Overview

Dataset statistics

Number of variables9
Number of observations32
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory2.5 KiB
Average record size in memory79.1 B

Variable types

Text6
Numeric3

Dataset

Description경기도_시군별 장애인체육회 현황
Author경기복지재단(경기도장애인복지종합지원센터)
URLhttps://data.gg.go.kr/portal/data/service/selectServicePage.do?&infId=MUDZAQABQL9NPSO5VQI125411245&infSeq=1

Alerts

소재지우편번호 is highly overall correlated with WGS84위도High correlation
WGS84위도 is highly overall correlated with 소재지우편번호High correlation
기관명 has unique valuesUnique
소재지지번주소 has unique valuesUnique
소재지도로명주소 has unique valuesUnique
소재지우편번호 has unique valuesUnique
WGS84위도 has unique valuesUnique
WGS84경도 has unique valuesUnique
전화번호 has unique valuesUnique

Reproduction

Analysis started2023-12-10 21:24:26.170380
Analysis finished2023-12-10 21:24:27.373758
Duration1.2 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

시군명
Text

Distinct31
Distinct (%)96.9%
Missing0
Missing (%)0.0%
Memory size388.0 B
2023-12-11T06:24:27.515442image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length4
Median length3
Mean length3.09375
Min length3

Characters and Unicode

Total characters99
Distinct characters38
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique30 ?
Unique (%)93.8%

Sample

1st row가평군
2nd row고양시
3rd row과천시
4th row광명시
5th row광주시
ValueCountFrequency (%)
수원시 2
 
6.2%
가평군 1
 
3.1%
안양시 1
 
3.1%
하남시 1
 
3.1%
포천시 1
 
3.1%
평택시 1
 
3.1%
파주시 1
 
3.1%
이천시 1
 
3.1%
의정부시 1
 
3.1%
의왕시 1
 
3.1%
Other values (21) 21
65.6%
2023-12-11T06:24:27.826712image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
시 30
30.3%
천 6
 
6.1%
주 5
 
5.1%
양 5
 
5.1%
군 4
 
4.0%
남 3
 
3.0%
안 3
 
3.0%
성 3
 
3.0%
평 3
 
3.0%
포 3
 
3.0%
Other values (28) 34
34.3%

Most occurring categories

ValueCountFrequency (%)
Other Letter 99
100.0%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
시 30
30.3%
천 6
 
6.1%
주 5
 
5.1%
양 5
 
5.1%
군 4
 
4.0%
남 3
 
3.0%
안 3
 
3.0%
성 3
 
3.0%
평 3
 
3.0%
포 3
 
3.0%
Other values (28) 34
34.3%

Most occurring scripts

ValueCountFrequency (%)
Hangul 99
100.0%

Most frequent character per script

Hangul
ValueCountFrequency (%)
시 30
30.3%
천 6
 
6.1%
주 5
 
5.1%
양 5
 
5.1%
군 4
 
4.0%
남 3
 
3.0%
안 3
 
3.0%
성 3
 
3.0%
평 3
 
3.0%
포 3
 
3.0%
Other values (28) 34
34.3%

Most occurring blocks

ValueCountFrequency (%)
Hangul 99
100.0%

Most frequent character per block

Hangul
ValueCountFrequency (%)
시 30
30.3%
천 6
 
6.1%
주 5
 
5.1%
양 5
 
5.1%
군 4
 
4.0%
남 3
 
3.0%
안 3
 
3.0%
성 3
 
3.0%
평 3
 
3.0%
포 3
 
3.0%
Other values (28) 34
34.3%

기관명
Text

UNIQUE 

Distinct32
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size388.0 B
2023-12-11T06:24:28.035804image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length10
Median length9
Mean length9.09375
Min length9

Characters and Unicode

Total characters291
Distinct characters46
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique32 ?
Unique (%)100.0%

