
6.1577 2
 
< 0.1%
9.2447 2
 
< 0.1%
6.083 2
 
< 0.1%
6.0848 1
 
< 0.1%
6.1501 1
 
< 0.1%
5.6403 1
 
< 0.1%
Other values (228) 228
 
2.3%
2024-04-30T02:02:53.308455image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
* 9757
87.1%
. 243
 
2.2%
6 202
 
1.8%
1 161
 
1.4%
4 134
 
1.2%
9 113
 
1.0%
5 108
 
1.0%
2 102
 
0.9%
3 101
 
0.9%
7 95
 
0.8%
Other values (2) 186
 
1.7%

Most occurring categories

ValueCountFrequency (%)
Other Punctuation 10000
89.3%
Decimal Number 1202
 
10.7%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
6 202
16.8%
1 161
13.4%
4 134
11.1%
9 113
9.4%
5 108
9.0%
2 102
8.5%
3 101
8.4%
7 95
7.9%
8 94
7.8%
0 92
7.7%
Other Punctuation
ValueCountFrequency (%)
* 9757
97.6%
. 243
 
2.4%

Most occurring scripts

ValueCountFrequency (%)
Common 11202
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
* 9757
87.1%
. 243
 
2.2%
6 202
 
1.8%
1 161
 
1.4%
4 134
 
1.2%
9 113
 
1.0%
5 108
 
1.0%
2 102
 
0.9%
3 101
 
0.9%
7 95
 
0.8%
Other values (2) 186
 
1.7%

Most occurring blocks

ValueCountFrequency (%)
ASCII 11202
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
* 9757
87.1%
. 243
 
2.2%
6 202
 
1.8%
1 161
 
1.4%
4 134
 
1.2%
9 113
 
1.0%
5 108
 
1.0%
2 102
 
0.9%
3 101
 
0.9%
7 95
 
0.8%
Other values (2) 186
 
1.7%
Distinct221
Distinct (%)2.2%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
2024-04-30T02:02:53.585451image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length7
Median length1
Mean length1.1124
Min length1

Characters and Unicode

Total characters11124
Distinct characters12
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

Unique216 ?
Unique (%)2.2%

Sample

1st row*
2nd row6.3086
3rd row*
4th row*
5th row5.0889
ValueCountFrequency (%)
9776
97.8%
6.4656 2
 
< 0.1%
6.538 2
 
< 0.1%
6.5864 2
 
< 0.1%
6.5532 2
 
< 0.1%
6.6456 1
 
< 0.1%
6.2702 1
 
< 0.1%
6.4733 1
 
< 0.1%
6.53 1
 
< 0.1%
4.3185 1
 
< 0.1%
Other values (211) 211
 
2.1%
2024-04-30T02:02:53.959984image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
* 9776
87.9%
. 224
 
2.0%
6 221
 
2.0%
5 156
 
1.4%
4 121
 
1.1%
7 109
 
1.0%
1 95
 
0.9%
9 92
 
0.8%
8 90
 
0.8%
3 85
 
0.8%
Other values (2) 155
 
1.4%

Most occurring categories

ValueCountFrequency (%)
Other Punctuation 10000
89.9%
Decimal Number 1124
 
10.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
6 221
19.7%
5 156
13.9%
4 121
10.8%
7 109
9.7%
1 95
8.5%
9 92
8.2%
8 90
8.0%
3 85
 
7.6%
2 85
 
7.6%
0 70
 
6.2%
Other Punctuation
ValueCountFrequency (%)
* 9776
97.8%
. 224
 
2.2%

Most occurring scripts

ValueCountFrequency (%)
Common 11124
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
* 9776
87.9%
. 224
 
2.0%
6 221
 
2.0%
5 156
 
1.4%
4 121
 
1.1%
7 109
 
1.0%
1 95
 
0.9%
9 92
 
0.8%
8 90
 
0.8%
3 85
 
0.8%
Other values (2) 155
 
1.4%

Most occurring blocks

ValueCountFrequency (%)
ASCII 11124
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
* 9776
87.9%
. 224
 
2.0%
6 221
 
2.0%
5 156
 
1.4%
4 121
 
1.1%
7 109
 
1.0%
1 95
 
0.9%
9 92
 
0.8%
8 90
 
0.8%
3 85
 
0.8%
Other values (2) 155
 
1.4%
Distinct162
Distinct (%)1.6%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
2024-04-30T02:02:54.230499image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length7
Median length1
Mean length1.088
Min length1

Characters and Unicode

Total characters10880
Distinct characters12
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

Unique151 ?
Unique (%)1.5%

Sample

1st row*
2nd row*
3rd row*
4th row*
5th row*
ValueCountFrequency (%)
9824
98.2%
5.0284 5
 
< 0.1%
5.0274 3
 
< 0.1%
5.0466 3
 
< 0.1%
5.058 2
 
< 0.1%
5.0542 2
 
< 0.1%
5.4951 2
 
< 0.1%
5.0257 2
 
< 0.1%
5.0965 2
 
< 0.1%
5.1127 2
 
< 0.1%
Other values (152) 153
 
1.5%
2024-04-30T02:02:54.650069image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
* 9824
90.3%
. 176
 
1.6%
5 143
 
1.3%
4 123
 
1.1%
1 109
 
1.0%
6 87
 
0.8%
0 80
 
0.7%
2 73
 
0.7%
7 71
 
0.7%
8 69
 
0.6%
Other values (2) 125
 
1.1%

Most occurring categories

ValueCountFrequency (%)
Other Punctuation 10000
91.9%
Decimal Number 880
 
8.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
5 143
16.2%
4 123
14.0%
1 109
12.4%
6 87
9.9%
0 80
9.1%
2 73
8.3%
7 71
8.1%
8 69
7.8%
9 69
7.8%
3 56
 
6.4%
Other Punctuation
ValueCountFrequency (%)
* 9824
98.2%
. 176
 
1.8%

Most occurring scripts

ValueCountFrequency (%)
Common 10880
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
* 9824
90.3%
. 176
 
