Overview

Dataset statistics

Number of variables34
Number of observations10000
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory2.7 MiB
Average record size in memory285.0 B

Variable types

Categorical1
Numeric4
Text29

Dataset

Description기준일ID,시간대구분,행정동코드,거주지 자치구 코드,총생활인구수,남자10세부터14세생활인구수,남자15세부터19세생활인구수,남자20세부터24세생활인구수,남자25세부터29세생활인구수,남자30세부터34세생활인구수,남자35세부터39세생활인구수,남자40세부터44세생활인구수,남자45세부터49세생활인구수,남자50세부터54세생활인구수,남자55세부터59세생활인구수,남자60세부터64세생활인구수,남자65세부터69세생활인구수,남자70세부터74세생활인구수,남자75세부터79세생활인구수,여자10세부터14세생활인구수,여자15세부터19세생활인구수,여자20세부터24세생활인구수,여자25세부터29세생활인구수,여자30세부터34세생활인구수,여자35세부터39세생활인구수,여자40세부터44세생활인구수,여자45세부터49세생활인구수,여자50세부터54세생활인구수,여자55세부터59세생활인구수,여자60세부터64세생활인구수,여자65세부터69세생활인구수,여자70세부터74세생활인구수,여자75세부터79세생활인구수,장기체류외국인수
Author서울특별시
URLhttps://data.seoul.go.kr/dataList/OA-15377/S/1/datasetView.do

Alerts

기준일ID has constant value ""Constant
시간대구분 has 1813 (18.1%) zerosZeros
총생활인구수 has 413 (4.1%) zerosZeros

Reproduction

Analysis started2024-04-29 17:21:01.739426
Analysis finished2024-04-29 17:21:03.064957
Duration1.33 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

2024-04-30T02:21:03.123164image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-30T02:21:03.192713image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
20240422 10000
100.0%

시간대구분
Real number (ℝ)

ZEROS 

Distinct6
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2.3239
Minimum0
Maximum5
Zeros1813
Zeros (%)18.1%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-04-30T02:21:03.259787image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q11
median2
Q34
95-th percentile5
Maximum5
Range5
Interquartile range (IQR)3

Descriptive statistics

Standard deviation1.6400176
Coefficient of variation (CV)0.70571781
Kurtosis-1.1891601
Mean2.3239
Median Absolute Deviation (MAD)1
Skewness0.081736861
Sum23239
Variance2.6896578
MonotonicityNot monotonic
2024-04-30T02:21:03.348250image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=6)
ValueCountFrequency (%)
0 1813
18.1%
3 1808
18.1%
1 1775
17.8%
2 1762
17.6%
4 1694
16.9%
5 1148
11.5%
ValueCountFrequency (%)
0 1813
18.1%
1 1775
17.8%
2 1762
17.6%
3 1808
18.1%
4 1694
16.9%
5 1148
11.5%
ValueCountFrequency (%)
5 1148
11.5%
4 1694
16.9%
3 1808
18.1%
2 1762
17.6%
1 1775
17.8%
0 1813
18.1%

행정동코드
Real number (ℝ)

Distinct424
Distinct (%)4.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean11417677
Minimum11110515
Maximum11740700
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-04-30T02:21:03.448981image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum11110515
5-th percentile11140570
Q111260575
median11410620
Q311560720
95-th percentile11710647
Maximum11740700
Range630185
Interquartile range (IQR)300145

Descriptive statistics

Standard deviation188326.24
Coefficient of variation (CV)0.01649427
Kurtosis-1.2181674
Mean11417677
Median Absolute Deviation (MAD)150070
Skewness0.099303735
Sum1.1417677 × 1011
Variance3.5466774 × 1010
MonotonicityNot monotonic
2024-04-30T02:21:03.596780image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
11260680 39
 
0.4%
11440690 38
 
0.4%
11200560 37
 
0.4%
11200590 37
 
0.4%
11530550 37
 
0.4%
11440555 37
 
0.4%
11410615 36
 
0.4%
11230545 36
 
0.4%
11290705 35
 
0.4%
11530530 34
 
0.3%
Other values (414) 9634
96.3%
ValueCountFrequency (%)
11110515 26
0.3%
11110530 20
0.2%
11110540 20
0.2%
11110550 27
0.3%
11110560 31
0.3%
11110570 15
0.1%
11110580 25
0.2%
11110600 22
0.2%
11110615 31
0.3%
11110630 27
0.3%
ValueCountFrequency (%)
11740700 27
0.3%
11740690 12
0.1%
11740685 17
0.2%
11740660 23
0.2%
11740650 26
0.3%
11740640 18
0.2%
11740620 24
0.2%
11740610 21
0.2%
11740600 16
0.2%
11740590 17
0.2%
Distinct25
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean11418.496
Minimum11110
Maximum11740
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-04-30T02:21:03.705411image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum11110
5-th percentile11140
Q111260
median11410
Q311560
95-th percentile11710
Maximum11740
Range630
Interquartile range (IQR)300

Descriptive statistics

Standard deviation188.11275
Coefficient of variation (CV)0.016474389
Kurtosis-1.2242973
Mean11418.496
Median Absolute Deviation (MAD)150
Skewness0.068421583
Sum1.1418496 × 108
Variance35386.407
MonotonicityNot monotonic
2024-04-30T02:21:03.812017image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=25)
ValueCountFrequency (%)
11710 453
 
4.5%
11215 443
 
4.4%
11680 440
 
4.4%
11620 422
 
4.2%
11380 421
 
4.2%
11140 412
 
4.1%
11350 411
 
4.1%
11650 410
 
4.1%
11110 407
 
4.1%
11260 406
 
4.1%
Other values (15) 5775
57.8%
ValueCountFrequency (%)
11110 407
4.1%
11140 412
4.1%
11170 390
3.9%
11200 370
3.7%
11215 443
4.4%
11230 397
4.0%
11260 406
4.1%
11290 373
3.7%
11305 372
3.7%
11320 387
3.9%
ValueCountFrequency (%)
11740 388
3.9%
11710 453
4.5%
11680 440
4.4%
11650 410
4.1%
11620 422
4.2%
11590 378
3.8%
11560 399
4.0%
11545 361
3.6%
11530 400
4.0%
11500 398
4.0%

총생활인구수
Real number (ℝ)

ZEROS 

Distinct825
Distinct (%)8.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean153.9582
Minimum0
Maximum18909
Zeros413
Zeros (%)4.1%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-04-30T02:21:03.924782image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile1
Q16
median13
Q329
95-th percentile698.35
Maximum18909
Range18909
Interquartile range (IQR)23

Descriptive statistics

Standard deviation703.99188
Coefficient of variation (CV)4.572617
Kurtosis136.51867
Mean153.9582
Median Absolute Deviation (MAD)9
Skewness9.3253928
Sum1539582
Variance495604.57
MonotonicityNot monotonic
2024-04-30T02:21:04.037835image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
2 531
 
5.3%
3 494
 
4.9%
6 461
 
4.6%
5 445
 
4.5%
0 413
 
4.1%
4 390
 
3.9%
7 373
 
3.7%
8 351
 
3.5%
9 344
 
3.4%
10 314
 
3.1%
Other values (815) 5884
58.8%
ValueCountFrequency (%)
0 413
4.1%
1 206
 
2.1%
2 531
5.3%
3 494
4.9%
4 390
3.9%
5 445
4.5%
6 461
4.6%
7 373
3.7%
8 351
3.5%
9 344
3.4%
ValueCountFrequency (%)
18909 1
< 0.1%
14376 1
< 0.1%
14333 1
< 0.1%
12649 1
< 0.1%
12644 1
< 0.1%
10114 1
< 0.1%
9417 1
< 0.1%
8046 1
< 0.1%
7616 1
< 0.1%
7437 1
< 0.1%
Distinct722
Distinct (%)7.2%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
2024-04-30T02:21:04.375001image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length8
Median length1
Mean length1.4153
Min length1

Characters and Unicode

Total characters14153
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

Unique712 ?
Unique (%)7.1%

Sample

1st row*
2nd row*
3rd row*
4th row*
5th row164.8845
ValueCountFrequency (%)
9268
92.7%
5.3325 3
 
< 0.1%
5.9591 3
 
< 0.1%
5.5014 2
 
< 0.1%
5.5235 2
 
< 0.1%
5.9597 2
 
< 0.1%
5.5026 2
 
< 0.1%
5.6171 2
 
< 0.1%
6.4763 2
 
< 0.1%
5.8281 2
 
< 0.1%
Other values (712) 712
 
7.1%
2024-04-30T02:21:04.920161image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
* 9268
65.5%
. 732
 
5.2%
1 533
 
3.8%
5 524
 
3.7%
2 476
 
3.4%
3 429
 
3.0%
4 427
 
3.0%
6 397
 
2.8%
7 381
 
2.7%
9 348
 
2.5%
Other values (2) 638
 
4.5%

Most occurring categories

ValueCountFrequency (%)
Other Punctuation 10000
70.7%
Decimal Number 4153
29.3%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 533
12.8%
5 524
12.6%
2 476
11.5%
3 429
10.3%
4 427
10.3%
6 397
9.6%
7 381
9.2%
9 348
8.4%
8 344
8.3%
0 294
7.1%
Other Punctuation
ValueCountFrequency (%)
* 9268
92.7%
. 732
 
7.3%

Most occurring scripts

ValueCountFrequency (%)
Common 14153
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
* 9268
65.5%
. 732
 
5.2%
1 533
 
3.8%
5 524
 
3.7%
2 476
 
3.4%
3 429
 
3.0%
4 427
 
3.0%
6 397
 
2.8%
7 381
 
2.7%
9 348
 
2.5%
Other values (2) 638
 
4.5%

Most occurring blocks

ValueCountFrequency (%)
ASCII 14153
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
* 9268
65.5%
. 732
 
