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,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/F/1/datasetView.do

Alerts

기준일ID has constant value ""Constant
시간대구분 has 1819 (18.2%) zerosZeros
총생활인구수 has 310 (3.1%) zerosZeros

Reproduction

Analysis started2023-12-11 06:10:33.569971
Analysis finished2023-12-11 06:10:35.007727
Duration1.44 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
20221015
10000 

Length

Max length8
Median length8
Mean length8
Min length8

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row20221015
2nd row20221015
3rd row20221015
4th row20221015
5th row20221015

Common Values

ValueCountFrequency (%)
20221015 10000
100.0%

Length

2023-12-11T15:10:35.077014image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T15:10:35.189378image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
20221015 10000
100.0%

시간대구분
Real number (ℝ)

ZEROS 

Distinct6
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2.267
Minimum0
Maximum5
Zeros1819
Zeros (%)18.2%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2023-12-11T15:10:35.279135image/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 deviation1.5953575
Coefficient of variation (CV)0.7037307
Kurtosis-1.1610064
Mean2.267
Median Absolute Deviation (MAD)1
Skewness0.081269615
Sum22670
Variance2.5451655
MonotonicityNot monotonic
2023-12-11T15:10:35.404000image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=6)
ValueCountFrequency (%)
3 1872
18.7%
1 1825
18.2%
0 1819
18.2%
2 1798
18.0%
4 1797
18.0%
5 889
8.9%
ValueCountFrequency (%)
0 1819
18.2%
1 1825
18.2%
2 1798
18.0%
3 1872
18.7%
4 1797
18.0%
5 889
8.9%
ValueCountFrequency (%)
5 889
8.9%
4 1797
18.0%
3 1872
18.7%
2 1798
18.0%
1 1825
18.2%
0 1819
18.2%

행정동코드
Real number (ℝ)

Distinct424
Distinct (%)4.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean11418154
Minimum11110515
Maximum11740700
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2023-12-11T15:10:35.582305image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum11110515
5-th percentile11140550
Q111260540
median11410585
Q311590560
95-th percentile11710646
Maximum11740700
Range630185
Interquartile range (IQR)330020

Descriptive statistics

Standard deviation191573.4
Coefficient of variation (CV)0.016777967
Kurtosis-1.2691779
Mean11418154
Median Absolute Deviation (MAD)179865
Skewness0.096207728
Sum1.1418154 × 1011
Variance3.6700368 × 1010
MonotonicityNot monotonic
2023-12-11T15:10:35.776472image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
11200650 37
 
0.4%
11260570 36
 
0.4%
11530760 36
 
0.4%
11305575 36
 
0.4%
11140635 36
 
0.4%
11380510 36
 
0.4%
11410690 35
 
0.4%
11230720 35
 
0.4%
11200580 35
 
0.4%
11380590 34
 
0.3%
Other values (414) 9644
96.4%
ValueCountFrequency (%)
11110515 21
0.2%
11110530 30
0.3%
11110540 22
0.2%
11110550 29
0.3%
11110560 25
0.2%
11110570 29
0.3%
11110580 25
0.2%
11110600 25
0.2%
11110615 30
0.3%
11110630 29
0.3%
ValueCountFrequency (%)
11740700 15
0.1%
11740690 23
0.2%
11740685 18
0.2%
11740660 26
0.3%
11740650 13
0.1%
11740640 24
0.2%
11740620 17
0.2%
11740610 24
0.2%
11740600 24
0.2%
11740590 17
0.2%
Distinct25
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean11415.361
Minimum11110
Maximum11740
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2023-12-11T15:10:35.959057image/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 deviation185.9682
Coefficient of variation (CV)0.016291049
Kurtosis-1.2085986
Mean11415.361
Median Absolute Deviation (MAD)150
Skewness0.080036501
Sum1.1415361 × 108
Variance34584.173
MonotonicityNot monotonic
2023-12-11T15:10:36.412231image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=25)
ValueCountFrequency (%)
11620 443
 
4.4%
11410 434
 
4.3%
11500 430
 
4.3%
11230 427
 
4.3%
11290 422
 
4.2%
11440 421
 
4.2%
11650 418
 
4.2%
11305 415
 
4.2%
11590 412
 
4.1%
11170 409
 
4.1%
Other values (15) 5769
57.7%
ValueCountFrequency (%)
11110 394
3.9%
11140 407
4.1%
11170 409
4.1%
11200 397
4.0%
11215 398
4.0%
11230 427
4.3%
11260 396
4.0%
11290 422
4.2%
11305 415
4.2%
11320 346
3.5%
ValueCountFrequency (%)
11740 373
3.7%
11710 380
3.8%
11680 396
4.0%
11650 418
4.2%
11620 443
4.4%
11590 412
4.1%
11560 384
3.8%
11545 369
3.7%
11530 393
3.9%
11500 430
4.3%

총생활인구수
Real number (ℝ)

ZEROS 

Distinct862
Distinct (%)8.6%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean166.5252
Minimum0
Maximum33969
Zeros310
Zeros (%)3.1%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2023-12-11T15:10:36.553916image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile2
Q17
median16
Q339
95-th percentile670.2
Maximum33969
Range33969
Interquartile range (IQR)32

Descriptive statistics

Standard deviation859.89235
Coefficient of variation (CV)5.1637371
Kurtosis544.13726
Mean166.5252
Median Absolute Deviation (MAD)11
Skewness17.808378
Sum1665252
Variance739414.85
MonotonicityNot monotonic
2023-12-11T15:10:36.718084image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
3 422
 
4.2%
5 388
 
3.9%
6 378
 
3.8%
2 361
 
3.6%
8 330
 
3.3%
7 329
 
3.3%
9 322
 
3.2%
0 310
 
3.1%
4 289
 
2.9%
10 283
 
2.8%
Other values (852) 6588
65.9%
ValueCountFrequency (%)
0 310
3.1%
1 159
 
1.6%
2 361
3.6%
3 422
4.2%
4 289
2.9%
5 388
3.9%
6 378
3.8%
7 329
3.3%
8 330
3.3%
9 322
3.2%
ValueCountFrequency (%)
33969 1
< 0.1%
33718 1
< 0.1%
19043 1
< 0.1%
15230 1
< 0.1%
14989 1
< 0.1%
12750 1
< 0.1%
12226 1
< 0.1%
12070 1
< 0.1%
11984 1
< 0.1%
11905 1
< 0.1%
Distinct800
Distinct (%)8.0%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
2023-12-11T15:10:37.065635image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length9
Median length1
Mean length1.4549
Min length1

Characters and Unicode

Total characters14549
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

Unique786 ?
Unique (%)7.9%

Sample

1st row*
2nd row*
3rd row*
4th row*
5th row*
ValueCountFrequency (%)
9187
91.9%
5.6249 3
 
< 0.1%
8.7747 2
 
< 0.1%
5.4245 2
 
< 0.1%
5.5703 2
 
< 0.1%
4.4956 2
 
< 0.1%
5.3842 2
 
< 0.1%
5.4422 2
 
< 0.1%
5.3931 2
 
< 0.1%
5.4459 2
 
< 0.1%
Other values (790) 794
 
7.9%
2023-12-11T15:10:37.533078image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
* 9187
63.1%
. 813
 
5.6%
5 597
 
4.1%
1 559
 
3.8%
4 512
 
3.5%
2 502
 
3.5%
3 447
 
3.1%
6 434
 
3.0%
8 423
 
2.9%
9 378
 
2.6%
Other values (2) 697
 
4.8%

Most occurring categories

ValueCountFrequency (%)
Other Punctuation 10000
68.7%
Decimal Number 4549
31.3%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
5 597
13.1%
1 559
12.3%
4 512
11.3%
2 502
11.0%
3 447
9.8%
6 434
9.5%
8 423
9.3%
9 378
8.3%
7 377
8.3%
0 320
7.0%
Other Punctuation
ValueCountFrequency (%)
* 9187
91.9%
. 813
 
8.1%

Most occurring scripts

ValueCountFrequency (%)
Common 14549
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
* 9187
63.1%
. 813
 
5.6%
5 597
 
4.1%
1 559
 
3.8%
4 512
 
3.5%
2 502
 
3.5%
3 447
 
3.1%
6 434
 
3.0%
8 423
 
2.9%
9 378
 
2.6%
Other values (2) 697
 
4.8%

Most occurring blocks

ValueCountFrequency (%)
ASCII 14549
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
* 9187
63.1%
. 813
 
5.6%
5 597
 
4.1%
1 559
 
3.8%
4 512
 
3.5%
2 502
 
3.5%
3 447
 
3.1%
6 434
 
3.0%
8 423
 
2.9%
9 378
 
2.6%
Other values (2) 697
 
4.8%
Distinct1181
Distinct (%)11.8%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
2023-12-11T15:10:37.885594image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length9
Median length1
Mean length1.7222
Min length1

Characters and Unicode

Total characters17222
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

Unique1098 ?
Unique (%)11.0%

Sample

1st row*
2nd row*
3rd row*
4th row5.3563
5th row*
ValueCountFrequency (%)
8682
86.8%
5.4094 6
 
0.1%
5.4097 6
 
0.1%
5.3712 5
 
< 0.1%
5.3706 5
 
< 0.1%
5.3493 5
 
< 0.1%
5.4088 4
 
< 0.1%
5.3502 4
 
< 0.1%
5.3592 4
 
< 0.1%
5.7953 4
 
< 0.1%
Other values (1171) 1275
 
12.8%
2023-12-11T15:10:38.362041image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
* 8682
50.4%
. 1318
 
