Overview

Dataset statistics

Number of variables33
Number of observations10000
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory2.6 MiB
Average record size in memory277.0 B

Variable types

Categorical2
Numeric3
Text28

Dataset

Description기준일ID,시간대구분,행정동코드,집계구코드,총생활인구수,남자0세부터9세생활인구수,남자10세부터14세생활인구수,남자15세부터19세생활인구수,남자20세부터24세생활인구수,남자25세부터29세생활인구수,남자30세부터34세생활인구수,남자35세부터39세생활인구수,남자40세부터44세생활인구수,남자45세부터49세생활인구수,남자50세부터54세생활인구수,남자55세부터59세생활인구수,남자60세부터64세생활인구수,남자65세부터69세생활인구수,남자70세이상생활인구수,여자0세부터9세생활인구수,여자10세부터14세생활인구수,여자15세부터19세생활인구수,여자20세부터24세생활인구수,여자25세부터29세생활인구수,여자30세부터34세생활인구수,여자35세부터39세생활인구수,여자40세부터44세생활인구수,여자45세부터49세생활인구수,여자50세부터54세생활인구수,여자55세부터59세생활인구수,여자60세부터64세생활인구수,여자65세부터69세생활인구수,여자70세이상생활인구수
Author서울특별시
URLhttps://data.seoul.go.kr/dataList/OA-14979/S/1/datasetView.do

Alerts

기준일ID has constant value ""Constant

Reproduction

Analysis started2024-04-29 17:01:28.033580
Analysis finished2024-04-29 17:01:30.666009
Duration2.63 seconds
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

2024-04-30T02:01:30.735201image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-30T02:01:30.816513image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
20240422 10000
100.0%

시간대구분
Categorical

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
23
5335 
22
4665 

Length

Max length2
Median length2
Mean length2
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row23
2nd row23
3rd row23
4th row23
5th row23

Common Values

ValueCountFrequency (%)
23 5335
53.3%
22 4665
46.7%

Length

2024-04-30T02:01:31.051822image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-30T02:01:31.133493image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
23 5335
53.3%
22 4665
46.7%

행정동코드
Real number (ℝ)

Distinct423
Distinct (%)4.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean11437661
Minimum11110515
Maximum11740700
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-04-30T02:01:31.220618image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum11110515
5-th percentile11170660
Q111290770
median11440680
Q311590530
95-th percentile11710561
Maximum11740700
Range630185
Interquartile range (IQR)299760

Descriptive statistics

Standard deviation169180.17
Coefficient of variation (CV)0.014791501
Kurtosis-1.1232492
Mean11437661
Median Absolute Deviation (MAD)149860
Skewness-0.0026651782
Sum1.1437661 × 1011
Variance2.8621931 × 1010
MonotonicityNot monotonic
2024-04-30T02:01:31.337100image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
11380690 65
 
0.7%
11500540 65
 
0.7%
11470640 61
 
0.6%
11350595 60
 
0.6%
11350600 54
 
0.5%
11650651 54
 
0.5%
11500630 50
 
0.5%
11260680 49
 
0.5%
11500615 48
 
0.5%
11470550 48
 
0.5%
Other values (413) 9446
94.5%
ValueCountFrequency (%)
11110515 22
0.2%
11110530 7
 
0.1%
11110540 3
 
< 0.1%
11110550 13
0.1%
11110560 20
0.2%
11110570 7
 
0.1%
11110580 8
 
0.1%
11110600 6
 
0.1%
11110615 2
 
< 0.1%
11110630 6
 
0.1%
ValueCountFrequency (%)
11740700 17
0.2%
11740690 13
0.1%
11740685 23
0.2%
11740660 18
0.2%
11740650 10
0.1%
11740640 7
 
0.1%
11740620 15
0.1%
11740610 12
0.1%
11740600 17
0.2%
11740590 5
 
0.1%

집계구코드
Real number (ℝ)

Distinct8666
Distinct (%)86.7%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1.1138991 × 1012
Minimum1.101053 × 1012
Maximum1.125074 × 1012
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-04-30T02:01:31.468972image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1.101053 × 1012
5-th percentile1.103071 × 1012
Q11.108084 × 1012
median1.114073 × 1012
Q31.120053 × 1012
95-th percentile1.124057 × 1012
Maximum1.125074 × 1012
Range2.4021014 × 1010
Interquartile range (IQR)1.196902 × 1010

Descriptive statistics

Standard deviation6.5175754 × 109
Coefficient of variation (CV)0.0058511364
Kurtosis-1.0779426
Mean1.1138991 × 1012
Median Absolute Deviation (MAD)5.9820092 × 109
Skewness-0.08161803
Sum1.1138991 × 1016
Variance4.2478789 × 1019
MonotonicityNot monotonic
2024-04-30T02:01:31.609800image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1102070020011 2
 
< 0.1%
1119071020401 2
 
< 0.1%
1108078030006 2
 
< 0.1%
1112051040008 2
 
< 0.1%
1122066050402 2
 
< 0.1%
1108081030006 2
 
< 0.1%
1122052040303 2
 
< 0.1%
1117064020102 2
 
< 0.1%
1107062050005 2
 
< 0.1%
1103069010107 2
 
< 0.1%
Other values (8656) 9980
99.8%
ValueCountFrequency (%)
1101053010002 1
< 0.1%
1101053010003 1
< 0.1%
1101053010006 1
< 0.1%
1101053020003 1
< 0.1%
1101053020301 1
< 0.1%
1101053020304 1
< 0.1%
1101053020501 1
< 0.1%
1101054010002 1
< 0.1%
1101054010003 2
< 0.1%
1101055010003 1
< 0.1%
ValueCountFrequency (%)
1125074023904 1
< 0.1%
1125074023903 1
< 0.1%
1125074023901 1
< 0.1%
1125074021302 1
< 0.1%
1125074020202 1
< 0.1%
1125074020201 1
< 0.1%
1125074020102 1
< 0.1%
1125074020034 1
< 0.1%
1125074020033 1
< 0.1%
1125074020031 1
< 0.1%

총생활인구수
Real number (ℝ)

Distinct9990
Distinct (%)99.9%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean527.86748
Minimum0.0003
Maximum18037.683
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-04-30T02:01:31.733075image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0.0003
5-th percentile4.010195
Q1147.7905
median369.49135
Q3678.54102
95-th percentile1563.499
Maximum18037.683
Range18037.683
Interquartile range (IQR)530.75053

Descriptive statistics

Standard deviation689.46512
Coefficient of variation (CV)1.306133
Kurtosis90.262425
Mean527.86748
Median Absolute Deviation (MAD)253.1255
Skewness6.5204846
Sum5278674.8
Variance475362.15
MonotonicityNot monotonic
2024-04-30T02:01:31.854356image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
3.0261 2
 
< 0.1%
109.5995 2
 
< 0.1%
1.8359 2
 
< 0.1%
3.4211 2
 
< 0.1%
3.6581 2
 
< 0.1%
11.6778 2
 
< 0.1%
6.1119 2
 
< 0.1%
1.5993 2
 
< 0.1%
2.9567 2
 
< 0.1%
3.1753 2
 
< 0.1%
Other values (9980) 9980
99.8%
ValueCountFrequency (%)
0.0003 1
< 0.1%
0.0013 1
< 0.1%
0.0021 1
< 0.1%
0.0028 1
< 0.1%
0.0046 1
< 0.1%
0.0055 1
< 0.1%
0.0059 1
< 0.1%
0.0065 1
< 0.1%
0.0129 1
< 0.1%
0.0155 1
< 0.1%
ValueCountFrequency (%)
18037.683 1
< 0.1%
11901.1896 1
< 0.1%
11730.9918 1
< 0.1%
11687.2285 1
< 0.1%
10344.4072 1
< 0.1%
9451.51 1
< 0.1%
9221.923 1
< 0.1%
8884.4201 1
< 0.1%
8823.3569 1
< 0.1%
7839.5152 1
< 0.1%
Distinct7085
Distinct (%)70.9%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
2024-04-30T02:01:32.150635image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length8
Median length7
Mean length5.0377
Min length1

Characters and Unicode

Total characters50377
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

Unique7013 ?
Unique (%)70.1%

Sample

1st row47.1456
2nd row11.3504
3rd row6.8132
4th row14.6501
5th row6.3663
ValueCountFrequency (%)
2844
 
28.4%
7.7375 3
 
< 0.1%
17.1992 2
 
< 0.1%
16.3993 2
 
< 0.1%
11.0212 2
 
< 0.1%
27.1106 2
 
< 0.1%
8.8181 2
 
< 0.1%
4.0721 2
 
< 0.1%
4.4041 2
 
< 0.1%
8.5841 2
 
< 0.1%
Other values (7075) 7137
71.4%
2024-04-30T02:01:32.565429image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
. 7156
14.2%
1 6002
11.9%
2 4833
9.6%
4 4228
8.4%
3 4091
8.1%
5 3950
7.8%
6 3740
7.4%
7 3672
7.3%
8 3623
7.2%
9 3482
6.9%
Other values (2) 5600
11.1%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 40377
80.1%
Other Punctuation 10000
 
19.9%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 6002
14.9%
2 4833
12.0%
4 4228
10.5%
3 4091
10.1%
5 3950
9.8%
6 3740
9.3%
7 3672
9.1%
8 3623
9.0%
9 3482
8.6%
0 2756
6.8%
Other Punctuation
ValueCountFrequency (%)
. 7156
71.6%
* 2844
 