5.2%
1 533
 
3.8%
5 524
 
3.7%
2 476
 
3.4%
3 429
 
3.0%
4 427
 
3.0%
6 397
 
2.8%
7 381
 
2.7%
9 348
 
2.5%
Other values (2) 638
 
4.5%
Distinct1063
Distinct (%)10.6%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
2024-04-30T02:21:05.397027image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length8
Median length1
Mean length1.6453
Min length1

Characters and Unicode

Total characters16453
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

Unique995 ?
Unique (%)10.0%

Sample

1st row*
2nd row*
3rd row*
4th row*
5th row176.8595
ValueCountFrequency (%)
8833
88.3%
5.5321 6
 
0.1%
5.4819 5
 
< 0.1%
5.7974 4
 
< 0.1%
5.926 4
 
< 0.1%
5.9274 4
 
< 0.1%
5.5314 4
 
< 0.1%
5.3864 4
 
< 0.1%
5.5327 4
 
< 0.1%
5.7972 4
 
< 0.1%
Other values (1053) 1128
 
11.3%
2024-04-30T02:21:06.016975image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
* 8833
53.7%
. 1167
 
7.1%
5 990
 
6.0%
1 793
 
4.8%
3 693
 
4.2%
4 659
 
4.0%
2 634
 
3.9%
9 595
 
3.6%
6 593
 
3.6%
7 548
 
3.3%
Other values (2) 948
 
5.8%

Most occurring categories

ValueCountFrequency (%)
Other Punctuation 10000
60.8%
Decimal Number 6453
39.2%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
5 990
15.3%
1 793
12.3%
3 693
10.7%
4 659
10.2%
2 634
9.8%
9 595
9.2%
6 593
9.2%
7 548
8.5%
8 547
8.5%
0 401
6.2%
Other Punctuation
ValueCountFrequency (%)
* 8833
88.3%
. 1167
 
11.7%

Most occurring scripts

ValueCountFrequency (%)
Common 16453
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
* 8833
53.7%
. 1167
 
7.1%
5 990
 
6.0%
1 793
 
4.8%
3 693
 
4.2%
4 659
 
4.0%
2 634
 
3.9%
9 595
 
3.6%
6 593
 
3.6%
7 548
 
3.3%
Other values (2) 948
 
5.8%

Most occurring blocks

ValueCountFrequency (%)
ASCII 16453
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
* 8833
53.7%
. 1167
 
7.1%
5 990
 
6.0%
1 793
 
4.8%
3 693
 
4.2%
4 659
 
4.0%
2 634
 
3.9%
9 595
 
3.6%
6 593
 
3.6%
7 548
 
3.3%
Other values (2) 948
 
5.8%
Distinct1224
Distinct (%)12.2%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
2024-04-30T02:21:06.287861image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length8
Median length1
Mean length1.6915
Min length1

Characters and Unicode

Total characters16915
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

Unique1202 ?
Unique (%)12.0%

Sample

1st row*
2nd row*
3rd row*
4th row*
5th row107.8923
ValueCountFrequency (%)
8754
87.5%
7.8614 3
 
< 0.1%
7.8942 3
 
< 0.1%
7.9924 2
 
< 0.1%
6.4123 2
 
< 0.1%
7.9178 2
 
< 0.1%
7.8914 2
 
< 0.1%
7.9378 2
 
< 0.1%
7.9505 2
 
< 0.1%
7.8836 2
 
< 0.1%
Other values (1214) 1226
 
12.3%
2024-04-30T02:21:06.698186image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
* 8754
51.8%
. 1246
 
7.4%
1 889
 
5.3%
7 800
 
4.7%
4 792
 
4.7%
2 691
 
4.1%
8 675
 
4.0%
9 661
 
3.9%
6 650
 
3.8%
5 629
 
3.7%
Other values (2) 1128
 
6.7%

Most occurring categories

ValueCountFrequency (%)
Other Punctuation 10000
59.1%
Decimal Number 6915
40.9%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 889
12.9%
7 800
11.6%
4 792
11.5%
2 691
10.0%
8 675
9.8%
9 661
9.6%
6 650
9.4%
5 629
9.1%
3 602
8.7%
0 526
7.6%
Other Punctuation
ValueCountFrequency (%)
* 8754
87.5%
. 1246
 
12.5%

Most occurring scripts

ValueCountFrequency (%)
Common 16915
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
* 8754
51.8%
. 1246
 
7.4%
1 889
 
5.3%
7 800
 
4.7%
4 792
 
4.7%
2 691
 
4.1%
8 675
 
4.0%
9 661
 
3.9%
6 650
 
3.8%
5 629
 
3.7%
Other values (2) 1128
 
6.7%

Most occurring blocks

ValueCountFrequency (%)
ASCII 16915
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
* 8754
51.8%
. 1246
 
7.4%
1 889
 
5.3%
7 800
 
4.7%
4 792
 
4.7%
2 691
 
4.1%
8 675
 
4.0%
9 661
 
3.9%
6 650
 
3.8%
5 629
 
3.7%
Other values (2) 1128
 
6.7%
Distinct1645
Distinct (%)16.4%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
2024-04-30T02:21:07.024979image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length8
Median length1
Mean length1.922
Min length1

Characters and Unicode

Total characters19220
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

Unique1605 ?
Unique (%)16.1%

Sample

1st row*
2nd row*
3rd row*
4th row*
5th row135.857
ValueCountFrequency (%)
8312
83.1%
5.3858 3
 
< 0.1%
5.3892 3
 
< 0.1%
5.3872 3
 
< 0.1%
5.394 3
 
< 0.1%
5.3894 3
 
< 0.1%
5.4105 2
 
< 0.1%
5.3838 2
 
< 0.1%
5.422 2
 
< 0.1%
5.3452 2
 
< 0.1%
Other values (1635) 1665
 
16.7%
2024-04-30T02:21:07.485688image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
* 8312
43.2%
. 1688
 
8.8%
5 1191
 
6.2%
1 1164
 
6.1%
4 1071
 
5.6%
3 984
 
5.1%
2 914
 
4.8%
8 879
 
4.6%
6 839
 
4.4%
7 801
 
4.2%
Other values (2) 1377
 
7.2%

Most occurring categories

ValueCountFrequency (%)
Other Punctuation 10000
52.0%
Decimal Number 9220
48.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
5 1191
12.9%
1 1164
12.6%
4 1071
11.6%
3 984
10.7%
2 914
9.9%
8 879
9.5%
6 839
9.1%
7 801
8.7%
9 724
7.9%
0 653
7.1%
Other Punctuation
ValueCountFrequency (%)
* 8312
83.1%
. 1688
 
16.9%

Most occurring scripts

ValueCountFrequency (%)
Common 19220
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
* 8312
43.2%
. 1688
 
8.8%
5 1191
 
6.2%
1 1164
 
6.1%
4 1071
 
5.6%
3 984
 
5.1%
2 914
 
4.8%
8 879
 
4.6%
6 839
 
4.4%
7 801
 
4.2%
Other values (2) 1377
 
7.2%

Most occurring blocks

ValueCountFrequency (%)
ASCII 19220
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
* 8312
43.2%
. 1688
 
8.8%
5 1191
 
6.2%
1 1164
 
6.1%
4 1071
 
5.6%
3 984
 
5.1%
2 914
 
4.8%
8 879
 
4.6%
6 839
 
4.4%
7 801
 
4.2%
Other values (2) 1377
 
7.2%
Distinct1542
Distinct (%)15.4%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
2024-04-30T02:21:07.724442image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length8
Median length1
Mean length1.8689
Min length1

Characters and Unicode

Total characters18689
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

Unique1496 ?
Unique (%)15.0%

Sample

1st row*
2nd row*
3rd row*
4th row*
5th row154.9311
ValueCountFrequency (%)
8401
84.0%
4.889 6
 
0.1%
4.9128 5
 
< 0.1%
4.8708 3
 
< 0.1%
4.8992 3
 
< 0.1%
4.8236 3
 
< 0.1%
4.8606 3
 
< 0.1%
4.8946 3
 
< 0.1%
4.876 3
 
< 0.1%
7.3104 2
 
< 0.1%
Other values (1532) 1568
 
15.7%
2024-04-30T02:21:08.086801image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
* 8401
45.0%
. 1599
 
8.6%
4 1212
 
6.5%
1 977
 
5.2%
8 934
 
5.0%
6 867
 
4.6%
9 852
 
4.6%
5 843
 
4.5%
2 838
 
4.5%
7 822
 
4.4%
Other values (2) 1344
 
7.2%

Most occurring categories

ValueCountFrequency (%)
Other Punctuation 10000
53.5%
Decimal Number 8689
46.5%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
4 1212
13.9%
1 977
11.2%
8 934
10.7%
6 867
10.0%
9 852
9.8%
5 843
9.7%
2 838
9.6%
7 822
9.5%
3 799
9.2%
0 545
6.3%
Other Punctuation
ValueCountFrequency (%)
* 8401
84.0%
. 1599
 
16.0%

Most occurring scripts

ValueCountFrequency (%)
Common 18689
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
* 8401
45.0%
. 1599
 
8.6%
4 1212
 
6.5%
1 977
 
5.2%
8 934
 
5.0%
6 867
 
4.6%
9 852
 
4.6%
5 843
 
4.5%
2 838
 
4.5%
7 822
 
4.4%
Other values (2) 1344
 
7.2%

Most occurring blocks

ValueCountFrequency (%)
ASCII 18689
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
* 8401
45.0%
. 1599
 
8.6%
4 1212
 
6.5%
1 977
 
5.2%
8 934
 
5.0%
6 867
 
4.6%
9 852
 
4.6%
5 843
 
4.5%
2 838
 
4.5%
7 822
 
4.4%
Other values (2) 1344
 
7.2%
Distinct1292
Distinct (%)12.9%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
2024-04-30T02:21:08.369068image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length8
Median length1
Mean length1.7393
Min length1