7.7%
5 1064
 
6.2%
1 920
 
5.3%
3 788
 
4.6%
2 740
 
4.3%
4 729
 
4.2%
6 697
 
4.0%
7 608
 
3.5%
9 582
 
3.4%
Other values (2) 1094
 
6.4%

Most occurring categories

ValueCountFrequency (%)
Other Punctuation 10000
58.1%
Decimal Number 7222
41.9%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
5 1064
14.7%
1 920
12.7%
3 788
10.9%
2 740
10.2%
4 729
10.1%
6 697
9.7%
7 608
8.4%
9 582
8.1%
8 579
8.0%
0 515
7.1%
Other Punctuation
ValueCountFrequency (%)
* 8682
86.8%
. 1318
 
13.2%

Most occurring scripts

ValueCountFrequency (%)
Common 17222
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
* 8682
50.4%
. 1318
 
7.7%
5 1064
 
6.2%
1 920
 
5.3%
3 788
 
4.6%
2 740
 
4.3%
4 729
 
4.2%
6 697
 
4.0%
7 608
 
3.5%
9 582
 
3.4%
Other values (2) 1094
 
6.4%

Most occurring blocks

ValueCountFrequency (%)
ASCII 17222
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
* 8682
50.4%
. 1318
 
7.7%
5 1064
 
6.2%
1 920
 
5.3%
3 788
 
4.6%
2 740
 
4.3%
4 729
 
4.2%
6 697
 
4.0%
7 608
 
3.5%
9 582
 
3.4%
Other values (2) 1094
 
6.4%
Distinct1379
Distinct (%)13.8%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
2023-12-11T15:10:38.689098image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length8
Median length1
Mean length1.7752
Min length1

Characters and Unicode

Total characters17752
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

Unique1361 ?
Unique (%)13.6%

Sample

1st row*
2nd row*
3rd row*
4th row*
5th row*
ValueCountFrequency (%)
8604
86.0%
7.2334 3
 
< 0.1%
6.7142 2
 
< 0.1%
7.327 2
 
< 0.1%
7.297 2
 
< 0.1%
7.3568 2
 
< 0.1%
7.2718 2
 
< 0.1%
7.2546 2
 
< 0.1%
10.9389 2
 
< 0.1%
7.224 2
 
< 0.1%
Other values (1369) 1377
 
13.8%
2023-12-11T15:10:39.147419image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
* 8604
48.5%
. 1396
 
7.9%
1 1035
 
5.8%
7 860
 
4.8%
4 835
 
4.7%
2 804
 
4.5%
6 768
 
4.3%
3 764
 
4.3%
8 743
 
4.2%
5 717
 
4.0%
Other values (2) 1226
 
6.9%

Most occurring categories

ValueCountFrequency (%)
Other Punctuation 10000
56.3%
Decimal Number 7752
43.7%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 1035
13.4%
7 860
11.1%
4 835
10.8%
2 804
10.4%
6 768
9.9%
3 764
9.9%
8 743
9.6%
5 717
9.2%
9 691
8.9%
0 535
6.9%
Other Punctuation
ValueCountFrequency (%)
* 8604
86.0%
. 1396
 
14.0%

Most occurring scripts

ValueCountFrequency (%)
Common 17752
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
* 8604
48.5%
. 1396
 
7.9%
1 1035
 
5.8%
7 860
 
4.8%
4 835
 
4.7%
2 804
 
4.5%
6 768
 
4.3%
3 764
 
4.3%
8 743
 
4.2%
5 717
 
4.0%
Other values (2) 1226
 
6.9%

Most occurring blocks

ValueCountFrequency (%)
ASCII 17752
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
* 8604
48.5%
. 1396
 
7.9%
1 1035
 
5.8%
7 860
 
4.8%
4 835
 
4.7%
2 804
 
4.5%
6 768
 
4.3%
3 764
 
4.3%
8 743
 
4.2%
5 717
 
4.0%
Other values (2) 1226
 
6.9%
Distinct2146
Distinct (%)21.5%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
2023-12-11T15:10:39.460962image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length8
Median length1
Mean length2.1999
Min length1

Characters and Unicode

Total characters21999
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

Unique2089 ?
Unique (%)20.9%

Sample

1st row*
2nd row*
3rd row5.1844
4th row7.7639
5th row*
ValueCountFrequency (%)
7791
77.9%
5.076 3
 
< 0.1%
5.133 3
 
< 0.1%
5.0906 3
 
< 0.1%
5.0988 3
 
< 0.1%
5.0962 3
 
< 0.1%
5.118 3
 
< 0.1%
5.1076 3
 
< 0.1%
5.1056 3
 
< 0.1%
7.0941 2
 
< 0.1%
Other values (2136) 2183
 
21.8%
2023-12-11T15:10:39.929662image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
* 7791
35.4%
. 2209
 
10.0%
1 1619
 
7.4%
5 1452
 
6.6%
4 1251
 
5.7%
2 1225
 
5.6%
7 1186
 
5.4%
6 1139
 
5.2%
8 1082
 
4.9%
3 1049
 
4.8%
Other values (2) 1996
 
9.1%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 11999
54.5%
Other Punctuation 10000
45.5%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 1619
13.5%
5 1452
12.1%
4 1251
10.4%
2 1225
10.2%
7 1186
9.9%
6 1139
9.5%
8 1082
9.0%
3 1049
8.7%
9 1012
8.4%
0 984
8.2%
Other Punctuation
ValueCountFrequency (%)
* 7791
77.9%
. 2209
 
22.1%

Most occurring scripts

ValueCountFrequency (%)
Common 21999
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
* 7791
35.4%
. 2209
 
10.0%
1 1619
 
7.4%
5 1452
 
6.6%
4 1251
 
5.7%
2 1225
 
5.6%
7 1186
 
5.4%
6 1139
 
5.2%
8 1082
 
4.9%
3 1049
 
4.8%
Other values (2) 1996
 
9.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 21999
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
* 7791
35.4%
. 2209
 
10.0%
1 1619
 
7.4%
5 1452
 
6.6%
4 1251
 
5.7%
2 1225
 
5.6%
7 1186
 
5.4%
6 1139
 
5.2%
8 1082
 
4.9%
3 1049
 
4.8%
Other values (2) 1996
 
9.1%
Distinct1981
Distinct (%)19.8%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
2023-12-11T15:10:40.258144image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length8
Median length1
Mean length2.1029
Min length1

Characters and Unicode

Total characters21029
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

Unique1935 ?
Unique (%)19.4%

Sample

1st row*
2nd row*
3rd row6.9097
4th row*
5th row*
ValueCountFrequency (%)
7967
79.7%
5.2344 4
 
< 0.1%
5.1864 4
 
< 0.1%
5.2248 3
 
< 0.1%
5.2262 3
 
< 0.1%
7.7955 3
 
< 0.1%
5.2042 3
 
< 0.1%
4.248 2
 
< 0.1%
5.212 2
 
< 0.1%
5.0747 2
 
< 0.1%
Other values (1971) 2007
 
20.1%
2023-12-11T15:10:40.718938image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
* 7967
37.9%
. 2033
 
9.7%
1 1489
 
7.1%
5 1324
 
6.3%
4 1221
 
5.8%
2 1164
 
5.5%
7 1115
 
5.3%
8 1037
 
4.9%
6 1021
 
4.9%
3 971
 
4.6%
Other values (2) 1687
 
8.0%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 11029
52.4%
Other Punctuation 10000
47.6%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 1489
13.5%
5 1324
12.0%
4 1221
11.1%
2 1164
10.6%
7 1115
10.1%
8 1037
9.4%
6 1021
9.3%
3 971
8.8%
9 925
8.4%
0 762
6.9%
Other Punctuation
ValueCountFrequency (%)
* 7967
79.7%
. 2033
 
20.3%

Most occurring scripts

ValueCountFrequency (%)
Common 21029
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
* 7967
37.9%
. 2033
 
9.7%
1 1489
 
7.1%
5 1324
 
6.3%
4 1221
 
5.8%
2 1164
 
5.5%
7 1115
 
5.3%
8 1037
 
4.9%
6 1021
 
4.9%
3 971
 
4.6%
Other values (2) 1687
 
8.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 21029
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
* 7967
37.9%
. 2033
 
9.7%
1 1489
 
7.1%
5 1324
 
6.3%
4 1221
 
5.8%
2 1164
 
5.5%
7 1115
 
5.3%
8 1037
 
4.9%
6 1021
 
4.9%
3 971
 
4.6%
Other values (2) 1687
 
8.0%
Distinct1744
Distinct (%)17.4%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
2023-12-11T15:10:41.008768image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length9
Median length1
Mean length1.9923
Min length1

Characters and Unicode

Total characters19923
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

Unique1709 ?
Unique (%)17.1%

Sample

1st row*
2nd row*
3rd row4.2331
4th row8.2033
5th row*
ValueCountFrequency (%)
8218
82.2%
7.0502 4
 
< 0.1%
7.054 3
 
< 0.1%
7.0586 3
 
< 0.1%
7.0968 3
 
< 0.1%
7.063 2
 
< 0.1%
7.1778 2
 
< 0.1%
5.0216 2
 
< 0.1%
7.0464 2
 
< 0.1%
6.9371 2
 
< 0.1%
Other values (1734) 1759
 
17.6%
2023-12-11T15:10:41.509899image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
* 8218
41.2%
. 1782
 
8.9%
1 1357
 
6.8%
7 1084
 
5.4%
6 1038
 
5.2%
4 1015
 
5.1%
2 959
 
4.8%
5 946
 
4.7%
0 932
 
4.7%
8 907
 
4.6%
Other values (2) 1685
 
8.5%

Most occurring categories

ValueCountFrequency (%)
Other Punctuation 10000
50.2%
Decimal Number 9923
49.8%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 1357
13.7%
7 1084
10.9%
6 1038
10.5%
4 1015
10.2%
2 959
9.7%
5 946
9.5%
0 932
9.4%
8 907
9.1%
3 893
9.0%
9 792
8.0%
Other Punctuation
ValueCountFrequency (%)
* 8218
82.2%
. 1782
 