Sample

1st row가평군장애인체육회
2nd row고양시장애인체육회
3rd row과천시장애인체육회
4th row광명시장애인체육회
5th row광주시장애인체육회
ValueCountFrequency (%)
가평군장애인체육회 1
 
3.1%
고양시장애인체육회 1
 
3.1%
하남시장애인체육회 1
 
3.1%
포천시장애인체육회 1
 
3.1%
평택시장애인체육회 1
 
3.1%
파주시장애인체육회 1
 
3.1%
이천시장애인체육회 1
 
3.1%
의정부시장애인체육회 1
 
3.1%
의왕시장애인체육회 1
 
3.1%
용인시장애인체육회 1
 
3.1%
Other values (22) 22
68.8%
2023-12-11T06:24:28.334764image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
인 33
11.3%
회 32
11.0%
장 32
11.0%
애 32
11.0%
체 32
11.0%
육 32
11.0%
시 29
10.0%
천 6
 
2.1%
양 5
 
1.7%
주 5
 
1.7%
Other values (36) 53
18.2%

Most occurring categories

ValueCountFrequency (%)
Other Letter 291
100.0%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
인 33
11.3%
회 32
11.0%
장 32
11.0%
애 32
11.0%
체 32
11.0%
육 32
11.0%
시 29
10.0%
천 6
 
2.1%
양 5
 
1.7%
주 5
 
1.7%
Other values (36) 53
18.2%

Most occurring scripts

ValueCountFrequency (%)
Hangul 291
100.0%

Most frequent character per script

Hangul
ValueCountFrequency (%)
인 33
11.3%
회 32
11.0%
장 32
11.0%
애 32
11.0%
체 32
11.0%
육 32
11.0%
시 29
10.0%
천 6
 
2.1%
양 5
 
1.7%
주 5
 
1.7%
Other values (36) 53
18.2%

Most occurring blocks

ValueCountFrequency (%)
Hangul 291
100.0%

Most frequent character per block

Hangul
ValueCountFrequency (%)
인 33
11.3%
회 32
11.0%
장 32
11.0%
애 32
11.0%
체 32
11.0%
육 32
11.0%
시 29
10.0%
천 6
 
2.1%
양 5
 
1.7%
주 5
 
1.7%
Other values (36) 53
18.2%

소재지지번주소
Text

UNIQUE 

Distinct32
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size388.0 B
2023-12-11T06:24:28.586446image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length23
Median length21
Mean length19.4375
Min length15

Characters and Unicode

Total characters622
Distinct characters97
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique32 ?
Unique (%)100.0%

Sample

1st row경기도 가평군 가평읍 대곡리 316번지
2nd row경기도 고양시 일산서구 대화동 2320번지
3rd row경기도 과천시 관문동 3번지
4th row경기도 광명시 하안동 577번지
5th row경기도 광주시 양벌동 36-1
ValueCountFrequency (%)
경기도 32
 
22.4%
수원시 2
 
1.4%
장안구 2
 
1.4%
210번지 1
 
0.7%
처인구 1
 
0.7%
용인시 1
 
0.7%
345번지 1
 
0.7%
오산동 1
 
0.7%
오산시 1
 
0.7%
320번지 1
 
0.7%
Other values (100) 100
69.9%
2023-12-11T06:24:28.983544image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
111
17.8%
도 34
 
5.5%
경 32
 
5.1%
기 32
 
5.1%
지 32
 
5.1%
번 31
 
5.0%
시 30
 
4.8%
동 27
 
4.3%
1 18
 
2.9%
2 14
 
2.3%
Other values (87) 261
42.0%

Most occurring categories

ValueCountFrequency (%)
Other Letter 400
64.3%
Space Separator 111
 
17.8%
Decimal Number 101
 
16.2%
Dash Punctuation 10
 
1.6%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
도 34
 
8.5%
경 32
 
8.0%
기 32
 
8.0%
지 32
 
8.0%
번 31
 
7.8%
시 30
 
7.5%
동 27
 
6.8%
양 9
 
2.2%
리 9
 
2.2%
구 9
 
2.2%
Other values (75) 155
38.8%
Decimal Number
ValueCountFrequency (%)
1 18
17.8%
2 14
13.9%
0 13
12.9%
3 13
12.9%
6 13
12.9%
8 10
9.9%
7 7
 