Characters and Unicode

Total characters17393
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

Unique1281 ?
Unique (%)12.8%

Sample

1st row*
2nd row*
3rd row*
4th row*
5th row219.5529
ValueCountFrequency (%)
8697
87.0%
7.2742 3
 
< 0.1%
7.1826 3
 
< 0.1%
4.0348 2
 
< 0.1%
7.2486 2
 
< 0.1%
7.218 2
 
< 0.1%
7.2112 2
 
< 0.1%
7.2448 2
 
< 0.1%
7.2242 2
 
< 0.1%
7.1724 2
 
< 0.1%
Other values (1282) 1283
 
12.8%
2024-04-30T02:21:08.949243image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
* 8697
50.0%
. 1303
 
7.5%
1 1050
 
6.0%
7 846
 
4.9%
2 823
 
4.7%
4 752
 
4.3%
6 721
 
4.1%
8 719
 
4.1%
5 676
 
3.9%
3 640
 
3.7%
Other values (2) 1166
 
6.7%

Most occurring categories

ValueCountFrequency (%)
Other Punctuation 10000
57.5%
Decimal Number 7393
42.5%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 1050
14.2%
7 846
11.4%
2 823
11.1%
4 752
10.2%
6 721
9.8%
8 719
9.7%
5 676
9.1%
3 640
8.7%
9 637
8.6%
0 529
7.2%
Other Punctuation
ValueCountFrequency (%)
* 8697
87.0%
. 1303
 
13.0%

Most occurring scripts

ValueCountFrequency (%)
Common 17393
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
* 8697
50.0%
. 1303
 
7.5%
1 1050
 
6.0%
7 846
 
4.9%
2 823
 
4.7%
4 752
 
4.3%
6 721
 
4.1%
8 719
 
4.1%
5 676
 
3.9%
3 640
 
3.7%
Other values (2) 1166
 
6.7%

Most occurring blocks

ValueCountFrequency (%)
ASCII 17393
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
* 8697
50.0%
. 1303
 
7.5%
1 1050
 
6.0%
7 846
 
4.9%
2 823
 
4.7%
4 752
 
4.3%
6 721
 
4.1%
8 719
 
4.1%
5 676
 
3.9%
3 640
 
3.7%
Other values (2) 1166
 
6.7%
Distinct1180
Distinct (%)11.8%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
2024-04-30T02:21:09.241888image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length8
Median length1
Mean length1.6786
Min length1

Characters and Unicode

Total characters16786
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

Unique1160 ?
Unique (%)11.6%

Sample

1st row*
2nd row*
3rd row*
4th row*
5th row211.4613
ValueCountFrequency (%)
8799
88.0%
6.4068 3
 
< 0.1%
6.3008 3
 
< 0.1%
6.2646 3
 
< 0.1%
4.2534 2
 
< 0.1%
6.2518 2
 
< 0.1%
6.2915 2
 
< 0.1%
11.3165 2
 
< 0.1%
6.3332 2
 
< 0.1%
6.5114 2
 
< 0.1%
Other values (1170) 1180
 
11.8%
2024-04-30T02:21:09.619860image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
* 8799
52.4%
. 1201
 
7.2%
6 849
 
5.1%
1 836
 
5.0%
2 765
 
4.6%
4 710
 
4.2%
3 660
 
3.9%
5 648
 
3.9%
9 647
 
3.9%
8 580
 
3.5%
Other values (2) 1091
 
6.5%

Most occurring categories

ValueCountFrequency (%)
Other Punctuation 10000
59.6%
Decimal Number 6786
40.4%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
6 849
12.5%
1 836
12.3%
2 765
11.3%
4 710
10.5%
3 660
9.7%
5 648
9.5%
9 647
9.5%
8 580
8.5%
7 568
8.4%
0 523
7.7%
Other Punctuation
ValueCountFrequency (%)
* 8799
88.0%
. 1201
 
12.0%

Most occurring scripts

ValueCountFrequency (%)
Common 16786
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
* 8799
52.4%
. 1201
 
7.2%
6 849
 
5.1%
1 836
 
5.0%
2 765
 
4.6%
4 710
 
4.2%
3 660
 
3.9%
5 648
 
3.9%
9 647
 
3.9%
8 580
 
3.5%
Other values (2) 1091
 
6.5%

Most occurring blocks

ValueCountFrequency (%)
ASCII 16786
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
* 8799
52.4%
. 1201
 
7.2%
6 849
 
5.1%
1 836
 
5.0%
2 765
 
4.6%
4 710
 
4.2%
3 660
 
3.9%
5 648
 
3.9%
9 647
 
3.9%
8 580
 
3.5%
Other values (2) 1091
 
6.5%
Distinct1394
Distinct (%)13.9%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
2024-04-30T02:21:09.903337image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length8
Median length1
Mean length1.8419
Min length1

Characters and Unicode

Total characters18419
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

Unique1300 ?
Unique (%)13.0%

Sample

1st row*
2nd row*
3rd row*
4th row*
5th row267.8216
ValueCountFrequency (%)
8472
84.7%
4.0085 5
 
< 0.1%
4.0252 5
 
< 0.1%
4.0201 5
 
< 0.1%
4.0206 4
 
< 0.1%
4.0167 4
 
< 0.1%
4.0257 4
 
< 0.1%
4.0002 4
 
< 0.1%
4.0294 4
 
< 0.1%
4.0283 4
 
< 0.1%
Other values (1384) 1489
 
14.9%
2024-04-30T02:21:10.555368image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
* 8472
46.0%
. 1528
 
8.3%
4 1145
 
6.2%
1 1045
 
5.7%
0 983
 
5.3%
2 878
 
4.8%
7 775
 
4.2%
3 735
 
4.0%
6 729
 
4.0%
8 710
 
3.9%
Other values (2) 1419
 
7.7%

Most occurring categories

ValueCountFrequency (%)
Other Punctuation 10000
54.3%
Decimal Number 8419
45.7%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
4 1145
13.6%
1 1045
12.4%
0 983
11.7%
2 878
10.4%
7 775
9.2%
3 735
8.7%
6 729
8.7%
8 710
8.4%
9 710
8.4%
5 709
8.4%
Other Punctuation
ValueCountFrequency (%)
* 8472
84.7%
. 1528
 
15.3%

Most occurring scripts

ValueCountFrequency (%)
Common 18419
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
* 8472
46.0%
. 1528
 
8.3%
4 1145
 
6.2%
1 1045
 
5.7%
0 983
 
5.3%
2 878
 
4.8%
7 775
 
4.2%
3 735
 
4.0%
6 729
 
4.0%
8 710
 
3.9%
Other values (2) 1419
 
7.7%

Most occurring blocks

ValueCountFrequency (%)
ASCII 18419
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
* 8472
46.0%
. 1528
 
8.3%
4 1145
 
6.2%
1 1045
 
5.7%
0 983
 
5.3%
2 878
 
4.8%
7 775
 
4.2%
3 735
 
4.0%
6 729
 
4.0%
8 710
 
3.9%
Other values (2) 1419
 
7.7%
Distinct1140
Distinct (%)11.4%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
2024-04-30T02:21:10.793114image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length8
Median length1
Mean length1.6477
Min length1

Characters and Unicode

Total characters16477
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

Unique1125 ?
Unique (%)11.2%

Sample

1st row*
2nd row*
3rd row*
4th row*
5th row156.591
ValueCountFrequency (%)
8847
88.5%
6.0517 2
 
< 0.1%
8.3043 2
 
< 0.1%
6.1826 2
 
< 0.1%
6.0949 2
 
< 0.1%
6.0665 2
 
< 0.1%
58.8806 2
 
< 0.1%
6.1936 2
 
< 0.1%
6.1818 2
 
< 0.1%
6.0708 2
 
< 0.1%
Other values (1130) 1135
 
11.3%
2024-04-30T02:21:11.188601image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
* 8847
53.7%
. 1153
 
7.0%
1 913
 
5.5%
6 759
 
4.6%
4 696
 
4.2%
2 694
 
4.2%
5 669
 
4.1%
8 588
 
3.6%
3 586
 
3.6%
9 556
 
3.4%
Other values (2) 1016
 
6.2%

Most occurring categories

ValueCountFrequency (%)
Other Punctuation 10000
60.7%
Decimal Number 6477
39.3%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 913
14.1%
6 759
11.7%
4 696
10.7%
2 694
10.7%
5 669
10.3%
8 588
9.1%
3 586
9.0%
9 556
8.6%
7 550
8.5%
0 466
7.2%
Other Punctuation
ValueCountFrequency (%)
* 8847
88.5%
. 1153
 
11.5%

Most occurring scripts

ValueCountFrequency (%)
Common 16477
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
* 8847
53.7%
. 1153
 
7.0%
1 913
 
5.5%
6 759
 
4.6%
4 696
 
4.2%
2 694
 
4.2%
5 669
 
4.1%
8 588
 
3.6%
3 586
 
3.6%
9 556
 
3.4%
Other values (2) 1016
 
6.2%

Most occurring blocks

ValueCountFrequency (%)
ASCII 16477
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
* 8847
53.7%
. 1153
 
7.0%
1 913
 
5.5%
6 759
 
4.6%
4 696
 
4.2%
2 694
 
4.2%
5 669
 
4.1%
8 588
 
3.6%
3 586
 
3.6%
9 556
 
3.4%
Other values (2) 1016
 
6.2%
Distinct1112
Distinct (%)11.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
2024-04-30T02:21:11.461740image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length8
Median length1
Mean length1.6355
Min length1

Characters and Unicode

Total characters16355
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

Unique1097 ?
Unique (%)11.0%

Sample

1st row*
2nd row*
3rd row*
4th row*
5th row147.6072
ValueCountFrequency (%)
8873
88.7%
6.5348 3
 