17.8%

Most occurring scripts

ValueCountFrequency (%)
Common 19923
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
* 8218
41.2%
. 1782
 
8.9%
1 1357
 
6.8%
7 1084
 
5.4%
6 1038
 
5.2%
4 1015
 
5.1%
2 959
 
4.8%
5 946
 
4.7%
0 932
 
4.7%
8 907
 
4.6%
Other values (2) 1685
 
8.5%

Most occurring blocks

ValueCountFrequency (%)
ASCII 19923
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
* 8218
41.2%
. 1782
 
8.9%
1 1357
 
6.8%
7 1084
 
5.4%
6 1038
 
5.2%
4 1015
 
5.1%
2 959
 
4.8%
5 946
 
4.7%
0 932
 
4.7%
8 907
 
4.6%
Other values (2) 1685
 
8.5%
Distinct1474
Distinct (%)14.7%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
2023-12-11T15:10:41.834067image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length9
Median length1
Mean length1.8296
Min length1

Characters and Unicode

Total characters18296
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

Unique1448 ?
Unique (%)14.5%

Sample

1st row*
2nd row*
3rd row*
4th row*
5th row*
ValueCountFrequency (%)
8501
85.0%
6.326 3
 
< 0.1%
6.4082 2
 
< 0.1%
6.3592 2
 
< 0.1%
6.362 2
 
< 0.1%
6.3936 2
 
< 0.1%
6.3574 2
 
< 0.1%
4.7639 2
 
< 0.1%
6.6502 2
 
< 0.1%
6.359 2
 
< 0.1%
Other values (1464) 1480
 
14.8%
2023-12-11T15:10:42.271734image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
* 8501
46.5%
. 1499
 
8.2%
1 1054
 
5.8%
6 1010
 
5.5%
4 894
 
4.9%
3 884
 
4.8%
2 877
 
4.8%
5 853
 
4.7%
9 778
 
4.3%
8 731
 
4.0%
Other values (2) 1215
 
6.6%

Most occurring categories

ValueCountFrequency (%)
Other Punctuation 10000
54.7%
Decimal Number 8296
45.3%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 1054
12.7%
6 1010
12.2%
4 894
10.8%
3 884
10.7%
2 877
10.6%
5 853
10.3%
9 778
9.4%
8 731
8.8%
7 692
8.3%
0 523
6.3%
Other Punctuation
ValueCountFrequency (%)
* 8501
85.0%
. 1499
 
15.0%

Most occurring scripts

ValueCountFrequency (%)
Common 18296
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
* 8501
46.5%
. 1499
 
8.2%
1 1054
 
5.8%
6 1010
 
5.5%
4 894
 
4.9%
3 884
 
4.8%
2 877
 
4.8%
5 853
 
4.7%
9 778
 
4.3%
8 731
 
4.0%
Other values (2) 1215
 
6.6%

Most occurring blocks

ValueCountFrequency (%)
ASCII 18296
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
* 8501
46.5%
. 1499
 
8.2%
1 1054
 
5.8%
6 1010
 
5.5%
4 894
 
4.9%
3 884
 
4.8%
2 877
 
4.8%
5 853
 
4.7%
9 778
 
4.3%
8 731
 
4.0%
Other values (2) 1215
 
6.6%
Distinct1399
Distinct (%)14.0%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
2023-12-11T15:10:42.496398image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length9
Median length1
Mean length1.7934
Min length1

Characters and Unicode

Total characters17934
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

Unique1385 ?
Unique (%)13.9%

Sample

1st row*
2nd row*
3rd row*
4th row*
5th row*
ValueCountFrequency (%)
8583
85.8%
7.6584 4
 
< 0.1%
7.6556 3
 
< 0.1%
7.6597 3
 
< 0.1%
7.66 3
 
< 0.1%
7.6662 3
 
< 0.1%
7.7152 2
 
< 0.1%
4.0363 2
 
< 0.1%
7.6881 2
 
< 0.1%
7.5954 2
 
< 0.1%
Other values (1389) 1393
 
13.9%
2023-12-11T15:10:42.843280image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
* 8583
47.9%
. 1417
 
7.9%
1 1072
 
6.0%
7 915
 
5.1%
4 850
 
4.7%
6 845
 
4.7%
5 810
 
4.5%
2 762
 
4.2%
8 749
 
4.2%
3 701
 
3.9%
Other values (2) 1230
 
6.9%

Most occurring categories

ValueCountFrequency (%)
Other Punctuation 10000
55.8%
Decimal Number 7934
44.2%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 1072
13.5%
7 915
11.5%
4 850
10.7%
6 845
10.7%
5 810
10.2%
2 762
9.6%
8 749
9.4%
3 701
8.8%
9 699
8.8%
0 531
6.7%
Other Punctuation
ValueCountFrequency (%)
* 8583
85.8%
. 1417
 
14.2%

Most occurring scripts

ValueCountFrequency (%)
Common 17934
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
* 8583
47.9%
. 1417
 
7.9%
1 1072
 
6.0%
7 915
 
5.1%
4 850
 
4.7%
6 845
 
4.7%
5 810
 
4.5%
2 762
 
4.2%
8 749
 
4.2%
3 701
 
3.9%
Other values (2) 1230
 
6.9%

Most occurring blocks

ValueCountFrequency (%)
ASCII 17934
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
* 8583
47.9%
. 1417
 
7.9%
1 1072
 
6.0%
7 915
 
5.1%
4 850
 
4.7%
6 845
 
4.7%
5 810
 
4.5%
2 762
 
4.2%
8 749
 
4.2%
3 701
 
3.9%
Other values (2) 1230
 
6.9%
Distinct1329
Distinct (%)13.3%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
2023-12-11T15:10:43.084307image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length9
Median length1
Mean length1.7496
Min length1

Characters and Unicode

Total characters17496
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

Unique1304 ?
Unique (%)13.0%

Sample

1st row*
2nd row*
3rd row*
4th row*
5th row*
ValueCountFrequency (%)
8647
86.5%
6.0414 3
 
< 0.1%
9.0369 2
 
< 0.1%
6.1488 2
 
< 0.1%
4.9298 2
 
< 0.1%
13.8239 2
 
< 0.1%
6.0322 2
 
< 0.1%
9.1086 2
 
< 0.1%
9.2916 2
 
< 0.1%
6.1316 2
 
< 0.1%
Other values (1319) 1334
 
13.3%
2023-12-11T15:10:43.478762image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
* 8647
49.4%
. 1353
 
7.7%
1 988
 
5.6%
4 826
 
4.7%
6 816
 
4.7%
5 800
 
4.6%
2 759
 
4.3%
8 750
 
4.3%
9 736
 
4.2%
3 650
 
3.7%
Other values (2) 1171
 
6.7%

Most occurring categories

ValueCountFrequency (%)
Other Punctuation 10000
57.2%
Decimal Number 7496
42.8%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 988
13.2%
4 826
11.0%
6 816
10.9%
5 800
10.7%
2 759
10.1%
8 750
10.0%
9 736
9.8%
3 650
8.7%
7 626
8.4%
0 545
7.3%
Other Punctuation
ValueCountFrequency (%)
* 8647
86.5%
. 1353
 
13.5%

Most occurring scripts

ValueCountFrequency (%)
Common 17496
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
* 8647
49.4%
. 1353
 
7.7%
1 988
 
5.6%
4 826
 
4.7%
6 816
 
4.7%
5 800
 
4.6%
2 759
 
4.3%
8 750
 
4.3%
9 736
 
4.2%
3 650
 
3.7%
Other values (2) 1171
 
6.7%

Most occurring blocks

ValueCountFrequency (%)
ASCII 17496
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
* 8647
49.4%
. 1353
 
7.7%
1 988
 
5.6%
4 826
 
4.7%
6 816
 
4.7%
5 800
 
4.6%
2 759
 
4.3%
8 750
 
4.3%
9 736
 
4.2%
3 650
 
3.7%
Other values (2) 1171
 
6.7%
Distinct1226
Distinct (%)12.3%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
2023-12-11T15:10:43.773889image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length9
Median length1
Mean length1.6873
Min length1

Characters and Unicode

Total characters16873
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

Unique1220 ?
Unique (%)12.2%

Sample

1st row*
2nd row*
3rd row*
4th row*
5th row*
ValueCountFrequency (%)
8770
87.7%
6.1561 2
 
< 0.1%
6.7082 2
 
< 0.1%
5.0703 2
 
< 0.1%
6.8044 2
 
< 0.1%
6.76 2
 
< 0.1%
38.3119 1
 
< 0.1%
10.8135 1
 
< 0.1%
15.0879 1
 
< 0.1%
54.7534 1
 
< 0.1%
Other values (1216) 1216
 
12.2%
2023-12-11T15:10:44.212215image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
* 8770
52.0%
. 1230
 
7.3%
1 900
 
5.3%
6 834
 
4.9%
4 749
 
4.4%
7 689
 
4.1%
5 680
 
4.0%
3 660
 
3.9%
8 659
 
3.9%
2 658
 
3.9%
Other values (2) 1044
 
6.2%

Most occurring categories

ValueCountFrequency (%)
Other Punctuation 10000
59.3%
Decimal Number 6873
40.7%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 900
13.1%
6 834
12.1%
4 749
10.9%
7 689
10.0%
5 680
9.9%
3 660
9.6%
8 659
9.6%
2 658
9.6%
9 601
8.7%
0 443
6.4%
Other Punctuation
ValueCountFrequency (%)
* 8770
87.7%
. 1230
 
12.3%

Most occurring scripts

ValueCountFrequency (%)
Common 16873
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
* 8770
52.0%
. 1230
 