28.4%

Most occurring scripts

ValueCountFrequency (%)
Common 50377
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
. 7156
14.2%
1 6002
11.9%
2 4833
9.6%
4 4228
8.4%
3 4091
8.1%
5 3950
7.8%
6 3740
7.4%
7 3672
7.3%
8 3623
7.2%
9 3482
6.9%
Other values (2) 5600
11.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 50377
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
. 7156
14.2%
1 6002
11.9%
2 4833
9.6%
4 4228
8.4%
3 4091
8.1%
5 3950
7.8%
6 3740
7.4%
7 3672
7.3%
8 3623
7.2%
9 3482
6.9%
Other values (2) 5600
11.1%
Distinct5798
Distinct (%)58.0%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
2024-04-30T02:01:32.811975image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length8
Median length7
Mean length4.1948
Min length1

Characters and Unicode

Total characters41948
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

Unique5690 ?
Unique (%)56.9%

Sample

1st row30.2049
2nd row8.725
3rd row4.7855
4th row7.2295
5th row*
ValueCountFrequency (%)
4093
40.9%
6.186 3
 
< 0.1%
4.1847 3
 
< 0.1%
7.6956 3
 
< 0.1%
11.4263 2
 
< 0.1%
9.7709 2
 
< 0.1%
9.4492 2
 
< 0.1%
8.5122 2
 
< 0.1%
11.4417 2
 
< 0.1%
4.8627 2
 
< 0.1%
Other values (5788) 5886
58.9%
2024-04-30T02:01:33.148009image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
. 5907
14.1%
1 4649
11.1%
* 4093
9.8%
4 3404
8.1%
2 3342
8.0%
5 3290
7.8%
6 3162
7.5%
7 3025
7.2%
8 2994
7.1%
9 2961
7.1%
Other values (2) 5121
12.2%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 31948
76.2%
Other Punctuation 10000
 
23.8%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 4649
14.6%
4 3404
10.7%
2 3342
10.5%
5 3290
10.3%
6 3162
9.9%
7 3025
9.5%
8 2994
9.4%
9 2961
9.3%
3 2928
9.2%
0 2193
6.9%
Other Punctuation
ValueCountFrequency (%)
. 5907
59.1%
* 4093
40.9%

Most occurring scripts

ValueCountFrequency (%)
Common 41948
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
. 5907
14.1%
1 4649
11.1%
* 4093
9.8%
4 3404
8.1%
2 3342
8.0%
5 3290
7.8%
6 3162
7.5%
7 3025
7.2%
8 2994
7.1%
9 2961
7.1%
Other values (2) 5121
12.2%

Most occurring blocks

ValueCountFrequency (%)
ASCII 41948
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
. 5907
14.1%
1 4649
11.1%
* 4093
9.8%
4 3404
8.1%
2 3342
8.0%
5 3290
7.8%
6 3162
7.5%
7 3025
7.2%
8 2994
7.1%
9 2961
7.1%
Other values (2) 5121
12.2%
Distinct6655
Distinct (%)66.5%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
2024-04-30T02:01:33.390098image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length8
Median length7
Mean length4.7359
Min length1

Characters and Unicode

Total characters47359
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

Unique6549 ?
Unique (%)65.5%

Sample

1st row50.6172
2nd row16.5663
3rd row5.6073
4th row8.9523
5th row22.8936
ValueCountFrequency (%)
3239
32.4%
12.0725 3
 
< 0.1%
15.0009 3
 
< 0.1%
5.2468 2
 
< 0.1%
11.4132 2
 
< 0.1%
7.0537 2
 
< 0.1%
16.5012 2
 
< 0.1%
8.9204 2
 
< 0.1%
6.9557 2
 
< 0.1%
10.0273 2
 
< 0.1%
Other values (6645) 6741
67.4%
2024-04-30T02:01:33.733350image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
. 6761
14.3%
1 5615
11.9%
2 4145
8.8%
4 3919
8.3%
5 3701
7.8%
3 3657
7.7%
6 3611
7.6%
7 3529
7.5%
8 3406
7.2%
9 3243
6.8%
Other values (2) 5772
12.2%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 37359
78.9%
Other Punctuation 10000
 
21.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 5615
15.0%
2 4145
11.1%
4 3919
10.5%
5 3701
9.9%
3 3657
9.8%
6 3611
9.7%
7 3529
9.4%
8 3406
9.1%
9 3243
8.7%
0 2533
6.8%
Other Punctuation
ValueCountFrequency (%)
. 6761
67.6%
* 3239
32.4%

Most occurring scripts

ValueCountFrequency (%)
Common 47359
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
. 6761
14.3%
1 5615
11.9%
2 4145
8.8%
4 3919
8.3%
5 3701
7.8%
3 3657
7.7%
6 3611
7.6%
7 3529
7.5%
8 3406
7.2%
9 3243
6.8%
Other values (2) 5772
12.2%

Most occurring blocks

ValueCountFrequency (%)
ASCII 47359
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
. 6761
14.3%
1 5615
11.9%
2 4145
8.8%
4 3919
8.3%
5 3701
7.8%
3 3657
7.7%
6 3611
7.6%
7 3529
7.5%
8 3406
7.2%
9 3243
6.8%
Other values (2) 5772
12.2%
Distinct6868
Distinct (%)68.7%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
2024-04-30T02:01:34.004290image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length8
Median length7
Mean length4.8507
Min length1

Characters and Unicode

Total characters48507
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

Unique6787 ?
Unique (%)67.9%

Sample

1st row17.2695
2nd row8.0256
3rd row*
4th row11.5824
5th row84.0277
ValueCountFrequency (%)
3052
30.5%
4.7874 3
 
< 0.1%
7.2539 2
 
< 0.1%
5.3593 2
 
< 0.1%
8.7081 2
 
< 0.1%
11.062 2
 
< 0.1%
11.3159 2
 
< 0.1%
4.2877 2
 
< 0.1%
5.9612 2
 
< 0.1%
18.4544 2
 
< 0.1%
Other values (6858) 6929
69.3%
2024-04-30T02:01:34.413648image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
. 6948
14.3%
1 5758
11.9%
2 4185
8.6%
4 4023
8.3%
5 3896
8.0%
6 3694
7.6%
3 3652
7.5%
7 3591
7.4%
8 3550
7.3%
9 3427
7.1%
Other values (2) 5783
11.9%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 38507
79.4%
Other Punctuation 10000
 
20.6%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 5758
15.0%
2 4185
10.9%
4 4023
10.4%
5 3896
10.1%
6 3694
9.6%
3 3652
9.5%
7 3591
9.3%
8 3550
9.2%
9 3427
8.9%
0 2731
7.1%
Other Punctuation
ValueCountFrequency (%)
. 6948
69.5%
* 3052
30.5%

Most occurring scripts

ValueCountFrequency (%)
Common 48507
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
. 6948
14.3%
1 5758
11.9%
2 4185
8.6%
4 4023
8.3%
5 3896
8.0%
6 3694
7.6%
3 3652
7.5%
7 3591
7.4%
8 3550
7.3%
9 3427
7.1%
Other values (2) 5783
11.9%

Most occurring blocks

ValueCountFrequency (%)
ASCII 48507
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
. 6948
14.3%
1 5758
11.9%
2 4185
8.6%
4 4023
8.3%
5 3896
8.0%
6 3694
7.6%
3 3652
7.5%
7 3591
7.4%
8 3550
7.3%
9 3427
7.1%
Other values (2) 5783
11.9%
Distinct7345
Distinct (%)73.5%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
2024-04-30T02:01:34.726812image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length8
Median length7
Mean length5.1981
Min length1

Characters and Unicode

Total characters51981
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

Unique7251 ?
Unique (%)72.5%

Sample

1st row21.9551
2nd row11.125
3rd row10.0055
4th row15.0549
5th row74.2121
ValueCountFrequency (%)
2563
 
25.6%
4.7591 2
 
< 0.1%
5.2211 2
 
< 0.1%
9.7434 2
 
< 0.1%
38.9216 2
 
< 0.1%
10.3114 2
 
< 0.1%
16.27 2
 
< 0.1%
10.9613 2
 
< 0.1%
11.3461 2
 
< 0.1%
11.9795 2
 
< 0.1%
Other values (7335) 7419
74.2%
2024-04-30T02:01:35.144932image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
. 7437
14.3%
1 6250
12.0%
2 4811
9.3%
4 4271
8.2%
3 4115
7.9%
5 4087
7.9%
7 3914
7.5%
9 3914
7.5%
6 3904
7.5%
8 3838
7.4%
Other values (2) 5440
10.5%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 41981
80.8%
Other Punctuation 10000
 
19.2%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 6250
14.9%
2 4811
11.5%
4 4271
10.2%
3 4115
9.8%
5 4087
9.7%
7 3914
9.3%
9 3914
9.3%
6 3904
9.3%
8 3838
9.1%
0 2877
6.9%
Other Punctuation
ValueCountFrequency (%)
. 7437
74.4%
* 2563
 
25.6%

Most occurring scripts

ValueCountFrequency (%)
Common 51981
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
. 7437
14.3%
1 6250
12.0%
2 4811
9.3%
4 4271
8.2%
3 4115
7.9%
5 4087
7.9%
7 3914
7.5%
9 3914
7.5%
6 3904
7.5%
8 3838
7.4%
Other values (2) 5440
10.5%

Most occurring blocks

ValueCountFrequency (%)
ASCII 51981
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
. 7437
14.3%
1 6250
12.0%
2 4811
9.3%
4 4271
8.2%
3 4115
7.9%
5 4087
7.9%
7 3914
7.5%
9 3914
7.5%
6 3904
7.5%
8 3838
7.4%
Other values (2) 5440
10.5%
Distinct7394
Distinct (%)73.9%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
2024-04-30T02:01:35.423126image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length9
Median length8
Mean length5.2146
Min length1