< 0.1%
6.5864 3
 
< 0.1%
6.5264 2
 
< 0.1%
6.574 2
 
< 0.1%
6.4612 2
 
< 0.1%
6.5152 2
 
< 0.1%
6.5486 2
 
< 0.1%
6.5556 2
 
< 0.1%
6.5322 2
 
< 0.1%
Other values (1102) 1107
 
11.1%
2024-04-30T02:21:11.863026image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
* 8873
54.3%
. 1127
 
6.9%
6 811
 
5.0%
1 761
 
4.7%
5 738
 
4.5%
2 668
 
4.1%
4 652
 
4.0%
8 603
 
3.7%
3 589
 
3.6%
9 584
 
3.6%
Other values (2) 949
 
5.8%

Most occurring categories

ValueCountFrequency (%)
Other Punctuation 10000
61.1%
Decimal Number 6355
38.9%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
6 811
12.8%
1 761
12.0%
5 738
11.6%
2 668
10.5%
4 652
10.3%
8 603
9.5%
3 589
9.3%
9 584
9.2%
7 535
8.4%
0 414
6.5%
Other Punctuation
ValueCountFrequency (%)
* 8873
88.7%
. 1127
 
11.3%

Most occurring scripts

ValueCountFrequency (%)
Common 16355
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
* 8873
54.3%
. 1127
 
6.9%
6 811
 
5.0%
1 761
 
4.7%
5 738
 
4.5%
2 668
 
4.1%
4 652
 
4.0%
8 603
 
3.7%
3 589
 
3.6%
9 584
 
3.6%
Other values (2) 949
 
5.8%

Most occurring blocks

ValueCountFrequency (%)
ASCII 16355
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
* 8873
54.3%
. 1127
 
6.9%
6 811
 
5.0%
1 761
 
4.7%
5 738
 
4.5%
2 668
 
4.1%
4 652
 
4.0%
8 603
 
3.7%
3 589
 
3.6%
9 584
 
3.6%
Other values (2) 949
 
5.8%
Distinct1057
Distinct (%)10.6%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
2024-04-30T02:21:12.151910image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length8
Median length1
Mean length1.5968
Min length1

Characters and Unicode

Total characters15968
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

Unique1044 ?
Unique (%)10.4%

Sample

1st row*
2nd row*
3rd row*
4th row*
5th row105.1875
ValueCountFrequency (%)
8930
89.3%
5.0926 3
 
< 0.1%
5.1004 3
 
< 0.1%
5.0532 2
 
< 0.1%
5.0976 2
 
< 0.1%
5.1136 2
 
< 0.1%
4.9051 2
 
< 0.1%
5.0552 2
 
< 0.1%
5.2636 2
 
< 0.1%
5.1327 2
 
< 0.1%
Other values (1047) 1050
 
10.5%
2024-04-30T02:21:12.549935image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
* 8930
55.9%
. 1070
 
6.7%
1 793
 
5.0%
5 705
 
4.4%
4 629
 
3.9%
2 609
 
3.8%
7 568
 
3.6%
6 564
 
3.5%
3 554
 
3.5%
9 540
 
3.4%
Other values (2) 1006
 
6.3%

Most occurring categories

ValueCountFrequency (%)
Other Punctuation 10000
62.6%
Decimal Number 5968
37.4%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 793
13.3%
5 705
11.8%
4 629
10.5%
2 609
10.2%
7 568
9.5%
6 564
9.5%
3 554
9.3%
9 540
9.0%
8 509
8.5%
0 497
8.3%
Other Punctuation
ValueCountFrequency (%)
* 8930
89.3%
. 1070
 
10.7%

Most occurring scripts

ValueCountFrequency (%)
Common 15968
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
* 8930
55.9%
. 1070
 
6.7%
1 793
 
5.0%
5 705
 
4.4%
4 629
 
3.9%
2 609
 
3.8%
7 568
 
3.6%
6 564
 
3.5%
3 554
 
3.5%
9 540
 
3.4%
Other values (2) 1006
 
6.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 15968
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
* 8930
55.9%
. 1070
 
6.7%
1 793
 
5.0%
5 705
 
4.4%
4 629
 
3.9%
2 609
 
3.8%
7 568
 
3.6%
6 564
 
3.5%
3 554
 
3.5%
9 540
 
3.4%
Other values (2) 1006
 
6.3%
Distinct973
Distinct (%)9.7%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
2024-04-30T02:21:12.833553image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length8
Median length1
Mean length1.5442
Min length1

Characters and Unicode

Total characters15442
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

Unique963 ?
Unique (%)9.6%

Sample

1st row*
2nd row*
3rd row*
4th row*
5th row81.523
ValueCountFrequency (%)
9016
90.2%
4.4208 4
 
< 0.1%
4.4574 3
 
< 0.1%
4.4153 2
 
< 0.1%
4.4816 2
 
< 0.1%
4.3992 2
 
< 0.1%
4.3548 2
 
< 0.1%
4.4665 2
 
< 0.1%
4.4174 2
 
< 0.1%
4.4796 2
 
< 0.1%
Other values (963) 963
 
9.6%
2024-04-30T02:21:13.216591image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
* 9016
58.4%
. 984
 
6.4%
4 783
 
5.1%
1 615
 
4.0%
2 588
 
3.8%
3 556
 
3.6%
5 551
 
3.6%
6 533
 
3.5%
9 501
 
3.2%
8 496
 
3.2%
Other values (2) 819
 
5.3%

Most occurring categories

ValueCountFrequency (%)
Other Punctuation 10000
64.8%
Decimal Number 5442
35.2%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
4 783
14.4%
1 615
11.3%
2 588
10.8%
3 556
10.2%
5 551
10.1%
6 533
9.8%
9 501
9.2%
8 496
9.1%
7 457
8.4%
0 362
6.7%
Other Punctuation
ValueCountFrequency (%)
* 9016
90.2%
. 984
 
9.8%

Most occurring scripts

ValueCountFrequency (%)
Common 15442
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
* 9016
58.4%
. 984
 
6.4%
4 783
 
5.1%
1 615
 
4.0%
2 588
 
3.8%
3 556
 
3.6%
5 551
 
3.6%
6 533
 
3.5%
9 501
 
3.2%
8 496
 
3.2%
Other values (2) 819
 
5.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 15442
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
* 9016
58.4%
. 984
 
6.4%
4 783
 
5.1%
1 615
 
4.0%
2 588
 
3.8%
3 556
 
3.6%
5 551
 
3.6%
6 533
 
3.5%
9 501
 
3.2%
8 496
 
3.2%
Other values (2) 819
 
5.3%
Distinct840
Distinct (%)8.4%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
2024-04-30T02:21:13.486491image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length8
Median length1
Mean length1.4716
Min length1

Characters and Unicode

Total characters14716
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

Unique834 ?
Unique (%)8.3%

Sample

1st row*
2nd row*
3rd row*
4th row*
5th row64.4061
ValueCountFrequency (%)
9155
91.5%
5.896 3
 
< 0.1%
6.1216 2
 
< 0.1%
6.0202 2
 
< 0.1%
6.0274 2
 
< 0.1%
5.6846 2
 
< 0.1%
32.7761 1
 
< 0.1%
11.9092 1
 
< 0.1%
63.8126 1
 
< 0.1%
9.3547 1
 
< 0.1%
Other values (830) 830
 
8.3%
2024-04-30T02:21:13.847493image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
* 9155
62.2%
. 845
 
5.7%
1 566
 
3.8%
2 531
 
3.6%
4 517
 
3.5%
5 484
 
3.3%
6 476
 
3.2%
8 462
 
3.1%
7 461
 
3.1%
3 452
 
3.1%
Other values (2) 767
 
5.2%

Most occurring categories

ValueCountFrequency (%)
Other Punctuation 10000
68.0%
Decimal Number 4716
32.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 566
12.0%
2 531
11.3%
4 517
11.0%
5 484
10.3%
6 476
10.1%
8 462
9.8%
7 461
9.8%
3 452
9.6%
9 411
8.7%
0 356
7.5%
Other Punctuation
ValueCountFrequency (%)
* 9155
91.5%
. 845
 
8.5%

Most occurring scripts

ValueCountFrequency (%)
Common 14716
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
* 9155
62.2%
. 845
 
5.7%
1 566
 
3.8%
2 531
 
3.6%
4 517
 
3.5%
5 484
 
3.3%
6 476
 
3.2%
8 462
 
3.1%
7 461
 
3.1%
3 452
 
3.1%
Other values (2) 767
 
5.2%

Most occurring blocks

ValueCountFrequency (%)
ASCII 14716
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
* 9155
62.2%
. 845
 
5.7%
1 566
 
3.8%
2 531
 
3.6%
4 517
 
3.5%
5 484
 
3.3%
6 476
 
3.2%
8 462
 
3.1%
7 461
 
3.1%
3 452
 
3.1%
Other values (2) 767
 
5.2%
Distinct715
Distinct (%)7.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
2024-04-30T02:21:14.119690image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length8
Median length1
Mean length1.408
Min length1

Characters and Unicode

Total characters14080
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

Unique709 ?
Unique (%)7.1%

Sample

1st row*
2nd row*
3rd row*
4th row*
5th row57.4198
ValueCountFrequency (%)
9281
92.8%
7.0166 2
 
< 0.1%
7.163 2
 
< 0.1%
7.2602 2
 
< 0.1%
6.8548 2
 
< 0.1%
7.4128 2
 
< 0.1%
57.7236 1
 
< 0.1%
54.4888 1
 
< 0.1%
72.6716 1
 
< 0.1%
20.9327 1
 
< 0.1%
Other values (705) 705
 
7.0%
2024-04-30T02:21:14.523203image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
* 9281
65.9%
. 719
 