7.3%
1 900
 
5.3%
6 834
 
4.9%
4 749
 
4.4%
7 689
 
4.1%
5 680
 
4.0%
3 660
 
3.9%
8 659
 
3.9%
2 658
 
3.9%
Other values (2) 1044
 
6.2%

Most occurring blocks

ValueCountFrequency (%)
ASCII 16873
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
* 8770
52.0%
. 1230
 
7.3%
1 900
 
5.3%
6 834
 
4.9%
4 749
 
4.4%
7 689
 
4.1%
5 680
 
4.0%
3 660
 
3.9%
8 659
 
3.9%
2 658
 
3.9%
Other values (2) 1044
 
6.2%
Distinct1162
Distinct (%)11.6%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
2023-12-11T15:10:44.516009image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length9
Median length1
Mean length1.652
Min length1

Characters and Unicode

Total characters16520
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

Unique1144 ?
Unique (%)11.4%

Sample

1st row*
2nd row*
3rd row*
4th row*
5th row*
ValueCountFrequency (%)
8817
88.2%
5.2854 4
 
< 0.1%
5.1936 3
 
< 0.1%
5.2566 3
 
< 0.1%
5.2298 3
 
< 0.1%
8.0868 2
 
< 0.1%
5.2766 2
 
< 0.1%
5.218 2
 
< 0.1%
6.4169 2
 
< 0.1%
5.2228 2
 
< 0.1%
Other values (1152) 1160
 
11.6%
2023-12-11T15:10:44.954428image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
* 8817
53.4%
. 1183
 
7.2%
1 850
 
5.1%
5 827
 
5.0%
4 728
 
4.4%
2 706
 
4.3%
6 622
 
3.8%
3 606
 
3.7%
7 604
 
3.7%
8 584
 
3.5%
Other values (2) 993
 
6.0%

Most occurring categories

ValueCountFrequency (%)
Other Punctuation 10000
60.5%
Decimal Number 6520
39.5%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 850
13.0%
5 827
12.7%
4 728
11.2%
2 706
10.8%
6 622
9.5%
3 606
9.3%
7 604
9.3%
8 584
9.0%
9 578
8.9%
0 415
6.4%
Other Punctuation
ValueCountFrequency (%)
* 8817
88.2%
. 1183
 
11.8%

Most occurring scripts

ValueCountFrequency (%)
Common 16520
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
* 8817
53.4%
. 1183
 
7.2%
1 850
 
5.1%
5 827
 
5.0%
4 728
 
4.4%
2 706
 
4.3%
6 622
 
3.8%
3 606
 
3.7%
7 604
 
3.7%
8 584
 
3.5%
Other values (2) 993
 
6.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 16520
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
* 8817
53.4%
. 1183
 
7.2%
1 850
 
5.1%
5 827
 
5.0%
4 728
 
4.4%
2 706
 
4.3%
6 622
 
3.8%
3 606
 
3.7%
7 604
 
3.7%
8 584
 
3.5%
Other values (2) 993
 
6.0%
Distinct1010
Distinct (%)10.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
2023-12-11T15:10:45.282507image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length8
Median length1
Mean length1.561
Min length1

Characters and Unicode

Total characters15610
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

Unique1000 ?
Unique (%)10.0%

Sample

1st row*
2nd row*
3rd row*
4th row*
5th row*
ValueCountFrequency (%)
8982
89.8%
5.163 2
 
< 0.1%
18.0516 2
 
< 0.1%
5.0834 2
 
< 0.1%
4.5833 2
 
< 0.1%
5.1126 2
 
< 0.1%
5.1808 2
 
< 0.1%
5.0852 2
 
< 0.1%
5.1714 2
 
< 0.1%
5.1576 2
 
< 0.1%
Other values (1000) 1000
 
10.0%
2023-12-11T15:10:45.777811image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
* 8982
57.5%
. 1018
 
6.5%
1 709
 
4.5%
5 653
 
4.2%
4 644
 
4.1%
3 579
 
3.7%
6 571
 
3.7%
7 560
 
3.6%
2 530
 
3.4%
8 471
 
3.0%
Other values (2) 893
 
5.7%

Most occurring categories

ValueCountFrequency (%)
Other Punctuation 10000
64.1%
Decimal Number 5610
35.9%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 709
12.6%
5 653
11.6%
4 644
11.5%
3 579
10.3%
6 571
10.2%
7 560
10.0%
2 530
9.4%
8 471
8.4%
9 455
8.1%
0 438
7.8%
Other Punctuation
ValueCountFrequency (%)
* 8982
89.8%
. 1018
 
10.2%

Most occurring scripts

ValueCountFrequency (%)
Common 15610
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
* 8982
57.5%
. 1018
 
6.5%
1 709
 
4.5%
5 653
 
4.2%
4 644
 
4.1%
3 579
 
3.7%
6 571
 
3.7%
7 560
 
3.6%
2 530
 
3.4%
8 471
 
3.0%
Other values (2) 893
 
5.7%

Most occurring blocks

ValueCountFrequency (%)
ASCII 15610
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
* 8982
57.5%
. 1018
 
6.5%
1 709
 
4.5%
5 653
 
4.2%
4 644
 
4.1%
3 579
 
3.7%
6 571
 
3.7%
7 560
 
3.6%
2 530
 
3.4%
8 471
 
3.0%
Other values (2) 893
 
5.7%
Distinct863
Distinct (%)8.6%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
2023-12-11T15:10:46.132077image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length8
Median length1
Mean length1.4885
Min length1

Characters and Unicode

Total characters14885
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

Unique850 ?
Unique (%)8.5%

Sample

1st row*
2nd row*
3rd row*
4th row*
5th row*
ValueCountFrequency (%)
9122
91.2%
6.5932 3
 
< 0.1%
6.2582 3
 
< 0.1%
6.1896 3
 
< 0.1%
6.1882 3
 
< 0.1%
4.8895 2
 
< 0.1%
6.3192 2
 
< 0.1%
6.1898 2
 
< 0.1%
6.0641 2
 
< 0.1%
6.3074 2
 
< 0.1%
Other values (853) 856
 
8.6%
2023-12-11T15:10:46.682569image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
* 9122
61.3%
. 878
 
5.9%
1 607
 
4.1%
6 561
 
3.8%
5 540
 
3.6%
2 519
 
3.5%
4 516
 
3.5%
3 478
 
3.2%
7 447
 
3.0%
8 435
 
2.9%
Other values (2) 782
 
5.3%

Most occurring categories

ValueCountFrequency (%)
Other Punctuation 10000
67.2%
Decimal Number 4885
32.8%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 607
12.4%
6 561
11.5%
5 540
11.1%
2 519
10.6%
4 516
10.6%
3 478
9.8%
7 447
9.2%
8 435
8.9%
9 426
8.7%
0 356
7.3%
Other Punctuation
ValueCountFrequency (%)
* 9122
91.2%
. 878
 
8.8%

Most occurring scripts

ValueCountFrequency (%)
Common 14885
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
* 9122
61.3%
. 878
 
5.9%
1 607
 
4.1%
6 561
 
3.8%
5 540
 
3.6%
2 519
 
3.5%
4 516
 
3.5%
3 478
 
3.2%
7 447
 
3.0%
8 435
 
2.9%
Other values (2) 782
 
5.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 14885
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
* 9122
61.3%
. 878
 
5.9%
1 607
 
4.1%
6 561
 
3.8%
5 540
 
3.6%
2 519
 
3.5%
4 516
 
3.5%
3 478
 
3.2%
7 447
 
3.0%
8 435
 
2.9%
Other values (2) 782
 
5.3%
Distinct811
Distinct (%)8.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
2023-12-11T15:10:47.065366image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length8
Median length1
Mean length1.4962
Min length1

Characters and Unicode

Total characters14962
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

Unique761 ?
Unique (%)7.6%

Sample

1st row*
2nd row*
3rd row*
4th row5.1959
5th row*
ValueCountFrequency (%)
9087
90.9%
4.0608 7
 
0.1%
4.2096 7
 
0.1%
4.1192 6
 
0.1%
4.2094 6
 
0.1%
4.1152 5
 
< 0.1%
4.0185 5
 
< 0.1%
4.0944 5
 
< 0.1%
4.1855 5
 
< 0.1%
4.0937 4
 
< 0.1%
Other values (801) 863
 
8.6%
2023-12-11T15:10:47.643271image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
* 9087
60.7%
. 913
 
6.1%
4 684
 
4.6%
1 663
 
4.4%
2 532
 
3.6%
3 476
 
3.2%
5 460
 
3.1%
9 452
 
3.0%
6 448
 
3.0%
8 428
 
2.9%
Other values (2) 819
 
5.5%

Most occurring categories

ValueCountFrequency (%)
Other Punctuation 10000
66.8%
Decimal Number 4962
33.2%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
4 684
13.8%
1 663
13.4%
2 532
10.7%
3 476
9.6%
5 460
9.3%
9 452
9.1%
6 448
9.0%
8 428
8.6%
7 411
8.3%
0 408
8.2%
Other Punctuation
ValueCountFrequency (%)
* 9087
90.9%
. 913
 
9.1%

Most occurring scripts

ValueCountFrequency (%)
Common 14962
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
* 9087
60.7%
. 913
 
6.1%
4 684
 
4.6%
1 663
 
4.4%
2 532
 
3.6%
3 476
 
3.2%
5 460
 
3.1%
9 452
 
3.0%
6 448
 
3.0%
8 428
 
2.9%
Other values (2) 819
 
5.5%

Most occurring blocks

ValueCountFrequency (%)
ASCII 14962
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
* 9087
60.7%
. 913
 