6.9%
9 5
 
5.0%
4 4
 
4.0%
5 4
 
4.0%
Space Separator
ValueCountFrequency (%)
111
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 10
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 400
64.3%
Common 222
35.7%

Most frequent character per script

Hangul
ValueCountFrequency (%)
도 34
 
8.5%
경 32
 
8.0%
기 32
 
8.0%
지 32
 
8.0%
번 31
 
7.8%
시 30
 
7.5%
동 27
 
6.8%
양 9
 
2.2%
리 9
 
2.2%
구 9
 
2.2%
Other values (75) 155
38.8%
Common
ValueCountFrequency (%)
111
50.0%
1 18
 
8.1%
2 14
 
6.3%
0 13
 
5.9%
3 13
 
5.9%
6 13
 
5.9%
8 10
 
4.5%
- 10
 
4.5%
7 7
 
3.2%
9 5
 
2.3%
Other values (2) 8
 
3.6%

Most occurring blocks

ValueCountFrequency (%)
Hangul 400
64.3%
ASCII 222
35.7%

Most frequent character per block

ASCII
ValueCountFrequency (%)
111
50.0%
1 18
 
8.1%
2 14
 
6.3%
0 13
 
5.9%
3 13
 
5.9%
6 13
 
5.9%
8 10
 
4.5%
- 10
 
4.5%
7 7
 
3.2%
9 5
 
2.3%
Other values (2) 8
 
3.6%
Hangul
ValueCountFrequency (%)
도 34
 
8.5%
경 32
 
8.0%
기 32
 
8.0%
지 32
 
8.0%
번 31
 
7.8%
시 30
 
7.5%
동 27
 
6.8%
양 9
 
2.2%
리 9
 
2.2%
구 9
 
2.2%
Other values (75) 155
38.8%

소재지도로명주소
Text

UNIQUE 

Distinct32
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size388.0 B
2023-12-11T06:24:29.244492image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length24
Median length21
Mean length17.84375
Min length14

Characters and Unicode

Total characters571
Distinct characters99
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique32 ?
Unique (%)100.0%

Sample

1st row경기도 가평군 가평읍 문화로 131
2nd row경기도 고양시 일산서구 중앙로 1601
3rd row경기도 과천시 중앙로 294
4th row경기도 광명시 오리로 703
5th row경기도 광주시 양벌동 36-1
ValueCountFrequency (%)
경기도 32
 
22.4%
중앙로 3
 
2.1%
장안구 2
 
1.4%
수원시 2
 
1.4%
종합운동장로 2
 
1.4%
문화로 2
 
1.4%
화성시 1
 
0.7%
향교로 1
 
0.7%
용인시 1
 
0.7%
271 1
 
0.7%
Other values (96) 96
67.1%
2023-12-11T06:24:29.616063image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
111
19.4%
경 32
 
5.6%
도 32
 
5.6%
기 32
 
5.6%
시 31
 
5.4%
로 31
 
5.4%
1 19
 
3.3%
6 18
 
3.2%
0 13
 
2.3%
3 9
 
1.6%
Other values (89) 243
42.6%

Most occurring categories

ValueCountFrequency (%)
Other Letter 360
63.0%
Space Separator 111
 
19.4%
Decimal Number 98
 
17.2%
Dash Punctuation 2
 
0.4%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
경 32
 
8.9%
도 32
 
8.9%
기 32
 
8.9%
시 31
 
8.6%
로 31
 
8.6%
천 9
 
2.5%
구 9
 
2.5%
안 7
 
1.9%
양 7
 
1.9%
동 7
 
1.9%
Other values (77) 163
45.3%
Decimal Number
ValueCountFrequency (%)
1 19
19.4%
6 18
18.4%
0 13
13.3%
3 9
9.2%
2 9
9.2%
9 8
8.2%
7 7
 