5.1%
1 586
 
4.2%
2 458
 
3.3%
4 438
 
3.1%
6 418
 
3.0%
3 408
 
2.9%
5 391
 
2.8%
7 384
 
2.7%
8 367
 
2.6%
Other values (2) 630
 
4.5%

Most occurring categories

ValueCountFrequency (%)
Other Punctuation 10000
71.0%
Decimal Number 4080
29.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 586
14.4%
2 458
11.2%
4 438
10.7%
6 418
10.2%
3 408
10.0%
5 391
9.6%
7 384
9.4%
8 367
9.0%
9 347
8.5%
0 283
6.9%
Other Punctuation
ValueCountFrequency (%)
* 9281
92.8%
. 719
 
7.2%

Most occurring scripts

ValueCountFrequency (%)
Common 14080
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
* 9281
65.9%
. 719
 
5.1%
1 586
 
4.2%
2 458
 
3.3%
4 438
 
3.1%
6 418
 
3.0%
3 408
 
2.9%
5 391
 
2.8%
7 384
 
2.7%
8 367
 
2.6%
Other values (2) 630
 
4.5%

Most occurring blocks

ValueCountFrequency (%)
ASCII 14080
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
* 9281
65.9%
. 719
 
5.1%
1 586
 
4.2%
2 458
 
3.3%
4 438
 
3.1%
6 418
 
3.0%
3 408
 
2.9%
5 391
 
2.8%
7 384
 
2.7%
8 367
 
2.6%
Other values (2) 630
 
4.5%
Distinct687
Distinct (%)6.9%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
2024-04-30T02:21:14.788626image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length8
Median length1
Mean length1.3933
Min length1

Characters and Unicode

Total characters13933
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

Unique681 ?
Unique (%)6.8%

Sample

1st row*
2nd row*
3rd row*
4th row*
5th row121.8298
ValueCountFrequency (%)
9308
93.1%
5.54 3
 
< 0.1%
5.1096 2
 
< 0.1%
5.3177 2
 
< 0.1%
5.2609 2
 
< 0.1%
5.2369 2
 
< 0.1%
42.6909 1
 
< 0.1%
76.2645 1
 
< 0.1%
5.347 1
 
< 0.1%
91.389 1
 
< 0.1%
Other values (677) 677
 
6.8%
2024-04-30T02:21:15.158857image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
* 9308
66.8%
. 692
 
5.0%
1 539
 
3.9%
2 479
 
3.4%
5 450
 
3.2%
4 412
 
3.0%
9 372
 
2.7%
3 364
 
2.6%
6 357
 
2.6%
8 340
 
2.4%
Other values (2) 620
 
4.4%

Most occurring categories

ValueCountFrequency (%)
Other Punctuation 10000
71.8%
Decimal Number 3933
 
28.2%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 539
13.7%
2 479
12.2%
5 450
11.4%
4 412
10.5%
9 372
9.5%
3 364
9.3%
6 357
9.1%
8 340
8.6%
7 333
8.5%
0 287
7.3%
Other Punctuation
ValueCountFrequency (%)
* 9308
93.1%
. 692
 
6.9%

Most occurring scripts

ValueCountFrequency (%)
Common 13933
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
* 9308
66.8%
. 692
 
5.0%
1 539
 
3.9%
2 479
 
3.4%
5 450
 
3.2%
4 412
 
3.0%
9 372
 
2.7%
3 364
 
2.6%
6 357
 
2.6%
8 340
 
2.4%
Other values (2) 620
 
4.4%

Most occurring blocks

ValueCountFrequency (%)
ASCII 13933
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
* 9308
66.8%
. 692
 
5.0%
1 539
 
3.9%
2 479
 
3.4%
5 450
 
3.2%
4 412
 
3.0%
9 372
 
2.7%
3 364
 
2.6%
6 357
 
2.6%
8 340
 
2.4%
Other values (2) 620
 
4.4%
Distinct1054
Distinct (%)10.5%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
2024-04-30T02:21:15.449123image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length8
Median length1
Mean length1.644
Min length1

Characters and Unicode

Total characters16440
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

Unique983 ?
Unique (%)9.8%

Sample

1st row*
2nd row*
3rd row*
4th row*
5th row196.2143
ValueCountFrequency (%)
8842
88.4%
5.2745 5
 
< 0.1%
5.3473 4
 
< 0.1%
5.2138 4
 
< 0.1%
5.3474 4
 
< 0.1%
5.2151 4
 
< 0.1%
5.3097 4
 
< 0.1%
5.347 4
 
< 0.1%
5.293 4
 
< 0.1%
5.404 4
 
< 0.1%
Other values (1044) 1121
 
11.2%
2024-04-30T02:21:15.856637image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
* 8842
53.8%
. 1158
 
7.0%
5 911
 
5.5%
1 841
 
5.1%
2 744
 
4.5%
3 705
 
4.3%
4 662
 
4.0%
7 593
 
3.6%
6 532
 
3.2%
8 507
 
3.1%
Other values (2) 945
 
5.7%

Most occurring categories

ValueCountFrequency (%)
Other Punctuation 10000
60.8%
Decimal Number 6440
39.2%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
5 911
14.1%
1 841
13.1%
2 744
11.6%
3 705
10.9%
4 662
10.3%
7 593
9.2%
6 532
8.3%
8 507
7.9%
0 476
7.4%
9 469
7.3%
Other Punctuation
ValueCountFrequency (%)
* 8842
88.4%
. 1158
 
11.6%

Most occurring scripts

ValueCountFrequency (%)
Common 16440
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
* 8842
53.8%
. 1158
 
7.0%
5 911
 
5.5%
1 841
 
5.1%
2 744
 
4.5%
3 705
 
4.3%
4 662
 
4.0%
7 593
 
3.6%
6 532
 
3.2%
8 507
 
3.1%
Other values (2) 945
 
5.7%

Most occurring blocks

ValueCountFrequency (%)
ASCII 16440
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
* 8842
53.8%
. 1158
 
7.0%
5 911
 
5.5%
1 841
 
5.1%
2 744
 
4.5%
3 705
 
4.3%
4 662
 
4.0%
7 593
 
3.6%
6 532
 
3.2%
8 507
 
3.1%
Other values (2) 945
 
5.7%
Distinct1427
Distinct (%)14.3%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
2024-04-30T02:21:16.137069image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length9
Median length1
Mean length1.814
Min length1

Characters and Unicode

Total characters18140
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

Unique1399 ?
Unique (%)14.0%

Sample

1st row*
2nd row*
3rd row*
4th row*
5th row108.5225
ValueCountFrequency (%)
8544
85.4%
7.7764 4
 
< 0.1%
7.7742 3
 
< 0.1%
7.749 2
 
< 0.1%
7.7474 2
 
< 0.1%
7.8536 2
 
< 0.1%
7.6212 2
 
< 0.1%
7.8045 2
 
< 0.1%
7.7656 2
 
< 0.1%
7.8202 2
 
< 0.1%
Other values (1417) 1435
 
14.3%
2024-04-30T02:21:16.563701image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
* 8544
47.1%
. 1456
 
8.0%
7 1118
 
6.2%
1 1110
 
6.1%
4 891
 
4.9%
5 836
 
4.6%
6 798
 
4.4%
2 760
 
4.2%
8 718
 
4.0%
3 678
 
3.7%
Other values (2) 1231
 
6.8%

Most occurring categories

ValueCountFrequency (%)
Other Punctuation 10000
55.1%
Decimal Number 8140
44.9%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
7 1118
13.7%
1 1110
13.6%
4 891
10.9%
5 836
10.3%
6 798
9.8%
2 760
9.3%
8 718
8.8%
3 678
8.3%
9 661
8.1%
0 570
7.0%
Other Punctuation
ValueCountFrequency (%)
* 8544
85.4%
. 1456
 
14.6%

Most occurring scripts

ValueCountFrequency (%)
Common 18140
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
* 8544
47.1%
. 1456
 
8.0%
7 1118
 
6.2%
1 1110
 
6.1%
4 891
 
4.9%
5 836
 
4.6%
6 798
 
4.4%
2 760
 
4.2%
8 718
 
4.0%
3 678
 
3.7%
Other values (2) 1231
 
6.8%

Most occurring blocks

ValueCountFrequency (%)
ASCII 18140
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
* 8544
47.1%
. 1456
 
8.0%
7 1118
 
6.2%
1 1110
 
6.1%
4 891
 
4.9%
5 836
 
4.6%
6 798
 
4.4%
2 760
 
4.2%
8 718
 
4.0%
3 678
 
3.7%
Other values (2) 1231
 
6.8%
Distinct1711
Distinct (%)17.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
2024-04-30T02:21:16.823674image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length9
Median length1
Mean length1.9702
Min length1

Characters and Unicode

Total characters19702
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

Unique1654 ?
Unique (%)16.5%

Sample

1st row*
2nd row*
3rd row*
4th row*
5th row150.0008
ValueCountFrequency (%)
8229
82.3%
5.3862 4
 
< 0.1%
5.394 3
 
< 0.1%
5.3778 3
 
< 0.1%
5.3986 3
 
< 0.1%
5.3742 2
 
< 0.1%
5.3935 2
 
< 0.1%
5.2337 2
 
< 0.1%
5.4084 2
 
< 0.1%
5.3924 2
 
< 0.1%
Other values (1701) 1748
 
17.5%
2024-04-30T02:21:17.214112image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
* 8229
41.8%
. 1771
 
9.0%
5 1261
 
6.4%
1 1162
 
5.9%
4 1026
 
5.2%
3 1024
 
5.2%
8 968
 
4.9%
6 934
 
4.7%
2 919
 
4.7%
7 883
 
4.5%
Other values (2) 1525
 
7.7%

Most occurring categories

ValueCountFrequency (%)
Other Punctuation 10000
50.8%
Decimal Number 9702
49.2%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
5 1261
13.0%
1 1162
12.0%
4 1026
10.6%
3 1024
10.6%
8 968
10.0%
6 934
9.6%
2 919
9.5%
7 883
9.1%
9 814
8.4%
0 711
7.3%
Other Punctuation
ValueCountFrequency (%)
* 8229
82.3%
. 1771
 