Characters and Unicode

Total characters52146
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

Unique7308 ?
Unique (%)73.1%

Sample

1st row15.9658
2nd row8.0012
3rd row9.754
4th row6.5912
5th row64.1372
ValueCountFrequency (%)
2522
 
25.2%
9.5662 2
 
< 0.1%
12.4752 2
 
< 0.1%
5.7454 2
 
< 0.1%
8.389 2
 
< 0.1%
4.3775 2
 
< 0.1%
11.674 2
 
< 0.1%
4.2331 2
 
< 0.1%
13.8823 2
 
< 0.1%
7.7523 2
 
< 0.1%
Other values (7384) 7460
74.6%
2024-04-30T02:01:35.835868image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
. 7478
14.3%
1 6243
12.0%
2 4884
9.4%
3 4301
8.2%
4 4280
8.2%
5 4067
7.8%
7 4009
7.7%
6 3883
7.4%
8 3859
7.4%
9 3761
7.2%
Other values (2) 5381
10.3%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 42146
80.8%
Other Punctuation 10000
 
19.2%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 6243
14.8%
2 4884
11.6%
3 4301
10.2%
4 4280
10.2%
5 4067
9.6%
7 4009
9.5%
6 3883
9.2%
8 3859
9.2%
9 3761
8.9%
0 2859
6.8%
Other Punctuation
ValueCountFrequency (%)
. 7478
74.8%
* 2522
 
25.2%

Most occurring scripts

ValueCountFrequency (%)
Common 52146
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
. 7478
14.3%
1 6243
12.0%
2 4884
9.4%
3 4301
8.2%
4 4280
8.2%
5 4067
7.8%
7 4009
7.7%
6 3883
7.4%
8 3859
7.4%
9 3761
7.2%
Other values (2) 5381
10.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 52146
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
. 7478
14.3%
1 6243
12.0%
2 4884
9.4%
3 4301
8.2%
4 4280
8.2%
5 4067
7.8%
7 4009
7.7%
6 3883
7.4%
8 3859
7.4%
9 3761
7.2%
Other values (2) 5381
10.3%
Distinct7746
Distinct (%)77.5%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
2024-04-30T02:01:36.147051image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length9
Median length7
Mean length5.46
Min length1

Characters and Unicode

Total characters54600
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

Unique7681 ?
Unique (%)76.8%

Sample

1st row21.905
2nd row15.0203
3rd row11.0094
4th row6.5167
5th row58.8437
ValueCountFrequency (%)
2190
 
21.9%
4.6508 3
 
< 0.1%
21.4381 2
 
< 0.1%
9.5713 2
 
< 0.1%
27.1923 2
 
< 0.1%
23.6023 2
 
< 0.1%
15.8174 2
 
< 0.1%
8.3129 2
 
< 0.1%
13.9851 2
 
< 0.1%
20.9969 2
 
< 0.1%
Other values (7736) 7791
77.9%
2024-04-30T02:01:36.658008image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
. 7810
14.3%
1 6548
12.0%
2 5400
9.9%
3 4628
8.5%
4 4510
8.3%
5 4307
7.9%
6 4149
7.6%
7 4067
7.4%
8 4000
7.3%
9 3923
7.2%
Other values (2) 5258
9.6%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 44600
81.7%
Other Punctuation 10000
 
18.3%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 6548
14.7%
2 5400
12.1%
3 4628
10.4%
4 4510
10.1%
5 4307
9.7%
6 4149
9.3%
7 4067
9.1%
8 4000
9.0%
9 3923
8.8%
0 3068
6.9%
Other Punctuation
ValueCountFrequency (%)
. 7810
78.1%
* 2190
 
21.9%

Most occurring scripts

ValueCountFrequency (%)
Common 54600
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
. 7810
14.3%
1 6548
12.0%
2 5400
9.9%
3 4628
8.5%
4 4510
8.3%
5 4307
7.9%
6 4149
7.6%
7 4067
7.4%
8 4000
7.3%
9 3923
7.2%
Other values (2) 5258
9.6%

Most occurring blocks

ValueCountFrequency (%)
ASCII 54600
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
. 7810
14.3%
1 6548
12.0%
2 5400
9.9%
3 4628
8.5%
4 4510
8.3%
5 4307
7.9%
6 4149
7.6%
7 4067
7.4%
8 4000
7.3%
9 3923
7.2%
Other values (2) 5258
9.6%
Distinct7753
Distinct (%)77.5%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
2024-04-30T02:01:37.008772image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length9
Median length7
Mean length5.4447
Min length1

Characters and Unicode

Total characters54447
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

Unique7687 ?
Unique (%)76.9%

Sample

1st row36.3784
2nd row17.9807
3rd row*
4th row10.7003
5th row35.8654
ValueCountFrequency (%)
2182
 
21.8%
9.2194 3
 
< 0.1%
18.4708 2
 
< 0.1%
29.4942 2
 
< 0.1%
13.355 2
 
< 0.1%
9.5107 2
 
< 0.1%
29.421 2
 
< 0.1%
4.3844 2
 
< 0.1%
7.8095 2
 
< 0.1%
4.215 2
 
< 0.1%
Other values (7743) 7799
78.0%
2024-04-30T02:01:37.540664image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
. 7818
14.4%
1 6513
12.0%
2 5445
10.0%
3 4531
8.3%
4 4513
8.3%
5 4328
7.9%
6 4084
7.5%
7 4070
7.5%
9 4001
7.3%
8 3938
7.2%
Other values (2) 5206
9.6%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 44447
81.6%
Other Punctuation 10000
 
18.4%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 6513
14.7%
2 5445
12.3%
3 4531
10.2%
4 4513
10.2%
5 4328
9.7%
6 4084
9.2%
7 4070
9.2%
9 4001
9.0%
8 3938
8.9%
0 3024
6.8%
Other Punctuation
ValueCountFrequency (%)
. 7818
78.2%
* 2182
 
21.8%

Most occurring scripts

ValueCountFrequency (%)
Common 54447
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
. 7818
14.4%
1 6513
12.0%
2 5445
10.0%
3 4531
8.3%
4 4513
8.3%
5 4328
7.9%
6 4084
7.5%
7 4070
7.5%
9 4001
7.3%
8 3938
7.2%
Other values (2) 5206
9.6%

Most occurring blocks

ValueCountFrequency (%)
ASCII 54447
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
. 7818
14.4%
1 6513
12.0%
2 5445
10.0%
3 4531
8.3%
4 4513
8.3%
5 4328
7.9%
6 4084
7.5%
7 4070
7.5%
9 4001
7.3%
8 3938
7.2%
Other values (2) 5206
9.6%
Distinct7905
Distinct (%)79.0%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
2024-04-30T02:01:37.854211image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length9
Median length7
Mean length5.5524
Min length1

Characters and Unicode

Total characters55524
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

Unique7832 ?
Unique (%)78.3%

Sample

1st row47.7342
2nd row19.5195
3rd row13.7353
4th row9.9978
5th row40.1292
ValueCountFrequency (%)
2024
 
20.2%
6.8201 2
 
< 0.1%
12.01 2
 
< 0.1%
16.009 2
 
< 0.1%
8.6531 2
 
< 0.1%
17.7717 2
 
< 0.1%
11.2441 2
 
< 0.1%
18.3219 2
 
< 0.1%
11.1853 2
 
< 0.1%
14.9249 2
 
< 0.1%
Other values (7895) 7958
79.6%
2024-04-30T02:01:38.561300image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
. 7976
14.4%
1 6666
12.0%
2 5456
9.8%
3 4808
8.7%
4 4688
8.4%
5 4442
8.0%
6 4210
7.6%
9 4102
7.4%
8 4061
7.3%
7 3955
7.1%
Other values (2) 5160
9.3%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 45524
82.0%
Other Punctuation 10000
 
18.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 6666
14.6%
2 5456
12.0%
3 4808
10.6%
4 4688
10.3%
5 4442
9.8%
6 4210
9.2%
9 4102
9.0%
8 4061
8.9%
7 3955
8.7%
0 3136
6.9%
Other Punctuation
ValueCountFrequency (%)
. 7976
79.8%
* 2024
 
20.2%

Most occurring scripts

ValueCountFrequency (%)
Common 55524
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
. 7976
14.4%
1 6666
12.0%
2 5456
9.8%
3 4808
8.7%
4 4688
8.4%
5 4442
8.0%
6 4210
7.6%
9 4102
7.4%
8 4061
7.3%
7 3955
7.1%
Other values (2) 5160
9.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 55524
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
. 7976
14.4%
1 6666
12.0%
2 5456
9.8%
3 4808
8.7%
4 4688
8.4%
5 4442
8.0%
6 4210
7.6%
9 4102
7.4%
8 4061
7.3%
7 3955
7.1%
Other values (2) 5160
9.3%
Distinct7753
Distinct (%)77.5%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
2024-04-30T02:01:38.848855image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length9
Median length7
Mean length5.4324
Min length1

Characters and Unicode

Total characters54324
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

Unique7679 ?
Unique (%)76.8%

Sample

1st row41.2465
2nd row17.6827
3rd row6.8658
4th row8.1604
5th row17.7689
ValueCountFrequency (%)
2175
 