7.1%
8 7
 
7.1%
4 4
 
4.1%
5 4
 
4.1%
Space Separator
ValueCountFrequency (%)
111
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 360
63.0%
Common 211
37.0%

Most frequent character per script

Hangul
ValueCountFrequency (%)
경 32
 
8.9%
도 32
 
8.9%
기 32
 
8.9%
시 31
 
8.6%
로 31
 
8.6%
천 9
 
2.5%
구 9
 
2.5%
안 7
 
1.9%
양 7
 
1.9%
동 7
 
1.9%
Other values (77) 163
45.3%
Common
ValueCountFrequency (%)
111
52.6%
1 19
 
9.0%
6 18
 
8.5%
0 13
 
6.2%
3 9
 
4.3%
2 9
 
4.3%
9 8
 
3.8%
7 7
 
3.3%
8 7
 
3.3%
4 4
 
1.9%
Other values (2) 6
 
2.8%

Most occurring blocks

ValueCountFrequency (%)
Hangul 360
63.0%
ASCII 211
37.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
111
52.6%
1 19
 
9.0%
6 18
 
8.5%
0 13
 
6.2%
3 9
 
4.3%
2 9
 
4.3%
9 8
 
3.8%
7 7
 
3.3%
8 7
 
3.3%
4 4
 
1.9%
Other values (2) 6
 
2.8%
Hangul
ValueCountFrequency (%)
경 32
 
8.9%
도 32
 
8.9%
기 32
 
8.9%
시 31
 
8.6%
로 31
 
8.6%
천 9
 
2.5%
구 9
 
2.5%
안 7
 
1.9%
양 7
 
1.9%
동 7
 
1.9%
Other values (77) 163
45.3%

소재지우편번호
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct32
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean13962.188
Minimum10110
Maximum18588
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size420.0 B
2023-12-11T06:24:29.729534image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum10110
5-th percentile10613.5
Q111837.75
median13596.5
Q316132.5
95-th percentile18005.6
Maximum18588
Range8478
Interquartile range (IQR)4294.75

Descriptive statistics

Standard deviation2534.6065
Coefficient of variation (CV)0.18153363
Kurtosis-1.166209
Mean13962.188
Median Absolute Deviation (MAD)2165.5
Skewness0.28225747
Sum446790
Variance6424230.4
MonotonicityNot monotonic
2023-12-11T06:24:29.829920image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=32)
ValueCountFrequency (%)
12416 1
 
3.1%
13918 1
 
3.1%
18588 1
 
3.1%
12912 1
 
3.1%
11154 1
 
3.1%
17903 1
 
3.1%
10933 1
 
3.1%
17321 1
 
3.1%
11606 1
 
3.1%
16074 1
 
3.1%
Other values (22) 22
68.8%
ValueCountFrequency (%)
10110 1
3.1%
10223 1
3.1%
10933 1
3.1%
11012 1
3.1%
11154 1
3.1%
11360 1
3.1%
11502 1
3.1%
11606 1
3.1%
11915 1
3.1%
12244 1
3.1%
ValueCountFrequency (%)
18588 1
3.1%
18131 1
3.1%
17903 1
3.1%
17508 1
3.1%
17321 1
3.1%
16997 1
3.1%
16312 1
3.1%
16308 1
3.1%
16074 1
3.1%
15862 1
3.1%

WGS84위도
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct32
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean37.480348
Minimum36.98852
Maximum38.10751
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size420.0 B
2023-12-11T06:24:29.930823image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum36.98852
5-th percentile37.081322
Q137.296015
median37.436406
Q337.632001
95-th percentile37.894029
Maximum38.10751
Range1.1189902
Interquartile range (IQR)0.33598527