17.7%

Most occurring scripts

ValueCountFrequency (%)
Common 19702
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
* 8229
41.8%
. 1771
 
9.0%
5 1261
 
6.4%
1 1162
 
5.9%
4 1026
 
5.2%
3 1024
 
5.2%
8 968
 
4.9%
6 934
 
4.7%
2 919
 
4.7%
7 883
 
4.5%
Other values (2) 1525
 
7.7%

Most occurring blocks

ValueCountFrequency (%)
ASCII 19702
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
* 8229
41.8%
. 1771
 
9.0%
5 1261
 
6.4%
1 1162
 
5.9%
4 1026
 
5.2%
3 1024
 
5.2%
8 968
 
4.9%
6 934
 
4.7%
2 919
 
4.7%
7 883
 
4.5%
Other values (2) 1525
 
7.7%
Distinct1364
Distinct (%)13.6%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
2024-04-30T02:21:17.460368image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length8
Median length1
Mean length1.7686
Min length1

Characters and Unicode

Total characters17686
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

Unique1339 ?
Unique (%)13.4%

Sample

1st row*
2nd row*
3rd row*
4th row*
5th row171.2244
ValueCountFrequency (%)
8611
86.1%
5.5454 3
 
< 0.1%
5.5338 3
 
< 0.1%
5.518 2
 
< 0.1%
5.5 2
 
< 0.1%
5.5414 2
 
< 0.1%
5.4842 2
 
< 0.1%
5.502 2
 
< 0.1%
5.5202 2
 
< 0.1%
5.4736 2
 
< 0.1%
Other values (1354) 1369
 
13.7%
2024-04-30T02:21:17.811600image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
* 8611
48.7%
. 1389
 
7.9%
5 1055
 
6.0%
1 1003
 
5.7%
4 852
 
4.8%
2 805
 
4.6%
8 747
 
4.2%
3 711
 
4.0%
6 710
 
4.0%
7 665
 
3.8%
Other values (2) 1138
 
6.4%

Most occurring categories

ValueCountFrequency (%)
Other Punctuation 10000
56.5%
Decimal Number 7686
43.5%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
5 1055
13.7%
1 1003
13.0%
4 852
11.1%
2 805
10.5%
8 747
9.7%
3 711
9.3%
6 710
9.2%
7 665
8.7%
9 660
8.6%
0 478
6.2%
Other Punctuation
ValueCountFrequency (%)
* 8611
86.1%
. 1389
 
13.9%

Most occurring scripts

ValueCountFrequency (%)
Common 17686
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
* 8611
48.7%
. 1389
 
7.9%
5 1055
 
6.0%
1 1003
 
5.7%
4 852
 
4.8%
2 805
 
4.6%
8 747
 
4.2%
3 711
 
4.0%
6 710
 
4.0%
7 665
 
3.8%
Other values (2) 1138
 
6.4%

Most occurring blocks

ValueCountFrequency (%)
ASCII 17686
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
* 8611
48.7%
. 1389
 
7.9%
5 1055
 
6.0%
1 1003
 
5.7%
4 852
 
4.8%
2 805
 
4.6%
8 747
 
4.2%
3 711
 
4.0%
6 710
 
4.0%
7 665
 
3.8%
Other values (2) 1138
 
6.4%
Distinct1630
Distinct (%)16.3%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
2024-04-30T02:21:18.097308image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length8
Median length1
Mean length2.0277
Min length1

Characters and Unicode

Total characters20277
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

Unique1444 ?
Unique (%)14.4%

Sample

1st row*
2nd row*
3rd row*
4th row*
5th row289.7355
ValueCountFrequency (%)
8107
81.1%
4.1168 7
 
0.1%
4.0994 6
 
0.1%
4.0798 5
 
< 0.1%
4.1411 5
 
< 0.1%
4.0797 5
 
< 0.1%
4.1445 4
 
< 0.1%
4.1426 4
 
< 0.1%
4.1828 4
 
< 0.1%
4.095 4
 
< 0.1%
Other values (1620) 1849
 
18.5%
2024-04-30T02:21:18.530344image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
* 8107
40.0%
. 1893
 
9.3%
1 1678
 
8.3%
4 1634
 
8.1%
2 1100
 
5.4%
8 990
 
4.9%
0 859
 
4.2%
7 841
 
4.1%
9 814
 
4.0%
3 807
 
4.0%
Other values (2) 1554
 
7.7%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 10277
50.7%
Other Punctuation 10000
49.3%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 1678
16.3%
4 1634
15.9%
2 1100
10.7%
8 990
9.6%
0 859
8.4%
7 841
8.2%
9 814
7.9%
3 807
7.9%
5 799
7.8%
6 755
7.3%
Other Punctuation
ValueCountFrequency (%)
* 8107
81.1%
. 1893
 
18.9%

Most occurring scripts

ValueCountFrequency (%)
Common 20277
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
* 8107
40.0%
. 1893
 
9.3%
1 1678
 
8.3%
4 1634
 
8.1%
2 1100
 
5.4%
8 990
 
4.9%
0 859
 
4.2%
7 841
 
4.1%
9 814
 
4.0%
3 807
 
4.0%
Other values (2) 1554
 
7.7%

Most occurring blocks

ValueCountFrequency (%)
ASCII 20277
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
* 8107
40.0%
. 1893
 
9.3%
1 1678
 
8.3%
4 1634
 
8.1%
2 1100
 
5.4%
8 990
 
4.9%
0 859
 
4.2%
7 841
 
4.1%
9 814
 
4.0%
3 807
 
4.0%
Other values (2) 1554
 
7.7%
Distinct970
Distinct (%)9.7%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
2024-04-30T02:21:18.800324image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length8
Median length1
Mean length1.5648
Min length1

Characters and Unicode

Total characters15648
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

Unique964 ?
Unique (%)9.6%

Sample

1st row*
2nd row*
3rd row*
4th row*
5th row262.3675
ValueCountFrequency (%)
9025
90.2%
7.068 3
 
< 0.1%
7.1132 2
 
< 0.1%
7.0534 2
 
< 0.1%
7.0987 2
 
< 0.1%
7.139 2
 
< 0.1%
121.9453 1
 
< 0.1%
5.9442 1
 
< 0.1%
6.9656 1
 
< 0.1%
5.9846 1
 
< 0.1%
Other values (960) 960
 
9.6%
2024-04-30T02:21:19.186431image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
* 9025
57.7%
. 975
 
6.2%
1 783
 
5.0%
4 604
 
3.9%
2 602
 
3.8%
7 599
 
3.8%
3 558
 
3.6%
6 546
 
3.5%
8 523
 
3.3%
5 520
 
3.3%
Other values (2) 913
 
5.8%

Most occurring categories

ValueCountFrequency (%)
Other Punctuation 10000
63.9%
Decimal Number 5648
36.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 783
13.9%
4 604
10.7%
2 602
10.7%
7 599
10.6%
3 558
9.9%
6 546
9.7%
8 523
9.3%
5 520
9.2%
9 488
8.6%
0 425
7.5%
Other Punctuation
ValueCountFrequency (%)
* 9025
90.2%
. 975
 
9.8%

Most occurring scripts

ValueCountFrequency (%)
Common 15648
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
* 9025
57.7%
. 975
 
6.2%
1 783
 
5.0%
4 604
 
3.9%
2 602
 
3.8%
7 599
 
3.8%
3 558
 
3.6%
6 546
 
3.5%
8 523
 
3.3%
5 520
 
3.3%
Other values (2) 913
 
5.8%

Most occurring blocks

ValueCountFrequency (%)
ASCII 15648
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
* 9025
57.7%
. 975
 
6.2%
1 783
 
5.0%
4 604
 
3.9%
2 602
 
3.8%
7 599
 
3.8%
3 558
 
3.6%
6 546
 
3.5%
8 523
 
3.3%
5 520
 
3.3%
Other values (2) 913
 
5.8%
Distinct1380
Distinct (%)13.8%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
2024-04-30T02:21:19.440441image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length8
Median length1
Mean length1.8297
Min length1

Characters and Unicode

Total characters18297
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

Unique1279 ?
Unique (%)12.8%

Sample

1st row*
2nd row*
3rd row*
4th row*
5th row252.9731
ValueCountFrequency (%)
8494
84.9%
4.2986 6
 
0.1%
4.3137 6
 
0.1%
4.2981 4
 
< 0.1%
4.2985 4
 
< 0.1%
4.3476 4
 
< 0.1%
4.3387 4
 
< 0.1%
4.3241 4
 
< 0.1%
4.2973 3
 
< 0.1%
4.3252 3
 
< 0.1%
Other values (1370) 1468
 
14.7%
2024-04-30T02:21:19.790163image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
* 8494
46.4%
. 1506
 
8.2%
4 1333
 
7.3%
3 1041
 
5.7%
2 976
 
5.3%
1 950
 
5.2%
8 761
 
4.2%
7 719
 
3.9%
5 686
 
3.7%
6 685
 
3.7%
Other values (2) 1146
 
6.3%

Most occurring categories

ValueCountFrequency (%)
Other Punctuation 10000
54.7%
Decimal Number 8297
45.3%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
4 1333
16.1%
3 1041
12.5%
2 976
11.8%
1 950
11.4%
8 761
9.2%
7 719
8.7%
5 686
8.3%
6 685
8.3%
9 637
7.7%
0 509
 
6.1%
Other Punctuation
ValueCountFrequency (%)
* 8494
84.9%
. 1506
 
15.1%

Most occurring scripts

ValueCountFrequency (%)
Common 18297
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
* 8494
46.4%
. 1506
 