6.1%
4 684
 
4.6%
1 663
 
4.4%
2 532
 
3.6%
3 476
 
3.2%
5 460
 
3.1%
9 452
 
3.0%
6 448
 
3.0%
8 428
 
2.9%
Other values (2) 819
 
5.5%
Distinct794
Distinct (%)7.9%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
2023-12-11T15:10:48.063820image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length9
Median length1
Mean length1.4564
Min length1

Characters and Unicode

Total characters14564
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

Unique774 ?
Unique (%)7.7%

Sample

1st row*
2nd row*
3rd row*
4th row*
5th row*
ValueCountFrequency (%)
9182
91.8%
5.4914 4
 
< 0.1%
5.69 3
 
< 0.1%
5.3242 3
 
< 0.1%
5.1443 3
 
< 0.1%
5.4905 3
 
< 0.1%
5.3236 2
 
< 0.1%
5.1989 2
 
< 0.1%
5.4397 2
 
< 0.1%
5.6897 2
 
< 0.1%
Other values (784) 794
 
7.9%
2023-12-11T15:10:48.602552image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
* 9182
63.0%
. 818
 
5.6%
1 677
 
4.6%
5 591
 
4.1%
4 497
 
3.4%
2 475
 
3.3%
3 455
 
3.1%
6 420
 
2.9%
8 386
 
2.7%
9 384
 
2.6%
Other values (2) 679
 
4.7%

Most occurring categories

ValueCountFrequency (%)
Other Punctuation 10000
68.7%
Decimal Number 4564
31.3%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 677
14.8%
5 591
12.9%
4 497
10.9%
2 475
10.4%
3 455
10.0%
6 420
9.2%
8 386
8.5%
9 384
8.4%
7 379
8.3%
0 300
6.6%
Other Punctuation
ValueCountFrequency (%)
* 9182
91.8%
. 818
 
8.2%

Most occurring scripts

ValueCountFrequency (%)
Common 14564
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
* 9182
63.0%
. 818
 
5.6%
1 677
 
4.6%
5 591
 
4.1%
4 497
 
3.4%
2 475
 
3.3%
3 455
 
3.1%
6 420
 
2.9%
8 386
 
2.7%
9 384
 
2.6%
Other values (2) 679
 
4.7%

Most occurring blocks

ValueCountFrequency (%)
ASCII 14564
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
* 9182
63.0%
. 818
 
5.6%
1 677
 
4.6%
5 591
 
4.1%
4 497
 
3.4%
2 475
 
3.3%
3 455
 
3.1%
6 420
 
2.9%
8 386
 
2.7%
9 384
 
2.6%
Other values (2) 679
 
4.7%
Distinct1221
Distinct (%)12.2%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
2023-12-11T15:10:48.950055image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length9
Median length1
Mean length1.7425
Min length1

Characters and Unicode

Total characters17425
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

Unique1134 ?
Unique (%)11.3%

Sample

1st row*
2nd row*
3rd row*
4th row*
5th row*
ValueCountFrequency (%)
8638
86.4%
5.5099 7
 
0.1%
5.3393 6
 
0.1%
5.2668 6
 
0.1%
5.2656 6
 
0.1%
5.34 5
 
< 0.1%
5.207 5
 
< 0.1%
5.1891 5
 
< 0.1%
5.5615 5
 
< 0.1%
5.1905 5
 
< 0.1%
Other values (1211) 1312
 
13.1%
2023-12-11T15:10:49.540487image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
* 8638
49.6%
. 1362
 
7.8%
5 1169
 
6.7%
1 973
 
5.6%
2 833
 
4.8%
4 747
 
4.3%
6 728
 
4.2%
3 712
 
4.1%
9 605
 
3.5%
8 579
 
3.3%
Other values (2) 1079
 
6.2%

Most occurring categories

ValueCountFrequency (%)
Other Punctuation 10000
57.4%
Decimal Number 7425
42.6%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
5 1169
15.7%
1 973
13.1%
2 833
11.2%
4 747
10.1%
6 728
9.8%
3 712
9.6%
9 605
8.1%
8 579
7.8%
7 575
7.7%
0 504
6.8%
Other Punctuation
ValueCountFrequency (%)
* 8638
86.4%
. 1362
 
13.6%

Most occurring scripts

ValueCountFrequency (%)
Common 17425
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
* 8638
49.6%
. 1362
 
7.8%
5 1169
 
6.7%
1 973
 
5.6%
2 833
 
4.8%
4 747
 
4.3%
6 728
 
4.2%
3 712
 
4.1%
9 605
 
3.5%
8 579
 
3.3%
Other values (2) 1079
 
6.2%

Most occurring blocks

ValueCountFrequency (%)
ASCII 17425
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
* 8638
49.6%
. 1362
 
7.8%
5 1169
 
6.7%
1 973
 
5.6%
2 833
 
4.8%
4 747
 
4.3%
6 728
 
4.2%
3 712
 
4.1%
9 605
 
3.5%
8 579
 
3.3%
Other values (2) 1079
 
6.2%
Distinct1669
Distinct (%)16.7%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
2023-12-11T15:10:49.882901image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length9
Median length1
Mean length1.9514
Min length1

Characters and Unicode

Total characters19514
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

Unique1629 ?
Unique (%)16.3%

Sample

1st row*
2nd row*
3rd row*
4th row6.4352
5th row*
ValueCountFrequency (%)
8288
82.9%
6.8282 4
 
< 0.1%
6.845 3
 
< 0.1%
6.8636 3
 
< 0.1%
6.8666 3
 
< 0.1%
6.7017 2
 
< 0.1%
6.8324 2
 
< 0.1%
6.8688 2
 
< 0.1%
6.8068 2
 
< 0.1%
6.8596 2
 
< 0.1%
Other values (1659) 1689
 
16.9%
2023-12-11T15:10:50.367785image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
* 8288
42.5%
. 1712
 
8.8%
1 1310
 
6.7%
6 1181
 
6.1%
8 993
 
5.1%
4 955
 
4.9%
2 933
 
4.8%
5 909
 
4.7%
3 867
 
4.4%
7 837
 
4.3%
Other values (2) 1529
 
7.8%

Most occurring categories

ValueCountFrequency (%)
Other Punctuation 10000
51.2%
Decimal Number 9514
48.8%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 1310
13.8%
6 1181
12.4%
8 993
10.4%
4 955
10.0%
2 933
9.8%
5 909
9.6%
3 867
9.1%
7 837
8.8%
9 831
8.7%
0 698
7.3%
Other Punctuation
ValueCountFrequency (%)
* 8288
82.9%
. 1712
 
17.1%

Most occurring scripts

ValueCountFrequency (%)
Common 19514
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
* 8288
42.5%
. 1712
 
8.8%
1 1310
 
6.7%
6 1181
 
6.1%
8 993
 
5.1%
4 955
 
4.9%
2 933
 
4.8%
5 909
 
4.7%
3 867
 
4.4%
7 837
 
4.3%
Other values (2) 1529
 
7.8%

Most occurring blocks

ValueCountFrequency (%)
ASCII 19514
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
* 8288
42.5%
. 1712
 
8.8%
1 1310
 
6.7%
6 1181
 
6.1%
8 993
 
5.1%
4 955
 
4.9%
2 933
 
4.8%
5 909
 
4.7%
3 867
 
4.4%
7 837
 
4.3%
Other values (2) 1529
 
7.8%
Distinct2203
Distinct (%)22.0%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
2023-12-11T15:10:50.789692image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length8
Median length1
Mean length2.2339
Min length1

Characters and Unicode

Total characters22339
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

Unique2141 ?
Unique (%)21.4%

Sample

1st row4.1355
2nd row*
3rd row*
4th row10.1118
5th row*
ValueCountFrequency (%)
7725
77.2%
5.1686 4
 
< 0.1%
5.2012 3
 
< 0.1%
5.1716 3
 
< 0.1%
5.204 3
 
< 0.1%
5.1426 3
 
< 0.1%
5.1546 3
 
< 0.1%
5.1698 3
 
< 0.1%
5.157 3
 
< 0.1%
7.7559 3
 
< 0.1%
Other values (2193) 2247
 
22.5%
2023-12-11T15:10:51.313152image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
* 7725
34.6%
. 2275
 
10.2%
1 1763
 
7.9%
5 1459
 
6.5%
4 1334
 
6.0%
2 1274
 
5.7%
7 1243
 
5.6%
6 1163
 
5.2%
8 1133
 
5.1%
3 1075
 
4.8%
Other values (2) 1895
 
8.5%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 12339
55.2%
Other Punctuation 10000
44.8%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 1763
14.3%
5 1459
11.8%
4 1334
10.8%
2 1274
10.3%
7 1243
10.1%
6 1163
9.4%
8 1133
9.2%
3 1075
8.7%
9 1011
8.2%
0 884
7.2%
Other Punctuation
ValueCountFrequency (%)
* 7725
77.2%
. 2275
 
22.8%

Most occurring scripts

ValueCountFrequency (%)
Common 22339
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
* 7725
34.6%
. 2275
 
10.2%
1 1763
 
7.9%
5 1459
 
6.5%
4 1334
 
6.0%
2 1274
 
5.7%
7 1243
 
5.6%
6 1163
 
5.2%
8 1133
 
5.1%
3 1075
 
4.8%
Other values (2) 1895
 
8.5%

Most occurring blocks

ValueCountFrequency (%)
ASCII 22339
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
* 7725
34.6%
. 2275
 
10.2%
1 1763
 
7.9%
5 1459
 
6.5%
4 1334
 
6.0%
2 1274
 
5.7%
7 1243
 
5.6%
6 1163
 
5.2%
8 1133
 
5.1%
3 1075
 
4.8%
Other values (2) 1895
 
8.5%
Distinct1714
Distinct (%)17.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
2023-12-11T15:10:51.639419image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length9
Median length1
Mean length1.9671
Min length1