Descriptive statistics

Standard deviation0.2649887
Coefficient of variation (CV)0.0070700704
Kurtosis-0.17986414
Mean37.480348
Median Absolute Deviation (MAD)0.15636033
Skewness0.32956208
Sum1199.3711
Variance0.070219011
MonotonicityNot monotonic
2023-12-11T06:24:30.024457image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=32)
ValueCountFrequency (%)
37.8248742 1
 
3.1%
37.40527507 1
 
3.1%
37.13786295 1
 
3.1%
37.56673662 1
 
3.1%
37.88847519 1
 
3.1%
36.98851982 1
 
3.1%
37.75609246 1
 
3.1%
37.28722085 1
 
3.1%
37.75756895 1
 
3.1%
37.35067807 1
 
3.1%
Other values (22) 22
68.8%
ValueCountFrequency (%)
36.98851982 1
3.1%
37.012216 1
3.1%
37.13786295 1
3.1%
37.15626019 1
3.1%
37.24962344 1
3.1%
37.28722085 1
3.1%
37.28816117 1
3.1%
37.2955356 1
3.1%
37.29617521 1
3.1%
37.31958913 1
3.1%
ValueCountFrequency (%)
38.10751004 1
3.1%
37.90081724 1
3.1%
37.88847519 1
3.1%
37.8248742 1
3.1%
37.81300318 1
3.1%
37.75756895 1
3.1%
37.75609246 1
3.1%
37.6756846 1
3.1%
37.61743924 1
3.1%
37.60683867 1
3.1%

WGS84경도
Real number (ℝ)

UNIQUE 

Distinct32
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean127.07443
Minimum126.72002
Maximum127.6299
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size420.0 B
2023-12-11T06:24:30.125221image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum126.72002
5-th percentile126.7663
Q1126.9329
median127.0498
Q3127.18091
95-th percentile127.51398
Maximum127.6299
Range0.9098798
Interquartile range (IQR)0.24800568

Descriptive statistics

Standard deviation0.23427112
Coefficient of variation (CV)0.001843574
Kurtosis0.084546808
Mean127.07443
Median Absolute Deviation (MAD)0.12710345
Skewness0.70202347
Sum4066.3818
Variance0.054882959
MonotonicityNot monotonic
2023-12-11T06:24:30.221625image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=32)
ValueCountFrequency (%)
127.507218 1
 
3.1%
126.9467029 1
 
3.1%
126.9224111 1
 
3.1%
127.1937861 1
 
3.1%
127.2005478 1
 
3.1%
127.1082554 1
 
3.1%
126.7857331 1
 
3.1%
127.4956237 1
 
3.1%
127.0290955 1
 
3.1%
126.9681601 1
 
3.1%
Other values (22) 22
68.8%
ValueCountFrequency (%)
126.720024 1
3.1%
126.7425418 1
3.1%
126.7857331 1
3.1%
126.7988743 1
3.1%
126.8052413 1
3.1%
126.815741 1
3.1%
126.8714047 1
3.1%
126.9224111 1
3.1%
126.9364021 1
3.1%
126.9467029 1
3.1%
ValueCountFrequency (%)
127.6299038 1
3.1%
127.5222499 1
3.1%
127.507218 1
3.1%
127.4956237 1
3.1%
127.3279763 1
3.1%
127.2578004 1
3.1%
127.2005478 1
3.1%
127.1937861 1
3.1%
127.176618 1
3.1%
127.1651613 1
3.1%

전화번호
Text

UNIQUE 

Distinct32
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size388.0 B
2023-12-11T06:24:30.390619image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length13
Median length12
Mean length12.0625
Min length11

Characters and Unicode

Total characters386
Distinct characters11
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique32 ?
Unique (%)100.0%

Sample

1st row031-8078-7976
2nd row031-912-6328
3rd row02-6953-1288
4th row02-899-7825
5th row031-764-2100
ValueCountFrequency (%)
031-8078-7976 1
 