21.8%
14.9618 2
 
< 0.1%
14.9326 2
 
< 0.1%
14.1618 2
 
< 0.1%
6.8963 2
 
< 0.1%
18.6004 2
 
< 0.1%
13.424 2
 
< 0.1%
9.4951 2
 
< 0.1%
7.9077 2
 
< 0.1%
28.256 2
 
< 0.1%
Other values (7743) 7807
78.1%
2024-04-30T02:01:39.358652image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
. 7825
14.4%
1 6538
12.0%
2 5318
9.8%
3 4546
8.4%
4 4428
8.2%
5 4278
7.9%
7 4180
7.7%
6 4170
7.7%
9 3978
7.3%
8 3924
7.2%
Other values (2) 5139
9.5%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 44324
81.6%
Other Punctuation 10000
 
18.4%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 6538
14.8%
2 5318
12.0%
3 4546
10.3%
4 4428
10.0%
5 4278
9.7%
7 4180
9.4%
6 4170
9.4%
9 3978
9.0%
8 3924
8.9%
0 2964
6.7%
Other Punctuation
ValueCountFrequency (%)
. 7825
78.2%
* 2175
 
21.8%

Most occurring scripts

ValueCountFrequency (%)
Common 54324
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
. 7825
14.4%
1 6538
12.0%
2 5318
9.8%
3 4546
8.4%
4 4428
8.2%
5 4278
7.9%
7 4180
7.7%
6 4170
7.7%
9 3978
7.3%
8 3924
7.2%
Other values (2) 5139
9.5%

Most occurring blocks

ValueCountFrequency (%)
ASCII 54324
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
. 7825
14.4%
1 6538
12.0%
2 5318
9.8%
3 4546
8.4%
4 4428
8.2%
5 4278
7.9%
7 4180
7.7%
6 4170
7.7%
9 3978
7.3%
8 3924
7.2%
Other values (2) 5139
9.5%
Distinct7657
Distinct (%)76.6%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
2024-04-30T02:01:39.673090image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length8
Median length7
Mean length5.3687
Min length1

Characters and Unicode

Total characters53687
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

Unique7565 ?
Unique (%)75.6%

Sample

1st row22.8015
2nd row12.1058
3rd row5.5993
4th row13.8788
5th row23.8238
ValueCountFrequency (%)
2251
 
22.5%
9.5274 3
 
< 0.1%
10.4754 3
 
< 0.1%
12.7372 2
 
< 0.1%
14.9603 2
 
< 0.1%
5.9546 2
 
< 0.1%
4.9911 2
 
< 0.1%
20.6465 2
 
< 0.1%
11.956 2
 
< 0.1%
8.7869 2
 
< 0.1%
Other values (7647) 7729
77.3%
2024-04-30T02:01:40.100794image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
. 7749
14.4%
1 6625
12.3%
2 5173
9.6%
3 4452
8.3%
4 4328
8.1%
5 4284
8.0%
6 4054
7.6%
8 4018
7.5%
7 3966
7.4%
9 3741
7.0%
Other values (2) 5297
9.9%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 43687
81.4%
Other Punctuation 10000
 
18.6%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 6625
15.2%
2 5173
11.8%
3 4452
10.2%
4 4328
9.9%
5 4284
9.8%
6 4054
9.3%
8 4018
9.2%
7 3966
9.1%
9 3741
8.6%
0 3046
7.0%
Other Punctuation
ValueCountFrequency (%)
. 7749
77.5%
* 2251
 
22.5%

Most occurring scripts

ValueCountFrequency (%)
Common 53687
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
. 7749
14.4%
1 6625
12.3%
2 5173
9.6%
3 4452
8.3%
4 4328
8.1%
5 4284
8.0%
6 4054
7.6%
8 4018
7.5%
7 3966
7.4%
9 3741
7.0%
Other values (2) 5297
9.9%

Most occurring blocks

ValueCountFrequency (%)
ASCII 53687
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
. 7749
14.4%
1 6625
12.3%
2 5173
9.6%
3 4452
8.3%
4 4328
8.1%
5 4284
8.0%
6 4054
7.6%
8 4018
7.5%
7 3966
7.4%
9 3741
7.0%
Other values (2) 5297
9.9%
Distinct7268
Distinct (%)72.7%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
2024-04-30T02:01:40.370460image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length8
Median length7
Mean length5.0868
Min length1

Characters and Unicode

Total characters50868
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

Unique7167 ?
Unique (%)71.7%

Sample

1st row35.9509
2nd row11.6272
3rd row7.0292
4th row6.0812
5th row13.1726
ValueCountFrequency (%)
2632
 
26.3%
7.3451 3
 
< 0.1%
8.3038 2
 
< 0.1%
13.2428 2
 
< 0.1%
15.2717 2
 
< 0.1%
15.0165 2
 
< 0.1%
21.9831 2
 
< 0.1%
5.0311 2
 
< 0.1%
12.0376 2
 
< 0.1%
7.5195 2
 
< 0.1%
Other values (7258) 7349
73.5%
2024-04-30T02:01:40.816770image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
. 7368
14.5%
1 6337
12.5%
2 4676
9.2%
4 4075
8.0%
3 4015
7.9%
5 3939
7.7%
6 3843
7.6%
7 3782
7.4%
8 3715
7.3%
9 3693
7.3%
Other values (2) 5425
10.7%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 40868
80.3%
Other Punctuation 10000
 
19.7%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 6337
15.5%
2 4676
11.4%
4 4075
10.0%
3 4015
9.8%
5 3939
9.6%
6 3843
9.4%
7 3782
9.3%
8 3715
9.1%
9 3693
9.0%
0 2793
6.8%
Other Punctuation
ValueCountFrequency (%)
. 7368
73.7%
* 2632
 
26.3%

Most occurring scripts

ValueCountFrequency (%)
Common 50868
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
. 7368
14.5%
1 6337
12.5%
2 4676
9.2%
4 4075
8.0%
3 4015
7.9%
5 3939
7.7%
6 3843
7.6%
7 3782
7.4%
8 3715
7.3%
9 3693
7.3%
Other values (2) 5425
10.7%

Most occurring blocks

ValueCountFrequency (%)
ASCII 50868
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
. 7368
14.5%
1 6337
12.5%
2 4676
9.2%
4 4075
8.0%
3 4015
7.9%
5 3939
7.7%
6 3843
7.6%
7 3782
7.4%
8 3715
7.3%
9 3693
7.3%
Other values (2) 5425
10.7%
Distinct6588
Distinct (%)65.9%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
2024-04-30T02:01:41.156380image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length8
Median length7
Mean length4.636
Min length1

Characters and Unicode

Total characters46360
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

Unique6482 ?
Unique (%)64.8%

Sample

1st row21.3119
2nd row7.3212
3rd row*
4th row5.7388
5th row10.9992
ValueCountFrequency (%)
3308
33.1%
9.7147 2
 
< 0.1%
7.1417 2
 
< 0.1%
6.4243 2
 
< 0.1%
4.3066 2
 
< 0.1%
12.8706 2
 
< 0.1%
16.3311 2
 
< 0.1%
21.5074 2
 
< 0.1%
9.534 2
 
< 0.1%
7.8111 2
 
< 0.1%
Other values (6578) 6674
66.7%
2024-04-30T02:01:41.639659image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
. 6692
14.4%
1 5641
12.2%
2 3889
8.4%
4 3691
8.0%
5 3631
7.8%
8 3482
7.5%
6 3435
7.4%
7 3432
7.4%
9 3324
7.2%
* 3308
7.1%
Other values (2) 5835
12.6%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 36360
78.4%
Other Punctuation 10000
 
21.6%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 5641
15.5%
2 3889
10.7%
4 3691
10.2%
5 3631
10.0%
8 3482
9.6%
6 3435
9.4%
7 3432
9.4%
9 3324
9.1%
3 3285
9.0%
0 2550
7.0%
Other Punctuation
ValueCountFrequency (%)
. 6692
66.9%
* 3308
33.1%

Most occurring scripts

ValueCountFrequency (%)
Common 46360
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
. 6692
14.4%
1 5641
12.2%
2 3889
8.4%
4 3691
8.0%
5 3631
7.8%
8 3482
7.5%
6 3435
7.4%
7 3432
7.4%
9 3324
7.2%
* 3308
7.1%
Other values (2) 5835
12.6%

Most occurring blocks

ValueCountFrequency (%)
ASCII 46360
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
. 6692
14.4%
1 5641
12.2%
2 3889
8.4%
4 3691
8.0%
5 3631
7.8%
8 3482
7.5%
6 3435
7.4%
7 3432
7.4%
9 3324
7.2%
* 3308
7.1%
Other values (2) 5835
12.6%
Distinct7839
Distinct (%)78.4%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
2024-04-30T02:01:41.925124image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length8
Median length7
Mean length5.5142
Min length1

Characters and Unicode

Total characters55142
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

Unique7760 ?
Unique (%)77.6%

Sample

1st row26.7112
2nd row20.8727
3rd row9.6385
4th row14.1296
5th row17.0413
ValueCountFrequency (%)
2082
 
20.8%
10.194 3
 
< 0.1%
20.2829 3
 
< 0.1%
6.7621 2
 
< 0.1%
8.4243 2
 
< 0.1%
8.3259 2
 
< 0.1%
17.4977 2
 
< 0.1%
10.2181 2
 
< 0.1%
11.4827 2
 
< 0.1%
10.3427 2
 
< 0.1%
Other values (7829) 7898
79.0%
2024-04-30T02:01:42.326005image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
. 7918
14.4%
1 6626
12.0%
2 5527
10.0%
3 4701
8.5%
4 4573
8.3%
5 4418
8.0%
6 4266
7.7%
7 4105
7.4%
8 3949
7.2%
9 3937
7.1%
Other values (2) 5122
9.3%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 45142
81.9%
Other Punctuation 10000
 