1.6%
5 143
 
1.3%
4 123
 
1.1%
1 109
 
1.0%
6 87
 
0.8%
0 80
 
0.7%
2 73
 
0.7%
7 71
 
0.7%
8 69
 
0.6%
Other values (2) 125
 
1.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 10880
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
* 9824
90.3%
. 176
 
1.6%
5 143
 
1.3%
4 123
 
1.1%
1 109
 
1.0%
6 87
 
0.8%
0 80
 
0.7%
2 73
 
0.7%
7 71
 
0.7%
8 69
 
0.6%
Other values (2) 125
 
1.1%
Distinct97
Distinct (%)1.0%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
2024-04-30T02:02:54.889742image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length7
Median length1
Mean length1.051
Min length1

Characters and Unicode

Total characters10510
Distinct characters12
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

Unique91 ?
Unique (%)0.9%

Sample

1st row*
2nd row*
3rd row*
4th row*
5th row*
ValueCountFrequency (%)
9898
99.0%
4.4496 3
 
< 0.1%
4.4001 2
 
< 0.1%
4.4259 2
 
< 0.1%
4.4044 2
 
< 0.1%
4.3964 2
 
< 0.1%
5.9604 1
 
< 0.1%
4.4813 1
 
< 0.1%
4.3466 1
 
< 0.1%
4.3267 1
 
< 0.1%
Other values (87) 87
 
0.9%
2024-04-30T02:02:55.259489image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
* 9898
94.2%
4 139
 
1.3%
. 102
 
1.0%
5 52
 
0.5%
6 49
 
0.5%
3 46
 
0.4%
0 41
 
0.4%
8 40
 
0.4%
1 38
 
0.4%
9 37
 
0.4%
Other values (2) 68
 
0.6%

Most occurring categories

ValueCountFrequency (%)
Other Punctuation 10000
95.1%
Decimal Number 510
 
4.9%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
4 139
27.3%
5 52
 
10.2%
6 49
 
9.6%
3 46
 
9.0%
0 41
 
8.0%
8 40
 
7.8%
1 38
 
7.5%
9 37
 
7.3%
2 34
 
6.7%
7 34
 
6.7%
Other Punctuation
ValueCountFrequency (%)
* 9898
99.0%
. 102
 
1.0%

Most occurring scripts

ValueCountFrequency (%)
Common 10510
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
* 9898
94.2%
4 139
 
1.3%
. 102
 
1.0%
5 52
 
0.5%
6 49
 
0.5%
3 46
 
0.4%
0 41
 
0.4%
8 40
 
0.4%
1 38
 
0.4%
9 37
 
0.4%
Other values (2) 68
 
0.6%

Most occurring blocks

ValueCountFrequency (%)
ASCII 10510
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
* 9898
94.2%
4 139
 
1.3%
. 102
 
1.0%
5 52
 
0.5%
6 49
 
0.5%
3 46
 
0.4%
0 41
 
0.4%
8 40
 
0.4%
1 38
 
0.4%
9 37
 
0.4%
Other values (2) 68
 
0.6%
Distinct42
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
*
9958 
5.7472
 
2
15.3626
 
1
5.8062
 
1
4.1715
 
1
Other values (37)
 
37

Length

Max length7
Median length1
Mean length1.021
Min length1

Unique

Unique40 ?
Unique (%)0.4%

Sample

1st row*
2nd row*
3rd row*
4th row*
5th row*

Common Values

ValueCountFrequency (%)
* 9958
99.6%
5.7472 2
 
< 0.1%
15.3626 1
 
< 0.1%
5.8062 1
 
< 0.1%
4.1715 1
 
< 0.1%
4.7835 1
 
< 0.1%
5.9628 1
 
< 0.1%
8.7263 1
 
< 0.1%
5.2329 1
 
< 0.1%
8.8178 1
 
< 0.1%
Other values (32) 32
 
0.3%

Length

2024-04-30T02:02:55.429964image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
9958
99.6%
5.7472 2
 
< 0.1%
8.6896 1
 
< 0.1%
4.511 1
 
< 0.1%
6.158 1
 
< 0.1%
4.5114 1
 
< 0.1%
8.5276 1
 
< 0.1%
4.1292 1
 
< 0.1%
6.015 1
 
< 0.1%
20.5774 1
 
< 0.1%
Other values (32) 32
 
0.3%
Distinct32
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
*
9968 
7.2595
 
2
21.6663
 
1
7.0166
 
1
7.425
 
1
Other values (27)
 
27

Length

Max length7
Median length1
Mean length1.0159
Min length1

Unique

Unique30 ?
Unique (%)0.3%

Sample

1st row*
2nd row*
3rd row*
4th row*
5th row*

Common Values

ValueCountFrequency (%)
* 9968
99.7%
7.2595 2
 
< 0.1%
21.6663 1
 
< 0.1%
7.0166 1
 
< 0.1%
7.425 1
 
< 0.1%
7.1842 1
 
< 0.1%
6.8412 1
 
< 0.1%
6.4242 1
 
< 0.1%
5.6361 1
 
< 0.1%
10.4232 1
 
< 0.1%
Other values (22) 22
 
0.2%

Length

2024-04-30T02:02:55.574880image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
9968
99.7%
7.2595 2
 
< 0.1%
6.0621 1
 
< 0.1%
6.4462 1
 
< 0.1%
6.9297 1
 
< 0.1%
7.3007 1
 
< 0.1%
6.05 1
 
< 0.1%
7.2221 1
 
< 0.1%
5.06 1
 
< 0.1%
6.365 1
 
< 0.1%
Other values (22) 22
 
0.2%
Distinct46
Distinct (%)0.5%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
*
9953 
5.2582
 