Characters and Unicode

Total characters19671
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

Unique1664 ?
Unique (%)16.6%

Sample

1st row*
2nd row*
3rd row*
4th row*
5th row*
ValueCountFrequency (%)
8230
82.3%
5.728 4
 
< 0.1%
5.7962 3
 
< 0.1%
5.7574 3
 
< 0.1%
5.7558 3
 
< 0.1%
5.7554 3
 
< 0.1%
5.7776 3
 
< 0.1%
5.7862 3
 
< 0.1%
5.7704 2
 
< 0.1%
4.6065 2
 
< 0.1%
Other values (1704) 1744
 
17.4%
2023-12-11T15:10:52.237550image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
* 8230
41.8%
. 1770
 
9.0%
5 1296
 
6.6%
1 1203
 
6.1%
4 1019
 
5.2%
8 1013
 
5.1%
7 1011
 
5.1%
6 958
 
4.9%
2 951
 
4.8%
3 838
 
4.3%
Other values (2) 1382
 
7.0%

Most occurring categories

ValueCountFrequency (%)
Other Punctuation 10000
50.8%
Decimal Number 9671
49.2%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
5 1296
13.4%
1 1203
12.4%
4 1019
10.5%
8 1013
10.5%
7 1011
10.5%
6 958
9.9%
2 951
9.8%
3 838
8.7%
9 793
8.2%
0 589
6.1%
Other Punctuation
ValueCountFrequency (%)
* 8230
82.3%
. 1770
 
17.7%

Most occurring scripts

ValueCountFrequency (%)
Common 19671
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
* 8230
41.8%
. 1770
 
9.0%
5 1296
 
6.6%
1 1203
 
6.1%
4 1019
 
5.2%
8 1013
 
5.1%
7 1011
 
5.1%
6 958
 
4.9%
2 951
 
4.8%
3 838
 
4.3%
Other values (2) 1382
 
7.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 19671
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
* 8230
41.8%
. 1770
 
9.0%
5 1296
 
6.6%
1 1203
 
6.1%
4 1019
 
5.2%
8 1013
 
5.1%
7 1011
 
5.1%
6 958
 
4.9%
2 951
 
4.8%
3 838
 
4.3%
Other values (2) 1382
 
7.0%
Distinct1775
Distinct (%)17.8%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
2023-12-11T15:10:52.622085image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length9
Median length1
Mean length2.1006
Min length1

Characters and Unicode

Total characters21006
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

Unique1623 ?
Unique (%)16.2%

Sample

1st row*
2nd row*
3rd row7.2888
4th row*
5th row*
ValueCountFrequency (%)
7974
79.7%
4.0294 8
 
0.1%
4.024 7
 
0.1%
4.0242 6
 
0.1%
4.0244 5
 
< 0.1%
4.0466 5
 
< 0.1%
4.0424 5
 
< 0.1%
4.0276 5
 
< 0.1%
4.0438 5
 
< 0.1%
4.0253 5
 
< 0.1%
Other values (1765) 1975
 
19.8%
2023-12-11T15:10:53.148150image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
* 7974
38.0%
. 2026
 
9.6%
4 1737
 
8.3%
0 1340
 
6.4%
1 1323
 
6.3%
2 1148
 
5.5%
8 950
 
4.5%
3 934
 
4.4%
5 925
 
4.4%
7 903
 
4.3%
Other values (2) 1746
 
8.3%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 11006
52.4%
Other Punctuation 10000
47.6%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
4 1737
15.8%
0 1340
12.2%
1 1323
12.0%
2 1148
10.4%
8 950
8.6%
3 934
8.5%
5 925
8.4%
7 903
8.2%
9 878
8.0%
6 868
7.9%
Other Punctuation
ValueCountFrequency (%)
* 7974
79.7%
. 2026
 
20.3%

Most occurring scripts

ValueCountFrequency (%)
Common 21006
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
* 7974
38.0%
. 2026
 
9.6%
4 1737
 
8.3%
0 1340
 
6.4%
1 1323
 
6.3%
2 1148
 
5.5%
8 950
 
4.5%
3 934
 
4.4%
5 925
 
4.4%
7 903
 
4.3%
Other values (2) 1746
 
8.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 21006
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
* 7974
38.0%
. 2026
 
9.6%
4 1737
 
8.3%
0 1340
 
6.4%
1 1323
 
6.3%
2 1148
 
5.5%
8 950
 
4.5%
3 934
 
4.4%
5 925
 
4.4%
7 903
 
4.3%
Other values (2) 1746
 
8.3%
Distinct1147
Distinct (%)11.5%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
2023-12-11T15:10:53.576880image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length9
Median length1
Mean length1.6558
Min length1

Characters and Unicode

Total characters16558
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

Unique1141 ?
Unique (%)11.4%

Sample

1st row*
2nd row*
3rd row*
4th row*
5th row*
ValueCountFrequency (%)
8849
88.5%
7.3104 2
 
< 0.1%
6.1398 2
 
< 0.1%
7.2142 2
 
< 0.1%
7.1878 2
 
< 0.1%
7.3242 2
 
< 0.1%
78.1569 1
 
< 0.1%
6.1568 1
 
< 0.1%
17.8234 1
 
< 0.1%
65.1664 1
 
< 0.1%
Other values (1137) 1137
 
11.4%
2023-12-11T15:10:54.133393image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
* 8849
53.4%
. 1151
 
7.0%
1 934
 
5.6%
7 741
 
4.5%
2 695
 
4.2%
4 687
 
4.1%
5 684
 
4.1%
6 663
 
4.0%
3 616
 
3.7%
8 553
 
3.3%
Other values (2) 985
 
5.9%

Most occurring categories

ValueCountFrequency (%)
Other Punctuation 10000
60.4%
Decimal Number 6558
39.6%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 934
14.2%
7 741
11.3%
2 695
10.6%
4 687
10.5%
5 684
10.4%
6 663
10.1%
3 616
9.4%
8 553
8.4%
9 546
8.3%
0 439
6.7%
Other Punctuation
ValueCountFrequency (%)
* 8849
88.5%
. 1151
 
11.5%

Most occurring scripts

ValueCountFrequency (%)
Common 16558
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
* 8849
53.4%
. 1151
 
7.0%
1 934
 
5.6%
7 741
 
4.5%
2 695
 
4.2%
4 687
 
4.1%
5 684
 
4.1%
6 663
 
4.0%
3 616
 
3.7%
8 553
 
3.3%
Other values (2) 985
 
5.9%

Most occurring blocks

ValueCountFrequency (%)
ASCII 16558
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
* 8849
53.4%
. 1151
 
7.0%
1 934
 
5.6%
7 741
 
4.5%
2 695
 
4.2%
4 687
 
4.1%
5 684
 
4.1%
6 663
 
4.0%
3 616
 
3.7%
8 553
 
3.3%
Other values (2) 985
 
5.9%
Distinct1485
Distinct (%)14.8%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
2023-12-11T15:10:54.525818image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length9
Median length1
Mean length1.9066
Min length1

Characters and Unicode

Total characters19066
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

Unique1367 ?
Unique (%)13.7%

Sample

1st row*
2nd row*
3rd row8.0952
4th row*
5th row*
ValueCountFrequency (%)
8343
83.4%
4.0476 6
 
0.1%
4.0103 6
 
0.1%
4.0098 6
 
0.1%
4.0458 6
 
0.1%
4.0116 5
 
< 0.1%
4.0109 5
 
< 0.1%
4.0452 5
 
< 0.1%
4.0303 5
 
< 0.1%
4.0248 4
 
< 0.1%
Other values (1475) 1609
 
16.1%
2023-12-11T15:10:55.085241image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
* 8343
43.8%
. 1657
 
8.7%
4 1404
 
7.4%
0 1112
 
5.8%
1 1063
 
5.6%
2 867
 
4.5%
5 799
 
4.2%
6 778
 
4.1%
8 777
 
4.1%
9 770
 
4.0%
Other values (2) 1496
 
7.8%

Most occurring categories

ValueCountFrequency (%)
Other Punctuation 10000
52.4%
Decimal Number 9066
47.6%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
4 1404
15.5%
0 1112
12.3%
1 1063
11.7%
2 867
9.6%
5 799
8.8%
6 778
8.6%
8 777
8.6%
9 770
8.5%
3 756
8.3%
7 740
8.2%
Other Punctuation
ValueCountFrequency (%)
* 8343
83.4%
. 1657
 
16.6%

Most occurring scripts

ValueCountFrequency (%)
Common 19066
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
* 8343
43.8%
. 1657
 
8.7%
4 1404
 
7.4%
0 1112
 
5.8%
1 1063
 
5.6%
2 867
 
4.5%
5 799
 
4.2%
6 778
 
4.1%
8 777
 
4.1%
9 770
 
4.0%
Other values (2) 1496
 
7.8%

Most occurring blocks

ValueCountFrequency (%)
ASCII 19066
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
* 8343
43.8%
. 1657
 
8.7%
4 1404
 
7.4%
0 1112
 
5.8%
1 1063
 
5.6%
2 867
 
4.5%
5 799
 
4.2%
6 778
 
4.1%
8 777
 
4.1%
9 770
 
4.0%
Other values (2) 1496
 
7.8%
Distinct1063
Distinct (%)10.6%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
2023-12-11T15:10:55.814154image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length9
Median length1
Mean length1.6073
Min length1

Characters and Unicode

Total characters16073
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

Unique1056 ?
Unique (%)10.6%

Sample

1st row*
2nd row*
3rd row*
4th row*
5th row*
ValueCountFrequency (%)
8932
89.3%
5.7502 2
 