18.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 6626
14.7%
2 5527
12.2%
3 4701
10.4%
4 4573
10.1%
5 4418
9.8%
6 4266
9.5%
7 4105
9.1%
8 3949
8.7%
9 3937
8.7%
0 3040
6.7%
Other Punctuation
ValueCountFrequency (%)
. 7918
79.2%
* 2082
 
20.8%

Most occurring scripts

ValueCountFrequency (%)
Common 55142
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
. 7918
14.4%
1 6626
12.0%
2 5527
10.0%
3 4701
8.5%
4 4573
8.3%
5 4418
8.0%
6 4266
7.7%
7 4105
7.4%
8 3949
7.2%
9 3937
7.1%
Other values (2) 5122
9.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 55142
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
. 7918
14.4%
1 6626
12.0%
2 5527
10.0%
3 4701
8.5%
4 4573
8.3%
5 4418
8.0%
6 4266
7.7%
7 4105
7.4%
8 3949
7.2%
9 3937
7.1%
Other values (2) 5122
9.3%
Distinct6973
Distinct (%)69.7%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
2024-04-30T02:01:42.605082image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length8
Median length7
Mean length4.9694
Min length1

Characters and Unicode

Total characters49694
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

Unique6886 ?
Unique (%)68.9%

Sample

1st row53.5442
2nd row15.0547
3rd row5.3993
4th row17.3824
5th row*
ValueCountFrequency (%)
2941
29.4%
10.3165 3
 
< 0.1%
8.8924 2
 
< 0.1%
22.6201 2
 
< 0.1%
4.0476 2
 
< 0.1%
6.4344 2
 
< 0.1%
26.7989 2
 
< 0.1%
15.9271 2
 
< 0.1%
6.2463 2
 
< 0.1%
11.287 2
 
< 0.1%
Other values (6963) 7040
70.4%
2024-04-30T02:01:42.998505image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
. 7059
14.2%
1 5761
11.6%
2 4539
9.1%
4 4083
8.2%
3 4003
8.1%
5 3963
8.0%
6 3814
7.7%
7 3704
7.5%
8 3571
7.2%
9 3471
7.0%
Other values (2) 5726
11.5%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 39694
79.9%
Other Punctuation 10000
 
20.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 5761
14.5%
2 4539
11.4%
4 4083
10.3%
3 4003
10.1%
5 3963
10.0%
6 3814
9.6%
7 3704
9.3%
8 3571
9.0%
9 3471
8.7%
0 2785
7.0%
Other Punctuation
ValueCountFrequency (%)
. 7059
70.6%
* 2941
29.4%

Most occurring scripts

ValueCountFrequency (%)
Common 49694
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
. 7059
14.2%
1 5761
11.6%
2 4539
9.1%
4 4083
8.2%
3 4003
8.1%
5 3963
8.0%
6 3814
7.7%
7 3704
7.5%
8 3571
7.2%
9 3471
7.0%
Other values (2) 5726
11.5%

Most occurring blocks

ValueCountFrequency (%)
ASCII 49694
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
. 7059
14.2%
1 5761
11.6%
2 4539
9.1%
4 4083
8.2%
3 4003
8.1%
5 3963
8.0%
6 3814
7.7%
7 3704
7.5%
8 3571
7.2%
9 3471
7.0%
Other values (2) 5726
11.5%
Distinct5635
Distinct (%)56.4%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
2024-04-30T02:01:43.311343image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length8
Median length7
Mean length4.0869
Min length1

Characters and Unicode

Total characters40869
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

Unique5560 ?
Unique (%)55.6%

Sample

1st row33.4652
2nd row11.5546
3rd row*
4th row8.8098
5th row*
ValueCountFrequency (%)
4290
42.9%
6.9466 3
 
< 0.1%
5.6108 3
 
< 0.1%
12.0301 2
 
< 0.1%
4.8073 2
 
< 0.1%
5.0022 2
 
< 0.1%
4.5188 2
 
< 0.1%
12.386 2
 
< 0.1%
12.4257 2
 
< 0.1%
4.7581 2
 
< 0.1%
Other values (5625) 5690
56.9%
2024-04-30T02:01:43.756128image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
. 5710
14.0%
1 4537
11.1%
* 4290
10.5%
2 3338
8.2%
4 3324
8.1%
5 3168
7.8%
6 3093
7.6%
7 2924
7.2%
3 2864
7.0%
8 2752
6.7%
Other values (2) 4869
11.9%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 30869
75.5%
Other Punctuation 10000
 
24.5%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 4537
14.7%
2 3338
10.8%
4 3324
10.8%
5 3168
10.3%
6 3093
10.0%
7 2924
9.5%
3 2864
9.3%
8 2752
8.9%
9 2705
8.8%
0 2164
7.0%
Other Punctuation
ValueCountFrequency (%)
. 5710
57.1%
* 4290
42.9%

Most occurring scripts

ValueCountFrequency (%)
Common 40869
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
. 5710
14.0%
1 4537
11.1%
* 4290
10.5%
2 3338
8.2%
4 3324
8.1%
5 3168
7.8%
6 3093
7.6%
7 2924
7.2%
3 2864
7.0%
8 2752
6.7%
Other values (2) 4869
11.9%

Most occurring blocks

ValueCountFrequency (%)
ASCII 40869
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
. 5710
14.0%
1 4537
11.1%
* 4290
10.5%
2 3338
8.2%
4 3324
8.1%
5 3168
7.8%
6 3093
7.6%
7 2924
7.2%
3 2864
7.0%
8 2752
6.7%
Other values (2) 4869
11.9%
Distinct6620
Distinct (%)66.2%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
2024-04-30T02:01:44.063723image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length8
Median length7
Mean length4.6981
Min length1

Characters and Unicode

Total characters46981
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

Unique6559 ?
Unique (%)65.6%

Sample

1st row57.8351
2nd row14.7333
3rd row*
4th row6.3076
5th row20.5694
ValueCountFrequency (%)
3320
33.2%
4.0304 3
 
< 0.1%
8.5908 2
 
< 0.1%
22.4875 2
 
< 0.1%
15.2284 2
 
< 0.1%
11.8076 2
 
< 0.1%
4.8581 2
 
< 0.1%
5.4564 2
 
< 0.1%
9.1671 2
 
< 0.1%
19.3753 2
 
< 0.1%
Other values (6610) 6661
66.6%
2024-04-30T02:01:44.585645image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
. 6680
14.2%
1 5449
11.6%
2 4123
8.8%
4 3848
8.2%
5 3757
8.0%
3 3558
7.6%
6 3513
7.5%
9 3491
7.4%
7 3470
7.4%
* 3320
7.1%
Other values (2) 5772
12.3%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 36981
78.7%
Other Punctuation 10000
 
21.3%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 5449
14.7%
2 4123
11.1%
4 3848
10.4%
5 3757
10.2%
3 3558
9.6%
6 3513
9.5%
9 3491
9.4%
7 3470
9.4%
8 3268
8.8%
0 2504
6.8%
Other Punctuation
ValueCountFrequency (%)
. 6680
66.8%
* 3320
33.2%

Most occurring scripts

ValueCountFrequency (%)
Common 46981
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
. 6680
14.2%
1 5449
11.6%
2 4123
8.8%
4 3848
8.2%
5 3757
8.0%
3 3558
7.6%
6 3513
7.5%
9 3491
7.4%
7 3470
7.4%
* 3320
7.1%
Other values (2) 5772
12.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 46981
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
. 6680
14.2%
1 5449
11.6%
2 4123
8.8%
4 3848
8.2%
5 3757
8.0%
3 3558
7.6%
6 3513
7.5%
9 3491
7.4%
7 3470
7.4%
* 3320
7.1%
Other values (2) 5772
12.3%
Distinct7320
Distinct (%)73.2%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
2024-04-30T02:01:44.928311image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length9
Median length8
Mean length5.1824
Min length1

Characters and Unicode

Total characters51824
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

Unique7242 ?
Unique (%)72.4%

Sample

1st row82.0475
2nd row13.1361
3rd row7.4624
4th row12.4043
5th row68.6565
ValueCountFrequency (%)
2601
 
26.0%
7.7911 3
 
< 0.1%
11.2856 3
 
< 0.1%
6.9596 3
 
< 0.1%
15.6359 2
 
< 0.1%
11.1982 2
 
< 0.1%
4.1917 2
 
< 0.1%
5.6656 2
 
< 0.1%
24.6498 2
 
< 0.1%
7.4388 2
 
< 0.1%
Other values (7310) 7378
73.8%
2024-04-30T02:01:45.350113image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
. 7399
14.3%
1 6267
12.1%
2 4765
9.2%
4 4320
8.3%
3 4152
8.0%
5 4039
7.8%
6 3958
7.6%
7 3932
7.6%
8 3842
7.4%
9 3683
7.1%
Other values (2) 5467
10.5%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 41824
80.7%
Other Punctuation 10000
 
19.3%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 6267
15.0%
2 4765
11.4%
4 4320
10.3%
3 4152
9.9%
5 4039
9.7%
6 3958
9.5%
7 3932
9.4%
8 3842
9.2%
9 3683
8.8%
0 2866
6.9%
Other Punctuation
ValueCountFrequency (%)
. 7399
74.0%
* 2601
 
26.0%

Most occurring scripts

ValueCountFrequency (%)
Common 51824
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
. 7399
14.3%
1 6267
12.1%
2 4765
9.2%
4 4320
8.3%
3 4152
8.0%
5 4039
7.8%
6 3958
7.6%
7 3932
7.6%
8 3842
7.4%
9 3683
7.1%
Other values (2) 5467
10.5%