2
5.2091
 
2
5.3178
 
1
5.1677
 
1
Other values (41)
 
41

Length

Max length7
Median length1
Mean length1.0237
Min length1

Unique

Unique43 ?
Unique (%)0.4%

Sample

1st row5.1021
2nd row*
3rd row*
4th row*
5th row*

Common Values

ValueCountFrequency (%)
* 9953
99.5%
5.2582 2
 
< 0.1%
5.2091 2
 
< 0.1%
5.3178 1
 
< 0.1%
5.1677 1
 
< 0.1%
5.1704 1
 
< 0.1%
4.6192 1
 
< 0.1%
5.2447 1
 
< 0.1%
5.3327 1
 
< 0.1%
5.1903 1
 
< 0.1%
Other values (36) 36
 
0.4%

Length

2024-04-30T02:02:55.704231image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
9953
99.5%
5.2091 2
 
< 0.1%
5.2582 2
 
< 0.1%
5.5037 1
 
< 0.1%
5.2605 1
 
< 0.1%
5.4243 1
 
< 0.1%
5.3707 1
 
< 0.1%
5.347 1
 
< 0.1%
5.155 1
 
< 0.1%
5.1684 1
 
< 0.1%
Other values (36) 36
 
0.4%
Distinct239
Distinct (%)2.4%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
2024-04-30T02:02:55.997429image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length7
Median length1
Mean length1.1558
Min length1

Characters and Unicode

Total characters11558
Distinct characters12
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

Unique190 ?
Unique (%)1.9%

Sample

1st row*
2nd row*
3rd row*
4th row*
5th row*
ValueCountFrequency (%)
9685
96.9%
5.353 7
 
0.1%
5.6009 5
 
< 0.1%
5.2282 5
 
< 0.1%
5.653 4
 
< 0.1%
5.6534 4
 
< 0.1%
5.2763 4
 
< 0.1%
5.293 4
 
< 0.1%
5.3163 4
 
< 0.1%
5.3526 3
 
< 0.1%
Other values (229) 275
 
2.8%
2024-04-30T02:02:56.429429image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
* 9685
83.8%
5 382
 
3.3%
. 315
 
2.7%
2 191
 
1.7%
3 180
 
1.6%
4 149
 
1.3%
1 137
 
1.2%
6 115
 
1.0%
8 110
 
1.0%
9 105
 
0.9%
Other values (2) 189
 
1.6%

Most occurring categories

ValueCountFrequency (%)
Other Punctuation 10000
86.5%
Decimal Number 1558
 
13.5%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
5 382
24.5%
2 191
12.3%
3 180
11.6%
4 149
 
9.6%
1 137
 
8.8%
6 115
 
7.4%
8 110
 
7.1%
9 105
 
6.7%
7 100
 
6.4%
0 89
 
5.7%
Other Punctuation
ValueCountFrequency (%)
* 9685
96.9%
. 315
 
3.1%

Most occurring scripts

ValueCountFrequency (%)
Common 11558
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
* 9685
83.8%
5 382
 
3.3%
. 315
 
2.7%
2 191
 
1.7%
3 180
 
1.6%
4 149
 
1.3%
1 137
 
1.2%
6 115
 
1.0%
8 110
 
1.0%
9 105
 
0.9%
Other values (2) 189
 
1.6%

Most occurring blocks

ValueCountFrequency (%)
ASCII 11558
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
* 9685
83.8%
5 382
 
3.3%
. 315
 
2.7%
2 191
 
1.7%
3 180
 
1.6%
4 149
 
1.3%
1 137
 
1.2%
6 115
 
1.0%
8 110
 
1.0%
9 105
 
0.9%
Other values (2) 189
 
1.6%
Distinct305
Distinct (%)3.0%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
2024-04-30T02:02:56.730089image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length7
Median length1
Mean length1.1615
Min length1

Characters and Unicode

Total characters11615
Distinct characters12
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

Unique294 ?
Unique (%)2.9%

Sample

1st row7.7051
2nd row*
3rd row*
4th row*
5th row*
ValueCountFrequency (%)
9684
96.8%
7.7655 3
 
< 0.1%
7.7404 3
 
< 0.1%
15.6449 2
 
< 0.1%
11.6732 2
 
< 0.1%
7.7724 2
 
< 0.1%
7.813 2
 
< 0.1%
7.7869 2
 
< 0.1%
7.795 2
 
< 0.1%
7.8074 2
 
< 0.1%
Other values (295) 296
 
3.0%
2024-04-30T02:02:57.206011image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
* 9684
83.4%
. 316
 
2.7%
7 306
 
2.6%
1 219
 
1.9%
4 179
 
1.5%
6 179
 
1.5%
8 141
 
1.2%
5 137
 
1.2%
3 123
 
1.1%
2 118
 
1.0%
Other values (2) 213
 
1.8%

Most occurring categories

ValueCountFrequency (%)
Other Punctuation 10000
86.1%
Decimal Number 1615
 
13.9%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
7 306
18.9%
1 219
13.6%
4 179
11.1%
6 179
11.1%
8 141
8.7%
5 137
8.5%
3 123
7.6%
2 118
 
7.3%
9 109
 
6.7%
0 104
 
6.4%
Other Punctuation
ValueCountFrequency (%)
* 9684
96.8%
. 316
 
3.2%

Most occurring scripts

ValueCountFrequency (%)
Common 11615
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
* 9684
83.4%
. 316
 
2.7%
7 306
 
2.6%
1 219
 
1.9%
4 179
 
1.5%
6 179
 
1.5%
8 141
 
1.2%
5 137
 
1.2%
3 123
 
1.1%
2 118
 
1.0%
Other values (2) 213
 
1.8%

Most occurring blocks

ValueCountFrequency (%)
ASCII 11615
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
* 9684
83.4%
. 316
 
2.7%
7 306
 
2.6%
1 219
 
1.9%
4 179
 
1.5%
6 179
 
1.5%
8 141
 
1.2%
5 137
 
1.2%
3 123
 
1.1%
2 118
 
1.0%
Other values (2) 213
 
1.8%
Distinct317
Distinct (%)3.2%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
2024-04-30T02:02:57.486348image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length7
Median length1
Mean length1.1683
Min length1

Characters and Unicode

Total characters11683
Distinct characters12
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

Unique299 ?
Unique (%)3.0%

Sample

1st row8.1163
2nd row*
3rd row*
4th row*
5th row*
ValueCountFrequency (%)
9663
96.6%
5.4102 4
 