< 0.1%
5.8994 2
 
< 0.1%
8.7045 2
 
< 0.1%
8.1426 2
 
< 0.1%
7.5055 2
 
< 0.1%
5.8494 2
 
< 0.1%
25.3195 1
 
< 0.1%
5.5116 1
 
< 0.1%
50.4393 1
 
< 0.1%
Other values (1053) 1053
 
10.5%
2023-12-11T15:10:56.409141image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
* 8932
55.6%
. 1068
 
6.6%
1 779
 
4.8%
5 765
 
4.8%
2 650
 
4.0%
7 619
 
3.9%
8 606
 
3.8%
6 602
 
3.7%
4 594
 
3.7%
9 534
 
3.3%
Other values (2) 924
 
5.7%

Most occurring categories

ValueCountFrequency (%)
Other Punctuation 10000
62.2%
Decimal Number 6073
37.8%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 779
12.8%
5 765
12.6%
2 650
10.7%
7 619
10.2%
8 606
10.0%
6 602
9.9%
4 594
9.8%
9 534
8.8%
3 532
8.8%
0 392
6.5%
Other Punctuation
ValueCountFrequency (%)
* 8932
89.3%
. 1068
 
10.7%

Most occurring scripts

ValueCountFrequency (%)
Common 16073
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
* 8932
55.6%
. 1068
 
6.6%
1 779
 
4.8%
5 765
 
4.8%
2 650
 
4.0%
7 619
 
3.9%
8 606
 
3.8%
6 602
 
3.7%
4 594
 
3.7%
9 534
 
3.3%
Other values (2) 924
 
5.7%

Most occurring blocks

ValueCountFrequency (%)
ASCII 16073
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
* 8932
55.6%
. 1068
 
6.6%
1 779
 
4.8%
5 765
 
4.8%
2 650
 
4.0%
7 619
 
3.9%
8 606
 
3.8%
6 602
 
3.7%
4 594
 
3.7%
9 534
 
3.3%
Other values (2) 924
 
5.7%
Distinct1051
Distinct (%)10.5%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
2023-12-11T15:10:56.790996image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length9
Median length1
Mean length1.6006
Min length1

Characters and Unicode

Total characters16006
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

Unique1045 ?
Unique (%)10.4%

Sample

1st row*
2nd row*
3rd row*
4th row*
5th row*
ValueCountFrequency (%)
8945
89.5%
6.5586 2
 
< 0.1%
6.6686 2
 
< 0.1%
6.6804 2
 
< 0.1%
10.2927 2
 
< 0.1%
6.5746 2
 
< 0.1%
101.746 1
 
< 0.1%
171.5497 1
 
< 0.1%
65.3697 1
 
< 0.1%
7.0252 1
 
< 0.1%
Other values (1041) 1041
 
10.4%
2023-12-11T15:10:57.353780image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
* 8945
55.9%
. 1055
 
6.6%
1 787
 
4.9%
6 696
 
4.3%
2 646
 
4.0%
5 645
 
4.0%
4 611
 
3.8%
7 586
 
3.7%
3 569
 
3.6%
9 554
 
3.5%
Other values (2) 912
 
5.7%

Most occurring categories

ValueCountFrequency (%)
Other Punctuation 10000
62.5%
Decimal Number 6006
37.5%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 787
13.1%
6 696
11.6%
2 646
10.8%
5 645
10.7%
4 611
10.2%
7 586
9.8%
3 569
9.5%
9 554
9.2%
8 493
8.2%
0 419
7.0%
Other Punctuation
ValueCountFrequency (%)
* 8945
89.5%
. 1055
 
10.5%

Most occurring scripts

ValueCountFrequency (%)
Common 16006
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
* 8945
55.9%
. 1055
 
6.6%
1 787
 
4.9%
6 696
 
4.3%
2 646
 
4.0%
5 645
 
4.0%
4 611
 
3.8%
7 586
 
3.7%
3 569
 
3.6%
9 554
 
3.5%
Other values (2) 912
 
5.7%

Most occurring blocks

ValueCountFrequency (%)
ASCII 16006
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
* 8945
55.9%
. 1055
 
6.6%
1 787
 
4.9%
6 696
 
4.3%
2 646
 
4.0%
5 645
 
4.0%
4 611
 
3.8%
7 586
 
3.7%
3 569
 
3.6%
9 554
 
3.5%
Other values (2) 912
 
5.7%
Distinct1005
Distinct (%)10.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
2023-12-11T15:10:57.734953image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length9
Median length1
Mean length1.581
Min length1

Characters and Unicode

Total characters15810
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

Unique987 ?
Unique (%)9.9%

Sample

1st row*
2nd row*
3rd row*
4th row*
5th row*
ValueCountFrequency (%)
8974
89.7%
5.7402 4
 
< 0.1%
5.6856 3
 
< 0.1%
5.7196 3
 
< 0.1%
5.7774 3
 
< 0.1%
5.711 2
 
< 0.1%
5.6854 2
 
< 0.1%
5.798 2
 
< 0.1%
5.503 2
 
< 0.1%
11.1801 2
 
< 0.1%
Other values (995) 1003
 
10.0%
2023-12-11T15:10:58.190584image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
* 8974
56.8%
. 1026
 
6.5%
1 784
 
5.0%
5 705
 
4.5%
4 681
 
4.3%
6 597
 
3.8%
7 582
 
3.7%
2 569
 
3.6%
9 509
 
3.2%
3 505
 
3.2%
Other values (2) 878
 
5.6%

Most occurring categories

ValueCountFrequency (%)
Other Punctuation 10000
63.3%
Decimal Number 5810
36.7%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 784
13.5%
5 705
12.1%
4 681
11.7%
6 597
10.3%
7 582
10.0%
2 569
9.8%
9 509
8.8%
3 505
8.7%
8 499
8.6%
0 379
6.5%
Other Punctuation
ValueCountFrequency (%)
* 8974
89.7%
. 1026
 
10.3%

Most occurring scripts

ValueCountFrequency (%)
Common 15810
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
* 8974
56.8%
. 1026
 
6.5%
1 784
 
5.0%
5 705
 
4.5%
4 681
 
4.3%
6 597
 
3.8%
7 582
 
3.7%
2 569
 
3.6%
9 509
 
3.2%
3 505
 
3.2%
Other values (2) 878
 
5.6%

Most occurring blocks

ValueCountFrequency (%)
ASCII 15810
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
* 8974
56.8%
. 1026
 
6.5%
1 784
 
5.0%
5 705
 
4.5%
4 681
 
4.3%
6 597
 
3.8%
7 582
 
3.7%
2 569
 
3.6%
9 509
 
3.2%
3 505
 
3.2%
Other values (2) 878
 
5.6%
Distinct887
Distinct (%)8.9%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
2023-12-11T15:10:58.524378image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length9
Median length1
Mean length1.508
Min length1

Characters and Unicode

Total characters15080
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

Unique874 ?
Unique (%)8.7%

Sample

1st row*
2nd row*
3rd row*
4th row*
5th row*
ValueCountFrequency (%)
9101
91.0%
6.0386 3
 
< 0.1%
5.8668 2
 
< 0.1%
6.0196 2
 
< 0.1%
5.8664 2
 
< 0.1%
11.9968 2
 
< 0.1%
5.9386 2
 
< 0.1%
6.0034 2
 
< 0.1%
8.9337 2
 
< 0.1%
14.984 2
 
< 0.1%
Other values (877) 880
 
8.8%
2023-12-11T15:10:58.964567image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
* 9101
60.4%
. 899
 
6.0%
1 631
 
4.2%
5 583
 
3.9%
4 551
 
3.7%
9 527
 
3.5%
3 497
 
3.3%
8 488
 
3.2%
6 487
 
3.2%
2 485
 
3.2%
Other values (2) 831
 
5.5%

Most occurring categories

ValueCountFrequency (%)
Other Punctuation 10000
66.3%
Decimal Number 5080
33.7%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 631
12.4%
5 583
11.5%
4 551
10.8%
9 527
10.4%
3 497
9.8%
8 488
9.6%
6 487
9.6%
2 485
9.5%
7 448
8.8%
0 383
7.5%
Other Punctuation
ValueCountFrequency (%)
* 9101
91.0%
. 899
 
9.0%

Most occurring scripts

ValueCountFrequency (%)
Common 15080
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
* 9101
60.4%
. 899
 
6.0%
1 631
 
4.2%
5 583
 
3.9%
4 551
 
3.7%
9 527
 
3.5%
3 497
 
3.3%
8 488
 
3.2%
6 487
 
3.2%
2 485
 
3.2%
Other values (2) 831
 
5.5%

Most occurring blocks

ValueCountFrequency (%)
ASCII 15080
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
* 9101
60.4%
. 899
 
6.0%
1 631
 
4.2%
5 583
 
3.9%
4 551
 
3.7%
9 527
 
3.5%
3 497
 
3.3%
8 488
 
3.2%
6 487
 
3.2%
2 485
 
3.2%
Other values (2) 831
 
5.5%
Distinct775
Distinct (%)7.8%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
2023-12-11T15:10:59.275497image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length8
Median length1
Mean length1.4504
Min length1

Characters and Unicode

Total characters14504
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

Unique765 ?
Unique (%)7.6%

Sample

1st row*
2nd row*
3rd row*
4th row*
5th row*
ValueCountFrequency (%)
9206
92.1%
4.0534 8
 
0.1%
4.0337 4
 
< 0.1%
4.0336 4
 
< 0.1%
4.0334 3
 
< 0.1%
4.0535 2
 
< 0.1%
4.0531 2
 
< 0.1%
4.0335 2
 
< 0.1%
4.0532 2
 
< 0.1%
4.0354 2
 
< 0.1%
Other values (765) 765
 
7.6%
2023-12-11T15:10:59.700610image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
* 9206
63.5%
. 794
 