8.2%
4 1333
 
7.3%
3 1041
 
5.7%
2 976
 
5.3%
1 950
 
5.2%
8 761
 
4.2%
7 719
 
3.9%
5 686
 
3.7%
6 685
 
3.7%
Other values (2) 1146
 
6.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 18297
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
* 8494
46.4%
. 1506
 
8.2%
4 1333
 
7.3%
3 1041
 
5.7%
2 976
 
5.3%
1 950
 
5.2%
8 761
 
4.2%
7 719
 
3.9%
5 686
 
3.7%
6 685
 
3.7%
Other values (2) 1146
 
6.3%
Distinct898
Distinct (%)9.0%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
2024-04-30T02:21:20.051445image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length8
Median length1
Mean length1.5234
Min length1

Characters and Unicode

Total characters15234
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

Unique891 ?
Unique (%)8.9%

Sample

1st row*
2nd row*
3rd row*
4th row*
5th row170.6058
ValueCountFrequency (%)
9096
91.0%
6.005 3
 
< 0.1%
6.0108 2
 
< 0.1%
5.9404 2
 
< 0.1%
6.0122 2
 
< 0.1%
5.9408 2
 
< 0.1%
6.0568 2
 
< 0.1%
9.0031 1
 
< 0.1%
10.1028 1
 
< 0.1%
6.1895 1
 
< 0.1%
Other values (888) 888
 
8.9%
2024-04-30T02:21:20.429239image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
* 9096
59.7%
. 904
 
5.9%
1 655
 
4.3%
2 576
 
3.8%
4 557
 
3.7%
6 544
 
3.6%
7 504
 
3.3%
5 500
 
3.3%
9 490
 
3.2%
3 484
 
3.2%
Other values (2) 924
 
6.1%

Most occurring categories

ValueCountFrequency (%)
Other Punctuation 10000
65.6%
Decimal Number 5234
34.4%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 655
12.5%
2 576
11.0%
4 557
10.6%
6 544
10.4%
7 504
9.6%
5 500
9.6%
9 490
9.4%
3 484
9.2%
8 482
9.2%
0 442
8.4%
Other Punctuation
ValueCountFrequency (%)
* 9096
91.0%
. 904
 
9.0%

Most occurring scripts

ValueCountFrequency (%)
Common 15234
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
* 9096
59.7%
. 904
 
5.9%
1 655
 
4.3%
2 576
 
3.8%
4 557
 
3.7%
6 544
 
3.6%
7 504
 
3.3%
5 500
 
3.3%
9 490
 
3.2%
3 484
 
3.2%
Other values (2) 924
 
6.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 15234
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
* 9096
59.7%
. 904
 
5.9%
1 655
 
4.3%
2 576
 
3.8%
4 557
 
3.7%
6 544
 
3.6%
7 504
 
3.3%
5 500
 
3.3%
9 490
 
3.2%
3 484
 
3.2%
Other values (2) 924
 
6.1%
Distinct956
Distinct (%)9.6%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
2024-04-30T02:21:20.684024image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length8
Median length1
Mean length1.5497
Min length1

Characters and Unicode

Total characters15497
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

Unique952 ?
Unique (%)9.5%

Sample

1st row*
2nd row*
3rd row*
4th row*
5th row214.0732
ValueCountFrequency (%)
9042
90.4%
6.286 2
 
< 0.1%
6.2802 2
 
< 0.1%
73.3506 2
 
< 0.1%
108.9214 1
 
< 0.1%
4.0383 1
 
< 0.1%
35.0392 1
 
< 0.1%
5.7208 1
 
< 0.1%
6.6351 1
 
< 0.1%
94.4382 1
 
< 0.1%
Other values (946) 946
 
9.5%
2024-04-30T02:21:21.027223image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
* 9042
58.3%
. 958
 
6.2%
1 659
 
4.3%
6 642
 
4.1%
2 611
 
3.9%
4 554
 
3.6%
7 546
 
3.5%
3 536
 
3.5%
5 532
 
3.4%
9 527
 
3.4%
Other values (2) 890
 
5.7%

Most occurring categories

ValueCountFrequency (%)
Other Punctuation 10000
64.5%
Decimal Number 5497
35.5%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 659
12.0%
6 642
11.7%
2 611
11.1%
4 554
10.1%
7 546
9.9%
3 536
9.8%
5 532
9.7%
9 527
9.6%
8 523
9.5%
0 367
6.7%
Other Punctuation
ValueCountFrequency (%)
* 9042
90.4%
. 958
 
9.6%

Most occurring scripts

ValueCountFrequency (%)
Common 15497
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
* 9042
58.3%
. 958
 
6.2%
1 659
 
4.3%
6 642
 
4.1%
2 611
 
3.9%
4 554
 
3.6%
7 546
 
3.5%
3 536
 
3.5%
5 532
 
3.4%
9 527
 
3.4%
Other values (2) 890
 
5.7%

Most occurring blocks

ValueCountFrequency (%)
ASCII 15497
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
* 9042
58.3%
. 958
 
6.2%
1 659
 
4.3%
6 642
 
4.1%
2 611
 
3.9%
4 554
 
3.6%
7 546
 
3.5%
3 536
 
3.5%
5 532
 
3.4%
9 527
 
3.4%
Other values (2) 890
 
5.7%
Distinct938
Distinct (%)9.4%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
2024-04-30T02:21:21.274565image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length8
Median length1
Mean length1.5425
Min length1

Characters and Unicode

Total characters15425
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

Unique930 ?
Unique (%)9.3%

Sample

1st row*
2nd row*
3rd row*
4th row*
5th row149.772
ValueCountFrequency (%)
9055
90.5%
5.474 3
 
< 0.1%
5.369 2
 
< 0.1%
5.3926 2
 
< 0.1%
5.3234 2
 
< 0.1%
5.162 2
 
< 0.1%
5.4002 2
 
< 0.1%
5.4192 2
 
< 0.1%
13.1178 1
 
< 0.1%
199.9106 1
 
< 0.1%
Other values (928) 928
 
9.3%
2024-04-30T02:21:21.680036image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
* 9055
58.7%
. 945
 
6.1%
1 690
 
4.5%
5 639
 
4.1%
4 607
 
3.9%
2 574
 
3.7%
3 551
 
3.6%
6 529
 
3.4%
9 493
 
3.2%
7 484
 
3.1%
Other values (2) 858
 
5.6%

Most occurring categories

ValueCountFrequency (%)
Other Punctuation 10000
64.8%
Decimal Number 5425
35.2%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 690
12.7%
5 639
11.8%
4 607
11.2%
2 574
10.6%
3 551
10.2%
6 529
9.8%
9 493
9.1%
7 484
8.9%
8 464
8.6%
0 394
7.3%
Other Punctuation
ValueCountFrequency (%)
* 9055
90.5%
. 945
 
9.4%

Most occurring scripts

ValueCountFrequency (%)
Common 15425
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
* 9055
58.7%
. 945
 
6.1%
1 690
 
4.5%
5 639
 
4.1%
4 607
 
3.9%
2 574
 
3.7%
3 551
 
3.6%
6 529
 
3.4%
9 493
 
3.2%
7 484
 
3.1%
Other values (2) 858
 
5.6%

Most occurring blocks

ValueCountFrequency (%)
ASCII 15425
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
* 9055
58.7%
. 945
 
6.1%
1 690
 
4.5%
5 639
 
4.1%
4 607
 
3.9%
2 574
 
3.7%
3 551
 
3.6%
6 529
 
3.4%
9 493
 
3.2%
7 484
 
3.1%
Other values (2) 858
 
5.6%
Distinct852
Distinct (%)8.5%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
2024-04-30T02:21:21.929016image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length8
Median length1
Mean length1.4915
Min length1

Characters and Unicode

Total characters14915
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

Unique846 ?
Unique (%)8.5%

Sample

1st row*
2nd row*
3rd row*
4th row*
5th row105.4688
ValueCountFrequency (%)
9144
91.4%
5.126 2
 
< 0.1%
7.2696 2
 
< 0.1%
5.0848 2
 
< 0.1%
5.089 2
 
< 0.1%
4.9218 2
 
< 0.1%
88.8086 1
 
< 0.1%
4.1687 1
 
< 0.1%
10.6783 1
 
< 0.1%
66.4319 1
 
< 0.1%
Other values (842) 842
 
8.4%
2024-04-30T02:21:22.313273image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
* 9144
61.3%
. 856
 
5.7%
1 668
 
4.5%
4 535
 
3.6%
2 535
 
3.6%
5 535
 
3.6%
6 506
 
3.4%
3 462
 
3.1%
8 448
 
3.0%
7 432
 
2.9%
Other values (2) 794
 
5.3%

Most occurring categories

ValueCountFrequency (%)
Other Punctuation 10000
67.0%
Decimal Number 4915
33.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 668
13.6%
4 535
10.9%
2 535
10.9%
5 535
10.9%
6 506
10.3%
3 462
9.4%
8 448
9.1%
7 432
8.8%
9 426
8.7%
0 368
7.5%
Other Punctuation
ValueCountFrequency (%)
* 9144
91.4%
. 856
 
8.6%

Most occurring scripts

ValueCountFrequency (%)
Common 14915
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
* 9144
61.3%
. 856
 
5.7%
1 668
 
4.5%
4 535
 
3.6%
2 535
 
3.6%
5 535
 
3.6%
6 506
 
3.4%
3 462
 
3.1%
8 448
 
3.0%
7 432
 
2.9%
Other values (2) 794
 
5.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 14915
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
* 9144
61.3%
. 856
 
5.7%
1 668
 
4.5%
4 535
 
3.6%
2 535
 
3.6%
5 535
 
3.6%
6 506
 
3.4%
3 462
 
3.1%
8 448
 
3.0%
7 432
 
2.9%
Other values (2) 794
 
5.3%
Distinct746
Distinct (%)7.5%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
2024-04-30T02:21:22.572781image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length8
Median length1
Mean length1.4309
Min length1