< 0.1%
5.373 3
 
< 0.1%
5.3778 3
 
< 0.1%
5.3813 2
 
< 0.1%
5.3861 2
 
< 0.1%
5.3568 2
 
< 0.1%
5.3578 2
 
< 0.1%
5.3723 2
 
< 0.1%
5.3715 2
 
< 0.1%
Other values (307) 315
 
3.1%
2024-04-30T02:02:57.882206image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
* 9663
82.7%
. 337
 
2.9%
5 279
 
2.4%
4 212
 
1.8%
3 191
 
1.6%
1 172
 
1.5%
7 152
 
1.3%
8 151
 
1.3%
2 142
 
1.2%
0 138
 
1.2%
Other values (2) 246
 
2.1%

Most occurring categories

ValueCountFrequency (%)
Other Punctuation 10000
85.6%
Decimal Number 1683
 
14.4%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
5 279
16.6%
4 212
12.6%
3 191
11.3%
1 172
10.2%
7 152
9.0%
8 151
9.0%
2 142
8.4%
0 138
8.2%
6 133
7.9%
9 113
6.7%
Other Punctuation
ValueCountFrequency (%)
* 9663
96.6%
. 337
 
3.4%

Most occurring scripts

ValueCountFrequency (%)
Common 11683
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
* 9663
82.7%
. 337
 
2.9%
5 279
 
2.4%
4 212
 
1.8%
3 191
 
1.6%
1 172
 
1.5%
7 152
 
1.3%
8 151
 
1.3%
2 142
 
1.2%
0 138
 
1.2%
Other values (2) 246
 
2.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 11683
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
* 9663
82.7%
. 337
 
2.9%
5 279
 
2.4%
4 212
 
1.8%
3 191
 
1.6%
1 172
 
1.5%
7 152
 
1.3%
8 151
 
1.3%
2 142
 
1.2%
0 138
 
1.2%
Other values (2) 246
 
2.1%
Distinct191
Distinct (%)1.9%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
2024-04-30T02:02:58.141267image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length7
Median length1
Mean length1.1018
Min length1

Characters and Unicode

Total characters11018
Distinct characters12
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

Unique180 ?
Unique (%)1.8%

Sample

1st row*
2nd row*
3rd row*
4th row*
5th row*
ValueCountFrequency (%)
9797
98.0%
5.4756 3
 
< 0.1%
5.5438 3
 
< 0.1%
5.4538 3
 
< 0.1%
5.5335 2
 
< 0.1%
8.2734 2
 
< 0.1%
5.5196 2
 
< 0.1%
5.5179 2
 
< 0.1%
5.5163 2
 
< 0.1%
5.5308 2
 
< 0.1%
Other values (181) 182
 
1.8%
2024-04-30T02:02:58.611729image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
* 9797
88.9%
5 229
 
2.1%
. 203
 
1.8%
4 157
 
1.4%
1 98
 
0.9%
3 91
 
0.8%
2 90
 
0.8%
7 81
 
0.7%
6 79
 
0.7%
8 73
 
0.7%
Other values (2) 120
 
1.1%

Most occurring categories

ValueCountFrequency (%)
Other Punctuation 10000
90.8%
Decimal Number 1018
 
9.2%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
5 229
22.5%
4 157
15.4%
1 98
9.6%
3 91
 
8.9%
2 90
 
8.8%
7 81
 
8.0%
6 79
 
7.8%
8 73
 
7.2%
9 66
 
6.5%
0 54
 
5.3%
Other Punctuation
ValueCountFrequency (%)
* 9797
98.0%
. 203
 
2.0%

Most occurring scripts

ValueCountFrequency (%)
Common 11018
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
* 9797
88.9%
5 229
 
2.1%
. 203
 
1.8%
4 157
 
1.4%
1 98
 
0.9%
3 91
 
0.8%
2 90
 
0.8%
7 81
 
0.7%
6 79
 
0.7%
8 73
 
0.7%
Other values (2) 120
 
1.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 11018
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
* 9797
88.9%
5 229
 
2.1%
. 203
 
1.8%
4 157
 
1.4%
1 98
 
0.9%
3 91
 
0.8%
2 90
 
0.8%
7 81
 
0.7%
6 79
 
0.7%
8 73
 
0.7%
Other values (2) 120
 
1.1%
Distinct439
Distinct (%)4.4%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
2024-04-30T02:02:58.845255image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length7
Median length1
Mean length1.3114
Min length1

Characters and Unicode

Total characters13114
Distinct characters12
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

Unique326 ?
Unique (%)3.3%

Sample

1st row4.1843
2nd row*
3rd row*
4th row4.1198
5th row*
ValueCountFrequency (%)
9368
93.7%
4.1151 10
 
0.1%
4.1166 7
 
0.1%
4.0792 7
 
0.1%
4.1201 6
 
0.1%
4.1158 6
 
0.1%
4.1152 5
 
< 0.1%
4.1091 5
 
< 0.1%
4.1095 5
 
< 0.1%
4.0621 4
 
< 0.1%
Other values (429) 577
 
5.8%
2024-04-30T02:02:59.222991image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
* 9368
71.4%
4 714
 
5.4%
. 632
 
4.8%
1 579
 
4.4%
0 332
 
2.5%
2 248
 
1.9%
8 243
 
1.9%
7 210
 
1.6%
5 203
 
1.5%
9 201
 
1.5%
Other values (2) 384
 
2.9%

Most occurring categories

ValueCountFrequency (%)
Other Punctuation 10000
76.3%
Decimal Number 3114
 
23.7%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
4 714
22.9%
1 579
18.6%
0 332
10.7%
2 248
 
8.0%
8 243
 
7.8%
7 210
 
6.7%
5 203
 
6.5%
9 201
 
6.5%
6 198
 
6.4%
3 186
 
6.0%
Other Punctuation
ValueCountFrequency (%)
* 9368
93.7%
. 632
 
6.3%

Most occurring scripts

ValueCountFrequency (%)
Common 13114
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
* 9368
71.4%
4 714
 