Most occurring blocks

ValueCountFrequency (%)
ASCII 51824
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
. 7399
14.3%
1 6267
12.1%
2 4765
9.2%
4 4320
8.3%
3 4152
8.0%
5 4039
7.8%
6 3958
7.6%
7 3932
7.6%
8 3842
7.4%
9 3683
7.1%
Other values (2) 5467
10.5%
Distinct7581
Distinct (%)75.8%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
2024-04-30T02:01:45.676767image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length9
Median length8
Mean length5.3389
Min length1

Characters and Unicode

Total characters53389
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

Unique7534 ?
Unique (%)75.3%

Sample

1st row25.8267
2nd row17.0544
3rd row13.6239
4th row11.2556
5th row72.2715
ValueCountFrequency (%)
2374
 
23.7%
9.5646 2
 
< 0.1%
15.3007 2
 
< 0.1%
17.5304 2
 
< 0.1%
10.5119 2
 
< 0.1%
15.7207 2
 
< 0.1%
8.9855 2
 
< 0.1%
8.1025 2
 
< 0.1%
7.7954 2
 
< 0.1%
10.2285 2
 
< 0.1%
Other values (7571) 7608
76.1%
2024-04-30T02:01:46.153075image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
. 7626
14.3%
1 6374
11.9%
2 5124
9.6%
3 4425
8.3%
4 4373
8.2%
5 4355
8.2%
6 4059
7.6%
8 3942
7.4%
7 3933
7.4%
9 3856
7.2%
Other values (2) 5322
10.0%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 43389
81.3%
Other Punctuation 10000
 
18.7%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 6374
14.7%
2 5124
11.8%
3 4425
10.2%
4 4373
10.1%
5 4355
10.0%
6 4059
9.4%
8 3942
9.1%
7 3933
9.1%
9 3856
8.9%
0 2948
6.8%
Other Punctuation
ValueCountFrequency (%)
. 7626
76.3%
* 2374
 
23.7%

Most occurring scripts

ValueCountFrequency (%)
Common 53389
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
. 7626
14.3%
1 6374
11.9%
2 5124
9.6%
3 4425
8.3%
4 4373
8.2%
5 4355
8.2%
6 4059
7.6%
8 3942
7.4%
7 3933
7.4%
9 3856
7.2%
Other values (2) 5322
10.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 53389
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
. 7626
14.3%
1 6374
11.9%
2 5124
9.6%
3 4425
8.3%
4 4373
8.2%
5 4355
8.2%
6 4059
7.6%
8 3942
7.4%
7 3933
7.4%
9 3856
7.2%
Other values (2) 5322
10.0%
Distinct7591
Distinct (%)75.9%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
2024-04-30T02:01:46.439189image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length8
Median length7
Mean length5.3422
Min length1

Characters and Unicode

Total characters53422
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

Unique7520 ?
Unique (%)75.2%

Sample

1st row22.635
2nd row12.2227
3rd row8.5125
4th row10.4499
5th row59.9177
ValueCountFrequency (%)
2340
 
23.4%
9.2142 2
 
< 0.1%
4.0764 2
 
< 0.1%
22.8587 2
 
< 0.1%
8.2226 2
 
< 0.1%
5.4926 2
 
< 0.1%
4.2867 2
 
< 0.1%
5.8793 2
 
< 0.1%
7.8253 2
 
< 0.1%
6.0905 2
 
< 0.1%
Other values (7581) 7642
76.4%
2024-04-30T02:01:46.834929image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
. 7660
14.3%
1 6339
11.9%
2 5172
9.7%
3 4448
8.3%
4 4377
8.2%
5 4237
7.9%
6 4045
7.6%
7 4001
7.5%
8 3920
7.3%
9 3884
7.3%
Other values (2) 5339
10.0%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 43422
81.3%
Other Punctuation 10000
 
18.7%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 6339
14.6%
2 5172
11.9%
3 4448
10.2%
4 4377
10.1%
5 4237
9.8%
6 4045
9.3%
7 4001
9.2%
8 3920
9.0%
9 3884
8.9%
0 2999
6.9%
Other Punctuation
ValueCountFrequency (%)
. 7660
76.6%
* 2340
 
23.4%

Most occurring scripts

ValueCountFrequency (%)
Common 53422
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
. 7660
14.3%
1 6339
11.9%
2 5172
9.7%
3 4448
8.3%
4 4377
8.2%
5 4237
7.9%
6 4045
7.6%
7 4001
7.5%
8 3920
7.3%
9 3884
7.3%
Other values (2) 5339
10.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 53422
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
. 7660
14.3%
1 6339
11.9%
2 5172
9.7%
3 4448
8.3%
4 4377
8.2%
5 4237
7.9%
6 4045
7.6%
7 4001
7.5%
8 3920
7.3%
9 3884
7.3%
Other values (2) 5339
10.0%
Distinct7852
Distinct (%)78.5%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
2024-04-30T02:01:47.105962image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length9
Median length7
Mean length5.5345
Min length1

Characters and Unicode

Total characters55345
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

Unique7770 ?
Unique (%)77.7%

Sample

1st row34.1186
2nd row18.5957
3rd row9.3694
4th row9.5125
5th row48.5601
ValueCountFrequency (%)
2067
 
20.7%
7.9657 3
 
< 0.1%
8.1217 2
 
< 0.1%
16.4215 2
 
< 0.1%
5.4853 2
 
< 0.1%
15.746 2
 
< 0.1%
35.2288 2
 
< 0.1%
13.1822 2
 
< 0.1%
14.9418 2
 
< 0.1%
17.0874 2
 
< 0.1%
Other values (7842) 7914
79.1%
2024-04-30T02:01:47.487252image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
. 7933
14.3%
1 6410
11.6%
2 5447
9.8%
3 4899
8.9%
4 4588
8.3%
5 4358
7.9%
6 4189
7.6%
8 4178
7.5%
7 4120
7.4%
9 4078
7.4%
Other values (2) 5145
9.3%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 45345
81.9%
Other Punctuation 10000
 
18.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 6410
14.1%
2 5447
12.0%
3 4899
10.8%
4 4588
10.1%
5 4358
9.6%
6 4189
9.2%
8 4178
9.2%
7 4120
9.1%
9 4078
9.0%
0 3078
6.8%
Other Punctuation
ValueCountFrequency (%)
. 7933
79.3%
* 2067
 
20.7%

Most occurring scripts

ValueCountFrequency (%)
Common 55345
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
. 7933
14.3%
1 6410
11.6%
2 5447
9.8%
3 4899
8.9%
4 4588
8.3%
5 4358
7.9%
6 4189
7.6%
8 4178
7.5%
7 4120
7.4%
9 4078
7.4%
Other values (2) 5145
9.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 55345
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
. 7933
14.3%
1 6410
11.6%
2 5447
9.8%
3 4899
8.9%
4 4588
8.3%
5 4358
7.9%
6 4189
7.6%
8 4178
7.5%
7 4120
7.4%
9 4078
7.4%
Other values (2) 5145
9.3%
Distinct7772
Distinct (%)77.7%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
2024-04-30T02:01:47.786738image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length8
Median length7
Mean length5.4672
Min length1

Characters and Unicode

Total characters54672
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

Unique7688 ?
Unique (%)76.9%

Sample

1st row41.5972
2nd row17.5907
3rd row4.3938
4th row11.569
5th row23.682
ValueCountFrequency (%)
2146
 
21.5%
25.3051 2
 
< 0.1%
11.5837 2
 
< 0.1%
12.0169 2
 
< 0.1%
19.8831 2
 
< 0.1%
6.6078 2
 
< 0.1%
8.6777 2
 
< 0.1%
21.168 2
 
< 0.1%
5.7073 2
 
< 0.1%
12.3153 2
 
< 0.1%
Other values (7762) 7836
78.4%
2024-04-30T02:01:48.195733image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
. 7854
14.4%
1 6578
12.0%
2 5325
9.7%
3 4713
8.6%
4 4439
8.1%
6 4301
7.9%
5 4192
7.7%
7 4050
7.4%
9 4014
7.3%
8 4009
7.3%
Other values (2) 5197
9.5%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 44672
81.7%
Other Punctuation 10000
 
18.3%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 6578
14.7%
2 5325
11.9%
3 4713
10.6%
4 4439
9.9%
6 4301
9.6%
5 4192
9.4%
7 4050
9.1%
9 4014
9.0%
8 4009
9.0%
0 3051
6.8%
Other Punctuation
ValueCountFrequency (%)
. 7854
78.5%
* 2146
 
21.5%

Most occurring scripts

ValueCountFrequency (%)
Common 54672
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
. 7854
14.4%
1 6578
12.0%
2 5325
9.7%
3 4713
8.6%
4 4439
8.1%
6 4301
7.9%
5 4192
7.7%
7 4050
7.4%
9 4014
7.3%
8 4009
7.3%
Other values (2) 5197
9.5%

Most occurring blocks

ValueCountFrequency (%)
ASCII 54672
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
. 7854
14.4%
1 6578
12.0%
2 5325
9.7%
3 4713
8.6%
4 4439
8.1%
6 4301
7.9%
5 4192
7.7%
7 4050
7.4%
9 4014
7.3%
8 4009
7.3%
Other values (2) 5197
9.5%
Distinct7879
Distinct (%)78.8%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
2024-04-30T02:01:48.499036image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length8
Median length7
Mean length5.5406
Min length1