Characters and Unicode

Total characters14309
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

Unique743 ?
Unique (%)7.4%

Sample

1st row*
2nd row*
3rd row*
4th row*
5th row78.299
ValueCountFrequency (%)
9253
92.5%
6.7662 2
 
< 0.1%
11.7391 2
 
< 0.1%
11.8584 1
 
< 0.1%
5.1678 1
 
< 0.1%
72.6972 1
 
< 0.1%
71.738 1
 
< 0.1%
6.0759 1
 
< 0.1%
6.9534 1
 
< 0.1%
34.8567 1
 
< 0.1%
Other values (736) 736
 
7.4%
2024-04-30T02:21:23.005912image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
* 9253
64.7%
. 747
 
5.2%
1 613
 
4.3%
2 459
 
3.2%
5 446
 
3.1%
3 433
 
3.0%
7 430
 
3.0%
6 429
 
3.0%
4 422
 
2.9%
8 403
 
2.8%
Other values (2) 674
 
4.7%

Most occurring categories

ValueCountFrequency (%)
Other Punctuation 10000
69.9%
Decimal Number 4309
30.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 613
14.2%
2 459
10.7%
5 446
10.4%
3 433
10.0%
7 430
10.0%
6 429
10.0%
4 422
9.8%
8 403
9.4%
9 380
8.8%
0 294
6.8%
Other Punctuation
ValueCountFrequency (%)
* 9253
92.5%
. 747
 
7.5%

Most occurring scripts

ValueCountFrequency (%)
Common 14309
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
* 9253
64.7%
. 747
 
5.2%
1 613
 
4.3%
2 459
 
3.2%
5 446
 
3.1%
3 433
 
3.0%
7 430
 
3.0%
6 429
 
3.0%
4 422
 
2.9%
8 403
 
2.8%
Other values (2) 674
 
4.7%

Most occurring blocks

ValueCountFrequency (%)
ASCII 14309
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
* 9253
64.7%
. 747
 
5.2%
1 613
 
4.3%
2 459
 
3.2%
5 446
 
3.1%
3 433
 
3.0%
7 430
 
3.0%
6 429
 
3.0%
4 422
 
2.9%
8 403
 
2.8%
Other values (2) 674
 
4.7%
Distinct889
Distinct (%)8.9%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
2024-04-30T02:21:23.284370image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length8
Median length1
Mean length1.5739
Min length1

Characters and Unicode

Total characters15739
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

Unique821 ?
Unique (%)8.2%

Sample

1st row*
2nd row*
3rd row*
4th row*
5th row104.7054
ValueCountFrequency (%)
8957
89.6%
4.3813 8
 
0.1%
4.4719 7
 
0.1%
4.3736 6
 
0.1%
4.4715 6
 
0.1%
4.535 5
 
< 0.1%
4.711 5
 
< 0.1%
4.6122 5
 
< 0.1%
4.6428 5
 
< 0.1%
4.5349 5
 
< 0.1%
Other values (879) 991
 
9.9%
2024-04-30T02:21:23.682816image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
* 8957
56.9%
. 1043
 
6.6%
4 977
 
6.2%
1 707
 
4.5%
6 585
 
3.7%
3 580
 
3.7%
2 570
 
3.6%
5 568
 
3.6%
7 495
 
3.1%
9 468
 
3.0%
Other values (2) 789
 
5.0%

Most occurring categories

ValueCountFrequency (%)
Other Punctuation 10000
63.5%
Decimal Number 5739
36.5%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
4 977
17.0%
1 707
12.3%
6 585
10.2%
3 580
10.1%
2 570
9.9%
5 568
9.9%
7 495
8.6%
9 468
8.2%
8 447
7.8%
0 342
 
6.0%
Other Punctuation
ValueCountFrequency (%)
* 8957
89.6%
. 1043
 
10.4%

Most occurring scripts

ValueCountFrequency (%)
Common 15739
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
* 8957
56.9%
. 1043
 
6.6%
4 977
 
6.2%
1 707
 
4.5%
6 585
 
3.7%
3 580
 
3.7%
2 570
 
3.6%
5 568
 
3.6%
7 495
 
3.1%
9 468
 
3.0%
Other values (2) 789
 
5.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 15739
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
* 8957
56.9%
. 1043
 
6.6%
4 977
 
6.2%
1 707
 
4.5%
6 585
 
3.7%
3 580
 
3.7%
2 570
 
3.6%
5 568
 
3.6%
7 495
 
3.1%
9 468
 
3.0%
Other values (2) 789
 
5.0%
Distinct1366
Distinct (%)13.7%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
2024-04-30T02:21:23.994516image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length9
Median length1
Mean length1.9315
Min length1

Characters and Unicode

Total characters19315
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

Unique1332 ?
Unique (%)13.3%

Sample

1st row*
2nd row*
3rd row*
4th row*
5th row48.3096
ValueCountFrequency (%)
8276
82.8%
4.2868 93
 
0.9%
4.2876 54
 
0.5%
4.2871 52
 
0.5%
4.2875 52
 
0.5%
4.2873 47
 
0.5%
8.5736 15
 
0.1%
8.575 9
 
0.1%
8.5742 8
 
0.1%
8.5752 6
 
0.1%
Other values (1356) 1388
 
13.9%
2024-04-30T02:21:24.390382image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
* 8276
42.8%
. 1724
 
8.9%
4 1291
 
6.7%
8 1144
 
5.9%
2 1125
 
5.8%
1 1019
 
5.3%
6 941
 
4.9%
7 941
 
4.9%
5 876
 
4.5%
3 813
 
4.2%
Other values (2) 1165
 
6.0%

Most occurring categories

ValueCountFrequency (%)
Other Punctuation 10000
51.8%
Decimal Number 9315
48.2%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
4 1291
13.9%
8 1144
12.3%
2 1125
12.1%
1 1019
10.9%
6 941
10.1%
7 941
10.1%
5 876
9.4%
3 813
8.7%
9 662
7.1%
0 503
 
5.4%
Other Punctuation
ValueCountFrequency (%)
* 8276
82.8%
. 1724
 
17.2%

Most occurring scripts

ValueCountFrequency (%)
Common 19315
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
* 8276
42.8%
. 1724
 
8.9%
4 1291
 
6.7%
8 1144
 
5.9%
2 1125
 
5.8%
1 1019
 
5.3%
6 941
 
4.9%
7 941
 
4.9%
5 876
 
4.5%
3 813
 
4.2%
Other values (2) 1165
 
6.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 19315
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
* 8276
42.8%
. 1724
 
8.9%
4 1291
 
6.7%
8 1144
 
5.9%
2 1125
 
5.8%
1 1019
 
5.3%
6 941
 
4.9%
7 941
 
4.9%
5 876
 
4.5%
3 813
 
4.2%
Other values (2) 1165
 
6.0%

Sample

기준일ID시간대구분행정동코드거주지 자치구 코드총생활인구수남자10세부터14세생활인구수남자15세부터19세생활인구수남자20세부터24세생활인구수남자25세부터29세생활인구수남자30세부터34세생활인구수남자35세부터39세생활인구수남자40세부터44세생활인구수남자45세부터49세생활인구수남자50세부터54세생활인구수남자55세부터59세생활인구수남자60세부터64세생활인구수남자65세부터69세생활인구수남자70세부터74세생활인구수남자75세부터79세생활인구수여자10세부터14세생활인구수여자15세부터19세생활인구수여자20세부터24세생활인구수여자25세부터29세생활인구수여자30세부터34세생활인구수여자35세부터39세생활인구수여자40세부터44세생활인구수여자45세부터49세생활인구수여자50세부터54세생활인구수여자55세부터59세생활인구수여자60세부터64세생활인구수여자65세부터69세생활인구수여자70세부터74세생활인구수여자75세부터79세생활인구수장기체류외국인수
633420240422011530595113057*****************************
4901920240422411680656112606*****************************
3937320240422311710580113803*****************************
21826202404222112157801138013*****************************
4968020240422411710646117104476164.8845176.8595107.8923135.857154.9311219.5529211.4613267.8216156.591147.6072105.187581.52364.406157.4198121.8298196.2143108.5225150.0008171.2244289.7355262.3675252.9731170.6058214.0732149.772105.468878.299104.705448.3096
8850202404220116806601126013***5.514*************************
637720240422011530730112150*****************************
43622202404224113056601114035*******************4.1259*6.76776.0108******
45973202404224115005351144064**7.0572**4.9928**********4.32828.3393*6.9825*4.04747.8032******
827220240422011650580115456*****************************
기준일ID시간대구분행정동코드거주지 자치구 코드총생활인구수남자10세부터14세생활인구수남자15세부터19세생활인구수남자20세부터24세생활인구수남자25세부터29세생활인구수남자30세부터34세생활인구수남자35세부터39세생활인구수남자40세부터44세생활인구수남자45세부터49세생활인구수남자50세부터54세생활인구수남자55세부터59세생활인구수남자60세부터64세생활인구수남자65세부터69세생활인구수남자70세부터74세생활인구수남자75세부터79세생활인구수여자10세부터14세생활인구수여자15세부터19세생활인구수여자20세부터24세생활인구수여자25세부터29세생활인구수여자30세부터34세생활인구수여자35세부터39세생활인구수여자40세부터44세생활인구수여자45세부터49세생활인구수여자50세부터54세생활인구수여자55세부터59세생활인구수여자60세부터64세생활인구수여자65세부터69세생활인구수여자70세부터74세생활인구수여자75세부터79세생활인구수장기체류외국인수
2957020240422211710647116207*****************************
53799202404225113205121117010*****************************
4186420240422411215760114400*****************************
34827202404223114106151165033**11.7586*************7.8124***7.0168********
365320240422011320670114100*****************************
23799202404222113206901121516*****************************
3129320240422311200520115455*****************************
5424720240422511350612111705*****************************
48324202404224116505311138011*******************4.0798*********
4722820240422411560660112002*****************************