5.4%
. 632
 
4.8%
1 579
 
4.4%
0 332
 
2.5%
2 248
 
1.9%
8 243
 
1.9%
7 210
 
1.6%
5 203
 
1.5%
9 201
 
1.5%
Other values (2) 384
 
2.9%

Most occurring blocks

ValueCountFrequency (%)
ASCII 13114
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
* 9368
71.4%
4 714
 
5.4%
. 632
 
4.8%
1 579
 
4.4%
0 332
 
2.5%
2 248
 
1.9%
8 243
 
1.9%
7 210
 
1.6%
5 203
 
1.5%
9 201
 
1.5%
Other values (2) 384
 
2.9%
Distinct91
Distinct (%)0.9%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
2024-04-30T02:02:59.474933image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length7
Median length1
Mean length1.0461
Min length1

Characters and Unicode

Total characters10461
Distinct characters12
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

Unique89 ?
Unique (%)0.9%

Sample

1st row*
2nd row*
3rd row*
4th row*
5th row*
ValueCountFrequency (%)
9909
99.1%
7.0665 2
 
< 0.1%
6.6944 1
 
< 0.1%
7.9879 1
 
< 0.1%
6.1432 1
 
< 0.1%
10.7413 1
 
< 0.1%
6.5824 1
 
< 0.1%
7.1682 1
 
< 0.1%
7.0609 1
 
< 0.1%
9.5396 1
 
< 0.1%
Other values (81) 81
 
0.8%
2024-04-30T02:02:59.820044image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
* 9909
94.7%
. 91
 
0.9%
7 82
 
0.8%
1 62
 
0.6%
4 52
 
0.5%
6 47
 
0.4%
2 46
 
0.4%
0 38
 
0.4%
9 37
 
0.4%
5 33
 
0.3%
Other values (2) 64
 
0.6%

Most occurring categories

ValueCountFrequency (%)
Other Punctuation 10000
95.6%
Decimal Number 461
 
4.4%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
7 82
17.8%
1 62
13.4%
4 52
11.3%
6 47
10.2%
2 46
10.0%
0 38
8.2%
9 37
8.0%
5 33
7.2%
3 32
 
6.9%
8 32
 
6.9%
Other Punctuation
ValueCountFrequency (%)
* 9909
99.1%
. 91
 
0.9%

Most occurring scripts

ValueCountFrequency (%)
Common 10461
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
* 9909
94.7%
. 91
 
0.9%
7 82
 
0.8%
1 62
 
0.6%
4 52
 
0.5%
6 47
 
0.4%
2 46
 
0.4%
0 38
 
0.4%
9 37
 
0.4%
5 33
 
0.3%
Other values (2) 64
 
0.6%

Most occurring blocks

ValueCountFrequency (%)
ASCII 10461
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
* 9909
94.7%
. 91
 
0.9%
7 82
 
0.8%
1 62
 
0.6%
4 52
 
0.5%
6 47
 
0.4%
2 46
 
0.4%
0 38
 
0.4%
9 37
 
0.4%
5 33
 
0.3%
Other values (2) 64
 
0.6%
Distinct357
Distinct (%)3.6%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
2024-04-30T02:03:00.117550image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length7
Median length1
Mean length1.2283
Min length1

Characters and Unicode

Total characters12283
Distinct characters12
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

Unique286 ?
Unique (%)2.9%

Sample

1st row8.7105
2nd row*
3rd row*
4th row*
5th row*
ValueCountFrequency (%)
9539
95.4%
4.2966 7
 
0.1%
4.3609 6
 
0.1%
4.3358 4
 
< 0.1%
4.2982 4
 
< 0.1%
4.3242 4
 
< 0.1%
4.3173 4
 
< 0.1%
4.3441 4
 
< 0.1%
4.2796 3
 
< 0.1%
4.334 3
 
< 0.1%
Other values (347) 422
 
4.2%
2024-04-30T02:03:00.540526image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
* 9539
77.7%
4 571
 
4.6%
. 461
 
3.8%
3 396
 
3.2%
2 260
 
2.1%
7 176
 
1.4%
1 171
 
1.4%
8 159
 
1.3%
5 152
 
1.2%
6 144
 
1.2%
Other values (2) 254
 
2.1%

Most occurring categories

ValueCountFrequency (%)
Other Punctuation 10000
81.4%
Decimal Number 2283
 
18.6%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
4 571
25.0%
3 396
17.3%
2 260
11.4%
7 176
 
7.7%
1 171
 
7.5%
8 159
 
7.0%
5 152
 
6.7%
6 144
 
6.3%
9 142
 
6.2%
0 112
 
4.9%
Other Punctuation
ValueCountFrequency (%)
* 9539
95.4%
. 461
 
4.6%

Most occurring scripts

ValueCountFrequency (%)
Common 12283
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
* 9539
77.7%
4 571
 
4.6%
. 461
 
3.8%
3 396
 
3.2%
2 260
 
2.1%
7 176
 
1.4%
1 171
 
1.4%
8 159
 
1.3%
5 152
 
1.2%
6 144
 
1.2%
Other values (2) 254
 
2.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 12283
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
* 9539
77.7%
4 571
 
4.6%
. 461
 
3.8%
3 396
 
3.2%
2 260
 
2.1%
7 176
 
1.4%
1 171
 
1.4%
8 159
 
1.3%
5 152
 
1.2%
6 144
 
1.2%
Other values (2) 254
 
2.1%
Distinct113
Distinct (%)1.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
2024-04-30T02:03:00.800816image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length7
Median length1
Mean length1.0579
Min length1

Characters and Unicode

Total characters10579
Distinct characters12
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

Unique108 ?
Unique (%)1.1%

Sample

1st row*
2nd row*
3rd row*
4th row*
5th row*
ValueCountFrequency (%)
9884
98.8%
6.0144 2
 