Characters and Unicode

Total characters55406
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

Unique7800 ?
Unique (%)78.0%

Sample

1st row61.7475
2nd row24.8949
3rd row8.9059
4th row10.1501
5th row29.0907
ValueCountFrequency (%)
2044
 
20.4%
14.2329 2
 
< 0.1%
17.2405 2
 
< 0.1%
6.5817 2
 
< 0.1%
12.2838 2
 
< 0.1%
9.4605 2
 
< 0.1%
5.7578 2
 
< 0.1%
10.7867 2
 
< 0.1%
11.3598 2
 
< 0.1%
7.5916 2
 
< 0.1%
Other values (7869) 7938
79.4%
2024-04-30T02:01:49.124569image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
. 7956
14.4%
1 6592
11.9%
2 5507
9.9%
3 4699
8.5%
4 4667
8.4%
5 4424
8.0%
6 4199
7.6%
7 4088
7.4%
8 4059
7.3%
9 4048
7.3%
Other values (2) 5167
9.3%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 45406
82.0%
Other Punctuation 10000
 
18.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 6592
14.5%
2 5507
12.1%
3 4699
10.3%
4 4667
10.3%
5 4424
9.7%
6 4199
9.2%
7 4088
9.0%
8 4059
8.9%
9 4048
8.9%
0 3123
6.9%
Other Punctuation
ValueCountFrequency (%)
. 7956
79.6%
* 2044
 
20.4%

Most occurring scripts

ValueCountFrequency (%)
Common 55406
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
. 7956
14.4%
1 6592
11.9%
2 5507
9.9%
3 4699
8.5%
4 4667
8.4%
5 4424
8.0%
6 4199
7.6%
7 4088
7.4%
8 4059
7.3%
9 4048
7.3%
Other values (2) 5167
9.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 55406
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
. 7956
14.4%
1 6592
11.9%
2 5507
9.9%
3 4699
8.5%
4 4667
8.4%
5 4424
8.0%
6 4199
7.6%
7 4088
7.4%
8 4059
7.3%
9 4048
7.3%
Other values (2) 5167
9.3%
Distinct7805
Distinct (%)78.0%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
2024-04-30T02:01:49.384087image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length8
Median length7
Mean length5.4652
Min length1

Characters and Unicode

Total characters54652
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

Unique7727 ?
Unique (%)77.3%

Sample

1st row45.238
2nd row15.7613
3rd row6.5863
4th row11.3594
5th row18.6423
ValueCountFrequency (%)
2118
 
21.2%
8.6609 3
 
< 0.1%
22.8394 2
 
< 0.1%
19.4491 2
 
< 0.1%
19.196 2
 
< 0.1%
15.9933 2
 
< 0.1%
23.687 2
 
< 0.1%
11.8347 2
 
< 0.1%
7.6977 2
 
< 0.1%
9.9788 2
 
< 0.1%
Other values (7795) 7863
78.6%
2024-04-30T02:01:49.790105image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
. 7882
14.4%
1 6554
12.0%
2 5347
9.8%
3 4640
8.5%
4 4499
8.2%
5 4265
7.8%
6 4131
7.6%
9 4084
7.5%
8 4045
7.4%
7 4028
7.4%
Other values (2) 5177
9.5%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 44652
81.7%
Other Punctuation 10000
 
18.3%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 6554
14.7%
2 5347
12.0%
3 4640
10.4%
4 4499
10.1%
5 4265
9.6%
6 4131
9.3%
9 4084
9.1%
8 4045
9.1%
7 4028
9.0%
0 3059
6.9%
Other Punctuation
ValueCountFrequency (%)
. 7882
78.8%
* 2118
 
21.2%

Most occurring scripts

ValueCountFrequency (%)
Common 54652
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
. 7882
14.4%
1 6554
12.0%
2 5347
9.8%
3 4640
8.5%
4 4499
8.2%
5 4265
7.8%
6 4131
7.6%
9 4084
7.5%
8 4045
7.4%
7 4028
7.4%
Other values (2) 5177
9.5%

Most occurring blocks

ValueCountFrequency (%)
ASCII 54652
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
. 7882
14.4%
1 6554
12.0%
2 5347
9.8%
3 4640
8.5%
4 4499
8.2%
5 4265
7.8%
6 4131
7.6%
9 4084
7.5%
8 4045
7.4%
7 4028
7.4%
Other values (2) 5177
9.5%
Distinct7808
Distinct (%)78.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
2024-04-30T02:01:50.062842image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length8
Median length7
Mean length5.4604
Min length1

Characters and Unicode

Total characters54604
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

Unique7751 ?
Unique (%)77.5%

Sample

1st row39.9794
2nd row18.196
3rd row4.7392
4th row14.4892
5th row19.1454
ValueCountFrequency (%)
2137
 
21.4%
25.5456 2
 
< 0.1%
15.3613 2
 
< 0.1%
5.6991 2
 
< 0.1%
15.878 2
 
< 0.1%
21.5438 2
 
< 0.1%
28.575 2
 
< 0.1%
9.4651 2
 
< 0.1%
8.4292 2
 
< 0.1%
6.4047 2
 
< 0.1%
Other values (7798) 7845
78.5%
2024-04-30T02:01:50.452779image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
. 7863
14.4%
1 6540
12.0%
2 5341
9.8%
3 4592
8.4%
4 4447
8.1%
5 4301
7.9%
6 4249
7.8%
9 4062
7.4%
8 4045
7.4%
7 4018
7.4%
Other values (2) 5146
9.4%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 44604
81.7%
Other Punctuation 10000
 
18.3%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 6540
14.7%
2 5341
12.0%
3 4592
10.3%
4 4447
10.0%
5 4301
9.6%
6 4249
9.5%
9 4062
9.1%
8 4045
9.1%
7 4018
9.0%
0 3009
6.7%
Other Punctuation
ValueCountFrequency (%)
. 7863
78.6%
* 2137
 
21.4%

Most occurring scripts

ValueCountFrequency (%)
Common 54604
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
. 7863
14.4%
1 6540
12.0%
2 5341
9.8%
3 4592
8.4%
4 4447
8.1%
5 4301
7.9%
6 4249
7.8%
9 4062
7.4%
8 4045
7.4%
7 4018
7.4%
Other values (2) 5146
9.4%

Most occurring blocks

ValueCountFrequency (%)
ASCII 54604
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
. 7863
14.4%
1 6540
12.0%
2 5341
9.8%
3 4592
8.4%
4 4447
8.1%
5 4301
7.9%
6 4249
7.8%
9 4062
7.4%
8 4045
7.4%
7 4018
7.4%
Other values (2) 5146
9.4%
Distinct7609
Distinct (%)76.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
2024-04-30T02:01:50.735231image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length8
Median length7
Mean length5.3211
Min length1

Characters and Unicode

Total characters53211
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

Unique7534 ?
Unique (%)75.3%

Sample

1st row29.9731
2nd row12.7054
3rd row4.9878
4th row14.0718
5th row14.7809
ValueCountFrequency (%)
2318
 
23.2%
5.3081 2
 
< 0.1%
8.1989 2
 
< 0.1%
6.8375 2
 
< 0.1%
21.3012 2
 
< 0.1%
11.5231 2
 
< 0.1%
11.3401 2
 
< 0.1%
18.3731 2
 
< 0.1%
19.1837 2
 
< 0.1%
19.5313 2
 
< 0.1%
Other values (7599) 7664
76.6%
2024-04-30T02:01:51.258992image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
. 7682
14.4%
1 6624
12.4%
2 5124
9.6%
4 4359
8.2%
3 4270
8.0%
6 4136
7.8%
5 4092
7.7%
7 3978
7.5%
8 3832
7.2%
9 3763
7.1%
Other values (2) 5351
10.1%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 43211
81.2%
Other Punctuation 10000
 
18.8%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 6624
15.3%
2 5124
11.9%
4 4359
10.1%
3 4270
9.9%
6 4136
9.6%
5 4092
9.5%
7 3978
9.2%
8 3832
8.9%
9 3763
8.7%
0 3033
7.0%
Other Punctuation
ValueCountFrequency (%)
. 7682
76.8%
* 2318
 
23.2%

Most occurring scripts

ValueCountFrequency (%)
Common 53211
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
. 7682
14.4%
1 6624
12.4%
2 5124
9.6%
4 4359
8.2%
3 4270
8.0%
6 4136
7.8%
5 4092
7.7%
7 3978
7.5%
8 3832
7.2%
9 3763
7.1%
Other values (2) 5351
10.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 53211
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
. 7682
14.4%
1 6624
12.4%
2 5124
9.6%
4 4359
8.2%
3 4270
8.0%
6 4136
7.8%
5 4092
7.7%
7 3978
7.5%
8 3832
7.2%
9 3763
7.1%
Other values (2) 5351
10.1%
Distinct7168
Distinct (%)71.7%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
2024-04-30T02:01:51.612528image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length8
Median length7
Mean length5.0274
Min length1

Characters and Unicode

Total characters50274
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

Unique7072 ?
Unique (%)70.7%

Sample

1st row25.9468
2nd row10.5925
3rd row7.029
4th row7.0951
5th row7.5426
ValueCountFrequency (%)
2736
 
27.4%
5.1788 3
 
< 0.1%
7.7767 3
 
< 0.1%
18.1203 2
 
< 0.1%
14.793 2
 
< 0.1%
5.3716 2
 
< 0.1%
4.2158 2
 
< 0.1%
22.5186 2
 
< 0.1%
5.8423 2
 
< 0.1%
9.9442 2
 
< 0.1%
Other values (7158) 7244
72.4%
2024-04-30T02:01:52.016238image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
. 7264
14.4%
1 6230
12.4%
2 4672
9.3%
4 4167
8.3%
5 3892
7.7%
3 3770
7.5%
6 3710
7.4%
7 3705
7.4%
9 3700
7.4%
8 3639
7.2%
Other values (2) 5525
11.0%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 40274
80.1%
Other Punctuation 10000
 