5.5%
1 593
 
4.1%
4 526
 
3.6%
3 484
 
3.3%
5 456
 
3.1%
7 452
 
3.1%
2 437
 
3.0%
6 419
 
2.9%
8 399
 
2.8%
Other values (2) 738
 
5.1%

Most occurring categories

ValueCountFrequency (%)
Other Punctuation 10000
68.9%
Decimal Number 4504
31.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 593
13.2%
4 526
11.7%
3 484
10.7%
5 456
10.1%
7 452
10.0%
2 437
9.7%
6 419
9.3%
8 399
8.9%
9 385
8.5%
0 353
7.8%
Other Punctuation
ValueCountFrequency (%)
* 9206
92.1%
. 794
 
7.9%

Most occurring scripts

ValueCountFrequency (%)
Common 14504
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
* 9206
63.5%
. 794
 
5.5%
1 593
 
4.1%
4 526
 
3.6%
3 484
 
3.3%
5 456
 
3.1%
7 452
 
3.1%
2 437
 
3.0%
6 419
 
2.9%
8 399
 
2.8%
Other values (2) 738
 
5.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 14504
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
* 9206
63.5%
. 794
 
5.5%
1 593
 
4.1%
4 526
 
3.6%
3 484
 
3.3%
5 456
 
3.1%
7 452
 
3.1%
2 437
 
3.0%
6 419
 
2.9%
8 399
 
2.8%
Other values (2) 738
 
5.1%
Distinct889
Distinct (%)8.9%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
2023-12-11T15:11:00.072372image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length8
Median length1
Mean length1.5645
Min length1

Characters and Unicode

Total characters15645
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

Unique812 ?
Unique (%)8.1%

Sample

1st row5.2619
2nd row*
3rd row*
4th row*
5th row*
ValueCountFrequency (%)
8978
89.8%
4.966 6
 
0.1%
5.158 6
 
0.1%
5.0895 4
 
< 0.1%
5.1399 4
 
< 0.1%
5.2622 4
 
< 0.1%
5.0683 4
 
< 0.1%
5.2673 4
 
< 0.1%
5.2619 4
 
< 0.1%
5.2668 4
 
< 0.1%
Other values (879) 982
 
9.8%
2023-12-11T15:11:00.539098image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
* 8978
57.4%
. 1022
 
6.5%
5 792
 
5.1%
1 713
 
4.6%
2 589
 
3.8%
4 567
 
3.6%
3 551
 
3.5%
6 547
 
3.5%
7 505
 
3.2%
9 498
 
3.2%
Other values (2) 883
 
5.6%

Most occurring categories

ValueCountFrequency (%)
Other Punctuation 10000
63.9%
Decimal Number 5645
36.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
5 792
14.0%
1 713
12.6%
2 589
10.4%
4 567
10.0%
3 551
9.8%
6 547
9.7%
7 505
8.9%
9 498
8.8%
8 446
7.9%
0 437
7.7%
Other Punctuation
ValueCountFrequency (%)
* 8978
89.8%
. 1022
 
10.2%

Most occurring scripts

ValueCountFrequency (%)
Common 15645
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
* 8978
57.4%
. 1022
 
6.5%
5 792
 
5.1%
1 713
 
4.6%
2 589
 
3.8%
4 567
 
3.6%
3 551
 
3.5%
6 547
 
3.5%
7 505
 
3.2%
9 498
 
3.2%
Other values (2) 883
 
5.6%

Most occurring blocks

ValueCountFrequency (%)
ASCII 15645
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
* 8978
57.4%
. 1022
 
6.5%
5 792
 
5.1%
1 713
 
4.6%
2 589
 
3.8%
4 567
 
3.6%
3 551
 
3.5%
6 547
 
3.5%
7 505
 
3.2%
9 498
 
3.2%
Other values (2) 883
 
5.6%
Distinct1587
Distinct (%)15.9%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
2023-12-11T15:11:00.859515image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length9
Median length1
Mean length2.0487
Min length1

Characters and Unicode

Total characters20487
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

Unique1549 ?
Unique (%)15.5%

Sample

1st row*
2nd row*
3rd row4.2428
4th row*
5th row*
ValueCountFrequency (%)
8045
80.5%
4.6245 108
 
1.1%
4.6256 81
 
0.8%
4.625 66
 
0.7%
4.6253 55
 
0.5%
9.2512 8
 
0.1%
9.2506 8
 
0.1%
9.25 7
 
0.1%
9.249 6
 
0.1%
9.2489 6
 
0.1%
Other values (1577) 1610
 
16.1%
2023-12-11T15:11:01.295722image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
* 8045
39.3%
. 1955
 
9.5%
4 1554
 
7.6%
2 1284
 
6.3%
6 1256
 
6.1%
1 1181
 
5.8%
5 1180
 
5.8%
3 962
 
4.7%
9 852
 
4.2%
7 852
 
4.2%
Other values (2) 1366
 
6.7%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 10487
51.2%
Other Punctuation 10000
48.8%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
4 1554
14.8%
2 1284
12.2%
6 1256
12.0%
1 1181
11.3%
5 1180
11.3%
3 962
9.2%
9 852
8.1%
7 852
8.1%
8 802
7.6%
0 564
 
5.4%
Other Punctuation
ValueCountFrequency (%)
* 8045
80.5%
. 1955
 
19.6%

Most occurring scripts

ValueCountFrequency (%)
Common 20487
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
* 8045
39.3%
. 1955
 
9.5%
4 1554
 
7.6%
2 1284
 
6.3%
6 1256
 
6.1%
1 1181
 
5.8%
5 1180
 
5.8%
3 962
 
4.7%
9 852
 
4.2%
7 852
 
4.2%
Other values (2) 1366
 
6.7%

Most occurring blocks

ValueCountFrequency (%)
ASCII 20487
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
* 8045
39.3%
. 1955
 
9.5%
4 1554
 
7.6%
2 1284
 
6.3%
6 1256
 
6.1%
1 1181
 
5.8%
5 1180
 
5.8%
3 962
 
4.7%
9 852
 
4.2%
7 852
 
4.2%
Other values (2) 1366
 
6.7%

Sample

기준일ID시간대구분행정동코드거주지 자치구 코드총생활인구수남자10세부터14세생활인구수남자15세부터19세생활인구수남자20세부터24세생활인구수남자25세부터29세생활인구수남자30세부터34세생활인구수남자35세부터39세생활인구수남자40세부터44세생활인구수남자45세부터49세생활인구수남자50세부터54세생활인구수남자55세부터59세생활인구수남자60세부터64세생활인구수남자65세부터69세생활인구수남자70세부터74세생활인구수남자75세부터79세생활인구수여자10세부터14세생활인구수여자15세부터19세생활인구수여자20세부터24세생활인구수여자25세부터29세생활인구수여자30세부터34세생활인구수여자35세부터39세생활인구수여자40세부터44세생활인구수여자45세부터49세생활인구수여자50세부터54세생활인구수여자55세부터59세생활인구수여자60세부터64세생활인구수여자65세부터69세생활인구수여자70세부터74세생활인구수여자75세부터79세생활인구수장기체류외국인수
26451202210152115005101129015*****************4.1355*********5.2619*
3450520221015311320515117107*****************************
12412202210151112306101114062***5.18446.90974.2331*************7.2888*8.0952******4.2428
22255202210152112157301171051*5.3563*7.7639*8.2033*******5.1959**6.435210.1118***********
4117220221015411110515113205*****************************
10564202210151111106401117044*****7.0938***********4.0348*13.48985.5375********
8918202210150116806101154517*****************5.2294***********
38273202210153115905201150019*****************************
447732022101541132051511320263864.2839108.393689.478186.428688.6281130.4617138.4181101.95685.7856109.944666.800879.948155.438942.273276.009293.3279113.0481104.692189.3624127.164692.4568116.646999.9163153.2714115.326160.159781.94445.490421.064
259682022101521144072011440201332.316830.348684.417499.8511111.870890.922364.141690.6449110.76556.72245.582830.937823.958232.214537.2849.3145110.4641112.662897.7328124.970982.1548118.194165.804665.352546.100944.032230.876749.548474.0482
기준일ID시간대구분행정동코드거주지 자치구 코드총생활인구수남자10세부터14세생활인구수남자15세부터19세생활인구수남자20세부터24세생활인구수남자25세부터29세생활인구수남자30세부터34세생활인구수남자35세부터39세생활인구수남자40세부터44세생활인구수남자45세부터49세생활인구수남자50세부터54세생활인구수남자55세부터59세생활인구수남자60세부터64세생활인구수남자65세부터69세생활인구수남자70세부터74세생활인구수남자75세부터79세생활인구수여자10세부터14세생활인구수여자15세부터19세생활인구수여자20세부터24세생활인구수여자25세부터29세생활인구수여자30세부터34세생활인구수여자35세부터39세생활인구수여자40세부터44세생활인구수여자45세부터49세생활인구수여자50세부터54세생활인구수여자55세부터59세생활인구수여자60세부터64세생활인구수여자65세부터69세생활인구수여자70세부터74세생활인구수여자75세부터79세생활인구수장기체류외국인수
48633202210154115905601117011*****************************
10369202210151111105301162044***5.12985.222810.5698***********5.3413***********
21338202210152111406651168018*****************************
18269202210151116206251174012*****************************
6510202210150115305951156092*4.2945**4.09028.7514*4.6761********8.8954*4.4064****6.3479****29.5564
53673202210155112307101168021**4.7808**************************
77632022101501162052511590170225.991868.719538.468488.303389.308781.053364.397777.072960.812673.589153.853225.36224.117428.695940.556148.261654.793102.396166.420969.415772.72880.377562.116475.974561.053654.322840.692955.609917.8209
2081202210150112306001144014*****************************
2442520221015211320710111700*****************************
45962202210154114106151150027******************5.8048*****5.2366****