< 0.1%
5.9897 2
 
< 0.1%
5.964 2
 
< 0.1%
6.0224 2
 
< 0.1%
5.2553 1
 
< 0.1%
5.6614 1
 
< 0.1%
9.0216 1
 
< 0.1%
5.9109 1
 
< 0.1%
6.2341 1
 
< 0.1%
Other values (103) 103
 
1.0%
2024-04-30T02:03:01.152358image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
* 9884
93.4%
. 116
 
1.1%
5 82
 
0.8%
6 76
 
0.7%
1 62
 
0.6%
4 60
 
0.6%
8 60
 
0.6%
9 54
 
0.5%
3 51
 
0.5%
2 48
 
0.5%
Other values (2) 86
 
0.8%

Most occurring categories

ValueCountFrequency (%)
Other Punctuation 10000
94.5%
Decimal Number 579
 
5.5%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
5 82
14.2%
6 76
13.1%
1 62
10.7%
4 60
10.4%
8 60
10.4%
9 54
9.3%
3 51
8.8%
2 48
8.3%
7 46
7.9%
0 40
6.9%
Other Punctuation
ValueCountFrequency (%)
* 9884
98.8%
. 116
 
1.2%

Most occurring scripts

ValueCountFrequency (%)
Common 10579
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
* 9884
93.4%
. 116
 
1.1%
5 82
 
0.8%
6 76
 
0.7%
1 62
 
0.6%
4 60
 
0.6%
8 60
 
0.6%
9 54
 
0.5%
3 51
 
0.5%
2 48
 
0.5%
Other values (2) 86
 
0.8%

Most occurring blocks

ValueCountFrequency (%)
ASCII 10579
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
* 9884
93.4%
. 116
 
1.1%
5 82
 
0.8%
6 76
 
0.7%
1 62
 
0.6%
4 60
 
0.6%
8 60
 
0.6%
9 54
 
0.5%
3 51
 
0.5%
2 48
 
0.5%
Other values (2) 86
 
0.8%
Distinct138
Distinct (%)1.4%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
2024-04-30T02:03:01.448138image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length7
Median length1
Mean length1.0723
Min length1

Characters and Unicode

Total characters10723
Distinct characters12
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

Unique131 ?
Unique (%)1.3%

Sample

1st row*
2nd row*
3rd row*
4th row*
5th row*
ValueCountFrequency (%)
9856
98.6%
6.2196 3
 
< 0.1%
6.3816 2
 
< 0.1%
6.2858 2
 
< 0.1%
6.3017 2
 
< 0.1%
6.2866 2
 
< 0.1%
6.312 2
 
< 0.1%
6.4562 1
 
< 0.1%
9.4885 1
 
< 0.1%
5.1398 1
 
< 0.1%
Other values (128) 128
 
1.3%
2024-04-30T02:03:01.860244image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
* 9856
91.9%
. 144
 
1.3%
6 132
 
1.2%
4 86
 
0.8%
2 80
 
0.7%
9 69
 
0.6%
5 65
 
0.6%
8 64
 
0.6%
1 62
 
0.6%
3 61
 
0.6%
Other values (2) 104
 
1.0%

Most occurring categories

ValueCountFrequency (%)
Other Punctuation 10000
93.3%
Decimal Number 723
 
6.7%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
6 132
18.3%
4 86
11.9%
2 80
11.1%
9 69
9.5%
5 65
9.0%
8 64
8.9%
1 62
8.6%
3 61
8.4%
7 56
7.7%
0 48
 
6.6%
Other Punctuation
ValueCountFrequency (%)
* 9856
98.6%
. 144
 
1.4%

Most occurring scripts

ValueCountFrequency (%)
Common 10723
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
* 9856
91.9%
. 144
 
1.3%
6 132
 
1.2%
4 86
 
0.8%
2 80
 
0.7%
9 69
 
0.6%
5 65
 
0.6%
8 64
 
0.6%
1 62
 
0.6%
3 61
 
0.6%
Other values (2) 104
 
1.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 10723
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
* 9856
91.9%
. 144
 
1.3%
6 132
 
1.2%
4 86
 
0.8%
2 80
 
0.7%
9 69
 
0.6%
5 65
 
0.6%
8 64
 
0.6%
1 62
 
0.6%
3 61
 
0.6%
Other values (2) 104
 
1.0%
Distinct139
Distinct (%)1.4%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
2024-04-30T02:03:02.122685image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length7
Median length1
Mean length1.0741
Min length1

Characters and Unicode

Total characters10741
Distinct characters12
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

Unique128 ?
Unique (%)1.3%

Sample

1st row5.4998
2nd row*
3rd row*
4th row*
5th row*
ValueCountFrequency (%)
9851
98.5%
5.3352 3
 
< 0.1%
5.4543 2
 
< 0.1%
5.4998 2
 
< 0.1%
5.5775 2
 
< 0.1%
5.4996 2
 
< 0.1%
5.4198 2
 
< 0.1%
5.3687 2
 
< 0.1%
5.4162 2
 
< 0.1%
5.4201 2
 
< 0.1%
Other values (129) 130
 
1.3%
2024-04-30T02:03:02.498336image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
* 9851
91.7%
5 159
 
1.5%
. 149
 
1.4%
4 101
 
0.9%
1 86
 
0.8%
3 70
 
0.7%
9 61
 
0.6%
6 57
 
0.5%
7 57
 
0.5%
8 56
 
0.5%
Other values (2) 94
 
0.9%

Most occurring categories

ValueCountFrequency (%)
Other Punctuation 10000
93.1%
Decimal Number 741
 
6.9%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
5 159
21.5%
4 101
13.6%
1 86
11.6%
3 70
9.4%
9 61
 
8.2%
6 57
 
7.7%
7 57
 
7.7%
8 56
 
7.6%
2 55
 
7.4%
0 39
 
5.3%
Other Punctuation
ValueCountFrequency (%)
* 9851
98.5%
. 149
 
1.5%

Most occurring scripts

ValueCountFrequency (%)
Common 10741
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
* 9851
91.7%
5 159
 
1.5%
. 149
 
1.4%
4 101
 
0.9%
1 86
 
0.8%
3 70
 
0.7%
9 61
 
0.6%
6 57
 
0.5%
7 57
 
0.5%
8 56
 
0.5%
Other values (2) 94
 
0.9%

Most occurring blocks

ValueCountFrequency (%)
ASCII 10741
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
* 9851
91.7%
5 159
 