19.9%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 6230
15.5%
2 4672
11.6%
4 4167
10.3%
5 3892
9.7%
3 3770
9.4%
6 3710
9.2%
7 3705
9.2%
9 3700
9.2%
8 3639
9.0%
0 2789
6.9%
Other Punctuation
ValueCountFrequency (%)
. 7264
72.6%
* 2736
 
27.4%

Most occurring scripts

ValueCountFrequency (%)
Common 50274
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
. 7264
14.4%
1 6230
12.4%
2 4672
9.3%
4 4167
8.3%
5 3892
7.7%
3 3770
7.5%
6 3710
7.4%
7 3705
7.4%
9 3700
7.4%
8 3639
7.2%
Other values (2) 5525
11.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 50274
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
. 7264
14.4%
1 6230
12.4%
2 4672
9.3%
4 4167
8.3%
5 3892
7.7%
3 3770
7.5%
6 3710
7.4%
7 3705
7.4%
9 3700
7.4%
8 3639
7.2%
Other values (2) 5525
11.0%
Distinct8280
Distinct (%)82.8%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
2024-04-30T02:01:52.305836image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length8
Median length7
Mean length5.852
Min length1

Characters and Unicode

Total characters58520
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

Unique8236 ?
Unique (%)82.4%

Sample

1st row63.306
2nd row43.6724
3rd row11.4607
4th row26.9058
5th row23.3148
ValueCountFrequency (%)
1678
 
16.8%
31.3134 2
 
< 0.1%
22.2401 2
 
< 0.1%
11.1271 2
 
< 0.1%
63.4914 2
 
< 0.1%
16.8728 2
 
< 0.1%
43.6586 2
 
< 0.1%
46.1123 2
 
< 0.1%
6.6516 2
 
< 0.1%
10.0996 2
 
< 0.1%
Other values (8270) 8304
83.0%
2024-04-30T02:01:52.709846image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
. 8322
14.2%
1 6374
10.9%
2 5772
9.9%
3 5277
9.0%
4 5039
8.6%
5 4882
8.3%
6 4631
7.9%
7 4494
7.7%
8 4399
7.5%
9 4340
7.4%
Other values (2) 4990
8.5%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 48520
82.9%
Other Punctuation 10000
 
17.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 6374
13.1%
2 5772
11.9%
3 5277
10.9%
4 5039
10.4%
5 4882
10.1%
6 4631
9.5%
7 4494
9.3%
8 4399
9.1%
9 4340
8.9%
0 3312
6.8%
Other Punctuation
ValueCountFrequency (%)
. 8322
83.2%
* 1678
 
16.8%

Most occurring scripts

ValueCountFrequency (%)
Common 58520
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
. 8322
14.2%
1 6374
10.9%
2 5772
9.9%
3 5277
9.0%
4 5039
8.6%
5 4882
8.3%
6 4631
7.9%
7 4494
7.7%
8 4399
7.5%
9 4340
7.4%
Other values (2) 4990
8.5%

Most occurring blocks

ValueCountFrequency (%)
ASCII 58520
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
. 8322
14.2%
1 6374
10.9%
2 5772
9.9%
3 5277
9.0%
4 5039
8.6%
5 4882
8.3%
6 4631
7.9%
7 4494
7.7%
8 4399
7.5%
9 4340
7.4%
Other values (2) 4990
8.5%

Sample

기준일ID시간대구분행정동코드집계구코드총생활인구수남자0세부터9세생활인구수남자10세부터14세생활인구수남자15세부터19세생활인구수남자20세부터24세생활인구수남자25세부터29세생활인구수남자30세부터34세생활인구수남자35세부터39세생활인구수남자40세부터44세생활인구수남자45세부터49세생활인구수남자50세부터54세생활인구수남자55세부터59세생활인구수남자60세부터64세생활인구수남자65세부터69세생활인구수남자70세이상생활인구수여자0세부터9세생활인구수여자10세부터14세생활인구수여자15세부터19세생활인구수여자20세부터24세생활인구수여자25세부터29세생활인구수여자30세부터34세생활인구수여자35세부터39세생활인구수여자40세부터44세생활인구수여자45세부터49세생활인구수여자50세부터54세생활인구수여자55세부터59세생활인구수여자60세부터64세생활인구수여자65세부터69세생활인구수여자70세이상생활인구수
595720240422231135060011110560104011054.457947.145630.204950.617217.269521.955115.965821.90536.378447.734241.246522.801535.950921.311926.711253.544233.465257.835182.047525.826722.63534.118641.597261.747545.23839.979429.973125.946863.306
136002024042223115906601120068030701431.688311.35048.72516.56638.025611.1258.001215.020317.980719.519517.682712.105811.62727.321220.872715.054711.554614.733313.136117.054412.222718.595717.590724.894915.761318.19612.705410.592543.6724
165562024042223116807301123073020008199.46216.81324.78555.6073*10.00559.75411.0094*13.73536.86585.59937.0292*9.63855.3993**7.462413.62398.51259.36944.39388.90596.58634.73924.98787.02911.4607
58812024042223113505951111079040101311.026414.65017.22958.952311.582415.05496.59126.516710.70039.99788.160413.87886.08125.738814.129617.38248.80986.307612.404311.255610.44999.512511.56910.150111.359414.489214.07187.095126.9058
169402024042223117105621124058010006882.61056.3663*22.893684.027774.212164.137258.843735.865440.129217.768923.823813.172610.999217.0413**20.569468.656572.271559.917748.560123.68229.090718.642319.145414.78097.542623.3148
17322024042223112157701105058020005528.31568.1255*7.000413.569419.583718.398416.342322.637915.569427.633823.142420.520512.226331.68611.16475.17735.775515.64723.055520.145121.737418.137827.140520.207232.949923.655416.665746.453
1509920240422231165058011220590201016.9371****************************
130212024042223115905101120072020003383.1537***6.491532.506128.706631.799810.88620.016911.277223.99710.593910.430329.1139***11.333617.32569.962718.465316.49354.963511.66512.10348.98588.399534.6899
29700202404222211500615111607401020730.228****************************
123392024042223115605401119054031101579.164123.79911.490721.53347.136610.149112.383920.170415.34523.536220.535620.628617.42328.561235.988427.106112.219819.328116.642317.800121.293235.334925.492328.274317.329429.532520.41614.077145.6368
기준일ID시간대구분행정동코드집계구코드총생활인구수남자0세부터9세생활인구수남자10세부터14세생활인구수남자15세부터19세생활인구수남자20세부터24세생활인구수남자25세부터29세생활인구수남자30세부터34세생활인구수남자35세부터39세생활인구수남자40세부터44세생활인구수남자45세부터49세생활인구수남자50세부터54세생활인구수남자55세부터59세생활인구수남자60세부터64세생활인구수남자65세부터69세생활인구수남자70세이상생활인구수여자0세부터9세생활인구수여자10세부터14세생활인구수여자15세부터19세생활인구수여자20세부터24세생활인구수여자25세부터29세생활인구수여자30세부터34세생활인구수여자35세부터39세생활인구수여자40세부터44세생활인구수여자45세부터49세생활인구수여자50세부터54세생활인구수여자55세부터59세생활인구수여자60세부터64세생활인구수여자65세부터69세생활인구수여자70세이상생활인구수
55272024042223113206811110054020603280.430511.75187.86114.82495.75617.33694.89257.77929.782611.73987.339910.17618.57468.579616.25348.74786.63249.33178.01667.24189.632614.018111.146911.818413.349214.479812.479.865821.0309
7620202404222311380690111207105030264.43644.4041************5.1329*************6.2988
212652024042222112306501106087020013894.960651.641422.31185.60228.200922.125129.709360.155546.581147.716826.689117.553220.774817.051735.319223.039610.681624.59919.950622.05536.969680.481549.125461.938513.7635.195829.309916.272360.1495
11620240422231111058011010580100012994.567142.025256.49874.206556.638669.114697.1152140.1111170.341120.724129.01190.609488.249877.8597137.344254.454926.054383.353791.5781111.089399.1843138.467138.732126.6728120.8365130.3652116.740270.9765236.2137
9602024042223112005201104052010403427.4911**6.11828.12477.310113.746328.332821.291616.159516.5187.339913.591411.403621.549914.28037.01459.57025.27216.995328.176429.836822.43226.306614.20119.109916.36658.542437.9014
288822024042222115005101116051020006116.8098**4.4876**5.86635.76347.19385.0791**5.597****4.3668*7.38197.626211.35928.03444.0447****6.6365
203632024042222112157401105055010005286.258913.60724.78677.21065.883716.372914.12237.426315.105613.52188.555316.5157.78356.774114.367511.92734.6954*6.730112.97379.504913.086513.39758.96989.798111.07218.17128.131412.5354
91542024042223114705401115054010008211.16555.86814.951812.93064.50766.31746.3084.33384.92769.9987.862711.73944.7446*8.03754.6727*14.2096.78327.02877.1511*7.994212.24429.825610.55446.51486.748514.6581
2479920240422221135060011110560100011951.669337.603624.091660.5666.177428.455830.623929.826724.121541.679349.158631.612936.010821.645228.897149.539530.9622412.2925560.85737.802825.966226.651848.061849.576944.99237.54638.870325.128252.9578
2584620240422221138053011120720100045.8917****************************