1.5%
. 149
 
1.4%
4 101
 
0.9%
1 86
 
0.8%
3 70
 
0.7%
9 61
 
0.6%
6 57
 
0.5%
7 57
 
0.5%
8 56
 
0.5%
Other values (2) 94
 
0.9%
Distinct108
Distinct (%)1.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
2024-04-30T02:03:02.761368image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length7
Median length1
Mean length1.0542
Min length1

Characters and Unicode

Total characters10542
Distinct characters12
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

Unique103 ?
Unique (%)1.0%

Sample

1st row*
2nd row*
3rd row*
4th row*
5th row*
ValueCountFrequency (%)
9889
98.9%
4.95 2
 
< 0.1%
5.0157 2
 
< 0.1%
5.0091 2
 
< 0.1%
4.9137 2
 
< 0.1%
4.048 1
 
< 0.1%
5.0878 1
 
< 0.1%
5.0952 1
 
< 0.1%
7.5136 1
 
< 0.1%
7.7099 1
 
< 0.1%
Other values (98) 98
 
1.0%
2024-04-30T02:03:03.107842image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
* 9889
93.8%
. 111
 
1.1%
5 90
 
0.9%
4 71
 
0.7%
1 65
 
0.6%
7 54
 
0.5%
8 49
 
0.5%
6 47
 
0.4%
2 47
 
0.4%
9 43
 
0.4%
Other values (2) 76
 
0.7%

Most occurring categories

ValueCountFrequency (%)
Other Punctuation 10000
94.9%
Decimal Number 542
 
5.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
5 90
16.6%
4 71
13.1%
1 65
12.0%
7 54
10.0%
8 49
9.0%
6 47
8.7%
2 47
8.7%
9 43
7.9%
0 43
7.9%
3 33
 
6.1%
Other Punctuation
ValueCountFrequency (%)
* 9889
98.9%
. 111
 
1.1%

Most occurring scripts

ValueCountFrequency (%)
Common 10542
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
* 9889
93.8%
. 111
 
1.1%
5 90
 
0.9%
4 71
 
0.7%
1 65
 
0.6%
7 54
 
0.5%
8 49
 
0.5%
6 47
 
0.4%
2 47
 
0.4%
9 43
 
0.4%
Other values (2) 76
 
0.7%

Most occurring blocks

ValueCountFrequency (%)
ASCII 10542
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
* 9889
93.8%
. 111
 
1.1%
5 90
 
0.9%
4 71
 
0.7%
1 65
 
0.6%
7 54
 
0.5%
8 49
 
0.5%
6 47
 
0.4%
2 47
 
0.4%
9 43
 
0.4%
Other values (2) 76
 
0.7%
Distinct43
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
*
9958 
4.4688
 
1
6.7762
 
1
4.469
 
1
6.7778
 
1
Other values (38)
 
38

Length

Max length7
Median length1
Mean length1.0218
Min length1

Unique

Unique42 ?
Unique (%)0.4%

Sample

1st row*
2nd row*
3rd row*
4th row*
5th row*

Common Values

ValueCountFrequency (%)
* 9958
99.6%
4.4688 1
 
< 0.1%
6.7762 1
 
< 0.1%
4.469 1
 
< 0.1%
6.7778 1
 
< 0.1%
6.7607 1
 
< 0.1%
28.7576 1
 
< 0.1%
10.5232 1
 
< 0.1%
7.1354 1
 
< 0.1%
4.5573 1
 
< 0.1%
Other values (33) 33
 
0.3%

Length

2024-04-30T02:03:03.254873image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
9958
99.6%
30.9963 1
 
< 0.1%
20.2976 1
 
< 0.1%
7.1818 1
 
< 0.1%
4.4942 1
 
< 0.1%
13.7753 1
 
< 0.1%
20.9817 1
 
< 0.1%
10.6703 1
 
< 0.1%
9.7752 1
 
< 0.1%
5.1278 1
 
< 0.1%
Other values (33) 33
 
0.3%
Distinct126
Distinct (%)1.3%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
2024-04-30T02:03:03.491740image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length7
Median length1
Mean length1.1361
Min length1

Characters and Unicode

Total characters11361
Distinct characters12
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

Unique84 ?
Unique (%)0.8%

Sample

1st row*
2nd row*
3rd row*
4th row*
5th row*
ValueCountFrequency (%)
9726
97.3%
4.3811 10
 
0.1%
4.4715 8
 
0.1%
4.5349 8
 
0.1%
4.6876 8
 
0.1%
4.6474 7
 
0.1%
4.6428 7
 
0.1%
4.3736 7
 
0.1%
4.6471 7
 
0.1%
4.6219 7
 
0.1%
Other values (116) 205
 
2.1%
2024-04-30T02:03:03.883866image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
* 9726
85.6%
4 445
 
3.9%
. 274
 
2.4%
6 159
 
1.4%
5 146
 
1.3%
1 121
 
1.1%
3 109
 
1.0%
7 88
 
0.8%
8 87
 
0.8%
9 81
 
0.7%
Other values (2) 125
 
1.1%

Most occurring categories

ValueCountFrequency (%)
Other Punctuation 10000
88.0%
Decimal Number 1361
 
12.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
4 445
32.7%
6 159
 
11.7%
5 146
 
10.7%
1 121
 
8.9%
3 109
 
8.0%
7 88
 
6.5%
8 87
 
6.4%
9 81
 
6.0%
2 78
 
5.7%
0 47
 
3.5%
Other Punctuation
ValueCountFrequency (%)
* 9726
97.3%
. 274
 
2.7%

Most occurring scripts

ValueCountFrequency (%)
Common 11361
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
* 9726
85.6%
4 445
 
3.9%
. 274
 
2.4%
6 159
 
1.4%
5 146
 
1.3%
1 121
 
1.1%
3 109
 
1.0%
7 88
 
0.8%
8 87
 
0.8%
9 81
 
0.7%
Other values (2) 125
 
1.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 11361
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
* 9726
85.6%
4 445
 
3.9%
. 274
 
2.4%
6 159
 
1.4%
5 146
 
1.3%
1 121
 
1.1%
3 109
 
1.0%
7 88
 
0.8%
8 87
 
0.8%
9 81
 
0.7%
Other values (2) 125
 
1.1%
Distinct260
Distinct (%)2.6%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
2024-04-30T02:03:04.203218image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length7
Median length1
Mean length1.2604
Min length1

Characters and Unicode

Total characters12604
Distinct characters12
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

Unique245 ?
Unique (%)2.5%

Sample

1st row*
2nd row*
3rd row*
4th row*
5th row6.4611
ValueCountFrequency (%)
9486
94.9%
4.2871 112
 
1.1%
4.2868 91
 
0.9%
4.2873 29
 
0.3%
8.5735 12
 
0.1%
8.5741 6
 
0.1%
8.5746 3
 
< 0.1%
4.2835 2
 
< 0.1%
12.8612 2
 
< 0.1%
4.2867 2
 
< 0.1%
Other values (250) 255
 
2.5%
2024-04-30T02:03:04.661752image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
* 9486
75.3%
. 514
 
4.1%
8 476
 
3.8%
4 458
 
3.6%
2 392
 
3.1%
1 278
 
2.2%
7 265
 
2.1%
6 225
 
1.8%
5 159
 
1.3%
3 138
 
1.1%
Other values (2) 213
 
1.7%

Most occurring categories

ValueCountFrequency (%)
Other Punctuation 10000
79.3%
Decimal Number 2604
 
20.7%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
8 476
18.3%
4 458
17.6%
2 392
15.1%
1 278
10.7%
7 265
10.2%
6 225
8.6%
5 159
 
6.1%
3 138
 
5.3%
9 108
 
4.1%
0 105
 
4.0%
Other Punctuation
ValueCountFrequency (%)
* 9486
94.9%
. 514
 
5.1%

Most occurring scripts

ValueCountFrequency (%)
Common 12604
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
* 9486
75.3%
. 514
 
4.1%
8 476
 
3.8%
4 458
 
3.6%
2 392
 
3.1%
1 278
 
2.2%
7 265
 
2.1%
6 225
 
1.8%
5 159
 
1.3%
3 138
 
1.1%
Other values (2) 213
 
1.7%

Most occurring blocks

ValueCountFrequency (%)
ASCII 12604
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
* 9486
75.3%
. 514
 
4.1%
8 476
 
3.8%
4 458
 
3.6%
2 392
 
3.1%
1 278
 
2.2%
7 265
 
2.1%
6 225
 
1.8%
5 159
 
1.3%
3 138
 
1.1%
Other values (2) 213
 
1.7%

Sample

기준일ID시간대구분행정동코드생활인구순위대도시권거주지코드총생활인구수남자10세부터14세생활인구수남자15세부터19세생활인구수남자20세부터24세생활인구수남자25세부터29세생활인구수남자30세부터34세생활인구수남자35세부터39세생활인구수남자40세부터44세생활인구수남자45세부터49세생활인구수남자50세부터54세생활인구수남자55세부터59세생활인구수남자60세부터64세생활인구수남자65세부터69세생활인구수남자70세부터74세생활인구수남자70세부터79세생활인구수여자10세부터14세생활인구수여자15세부터19세생활인구수여자20세부터24세생활인구수여자25세부터29세생활인구수여자30세부터34세생활인구수여자35세부터39세생활인구수여자40세부터44세생활인구수여자45세부터49세생활인구수여자50세부터54세생활인구수여자55세부터59세생활인구수여자60세부터64세생활인구수여자65세부터69세생활인구수여자70세부터74세생활인구수여자75세부터79세생활인구수장기체류외국인수
460082024042221111061552700088.42175.5019**10.86694.8528*15.7234*******5.1021*7.70518.1163*4.1843*8.7105**5.4998****
2057520240422011710532123600012.6884*********6.3086*******************
491812024042221121576026281853.8631*****************************
57772024042201129055534128118.3441****4.893**************4.1198*********
37512024042201121582092826021.1583*********5.0889******************6.4611
30654202404221113206708520009.9711*******4.0714*********************
437552024042211171058031418008.5905*5.5607***************************
311022024042211135060045411156.2638***************5.2748*************
4743820240422211170555122600015.4235*******************4.0448*********
1619820240422011590530264136012.0305*****************************
기준일ID시간대구분행정동코드생활인구순위대도시권거주지코드총생활인구수남자10세부터14세생활인구수남자15세부터19세생활인구수남자20세부터24세생활인구수남자25세부터29세생활인구수남자30세부터34세생활인구수남자35세부터39세생활인구수남자40세부터44세생활인구수남자45세부터49세생활인구수남자50세부터54세생활인구수남자55세부터59세생활인구수남자60세부터64세생활인구수남자65세부터69세생활인구수남자70세부터74세생활인구수남자70세부터79세생활인구수여자10세부터14세생활인구수여자15세부터19세생활인구수여자20세부터24세생활인구수여자25세부터29세생활인구수여자30세부터34세생활인구수여자35세부터39세생활인구수여자40세부터44세생활인구수여자45세부터49세생활인구수여자50세부터54세생활인구수여자55세부터59세생활인구수여자60세부터64세생활인구수여자65세부터69세생활인구수여자70세부터74세생활인구수여자75세부터79세생활인구수장기체류외국인수
315212024042211135064014136075.6571**20.020510.7861***4.4384******5.25617.4096*4.0895***********
5472720240422211380520152900014.0665*****************************
274482024042211123071025281108.0145***************5.3181*************
559202024042221141066029414803.8986*****************************
1596320240422011560710414157011.0402****************************4.2868
183582024042201165053149415503.1018*****************************
515752024042221129059038281772.1496*****************************
1065820240422011440565282818511.3174****4.8728************************
389942024042211159053043412106.3328*****************************
4149720240422111650581154600022.5692***************5.6009*************