3.1%
031-912-6328 1
 
3.1%
031-796-5123 1
 
3.1%
031-532-4027 1
 
3.1%
031-663-7330 1
 
3.1%
031-949-9552 1
 
3.1%
031-631-7939 1
 
3.1%
031-850-5757 1
 
3.1%
031-427-2727 1
 
3.1%
031-335-5645 1
 
3.1%
Other values (22) 22
68.8%
2023-12-11T06:24:30.675559image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
- 64
16.6%
3 54
14.0%
0 52
13.5%
1 38
9.8%
7 32
8.3%
8 31
8.0%
2 30
7.8%
5 25
 
6.5%
6 23
 
6.0%
9 20
 
5.2%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 322
83.4%
Dash Punctuation 64
 
16.6%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
3 54
16.8%
0 52
16.1%
1 38
11.8%
7 32
9.9%
8 31
9.6%
2 30
9.3%
5 25
7.8%
6 23
7.1%
9 20
 
6.2%
4 17
 
5.3%
Dash Punctuation
ValueCountFrequency (%)
- 64
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 386
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
- 64
16.6%
3 54
14.0%
0 52
13.5%
1 38
9.8%
7 32
8.3%
8 31
8.0%
2 30
7.8%
5 25
 
6.5%
6 23
 
6.0%
9 20
 
5.2%

Most occurring blocks

ValueCountFrequency (%)
ASCII 386
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
- 64
16.6%
3 54
14.0%
0 52
13.5%
1 38
9.8%
7 32
8.3%
8 31
8.0%
2 30
7.8%
5 25
 
6.5%
6 23
 
6.0%
9 20
 
5.2%

홈페이지URL
Text

Distinct30
Distinct (%)93.8%
Missing0
Missing (%)0.0%
Memory size388.0 B
2023-12-11T06:24:30.855904image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length78
Median length31
Mean length24.84375
Min length4

Characters and Unicode

Total characters795
Distinct characters37
Distinct categories5 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique29 ?
Unique (%)90.6%

Sample

1st rowhttps://gpsports.or.kr/kpc/main
2nd rowwww.goyangdpsports.com
3rd rowwww.gcsad.or.kr
4th rowhttps://ggsports.gg.go.kr/
5th rowhttp://psgju.co.kr/
ValueCountFrequency (%)
https://ggsports.gg.go.kr 3
 
9.4%
https://gpsports.or.kr/kpc/main 1
 
3.1%
http://www.assad.co.kr 1
 
3.1%
http://www.allsports.or.kr/page/?pid=aboutus2 1
 
3.1%
www.posad.or.kr 1
 
3.1%
ptsports.or.kr 1
 
3.1%
http://icsad.co.kr 1
 
3.1%
http://ujbsports5757.or.kr 1
 
3.1%
http://uwsad.or.kr 1
 
3.1%
http://www.yisad.or.kr 1
 
3.1%
Other values (20) 20
62.5%
2023-12-11T06:24:31.377586image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
. 82
 
10.3%
/ 76
 
9.6%
t 64
 
8.1%
s 60
 
7.5%
r 59
 
7.4%
p 56
 
7.0%
o 51
 
6.4%
w 48
 
6.0%
g 37
 
4.7%
h 31
 
3.9%
Other values (27) 231
29.1%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 580
73.0%
Other Punctuation 184
 
23.1%
Decimal Number 28
 
3.5%
Math Symbol 2
 
0.3%
Uppercase Letter 1
 
0.1%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
t 64
11.0%
s 60
10.3%
r 59
10.2%
p 56
9.7%
o 51
8.8%
w 48
8.3%
g 37
 
6.4%
h 31
 
5.3%
k 29
 
5.0%
a 28
 
4.8%
Other values (13) 117
20.2%
Decimal Number
ValueCountFrequency (%)
0 7
25.0%
1 6
21.4%
2 4
14.3%
7 4
14.3%
5 3
10.7%
8 2
 
7.1%
4 1
 
3.6%
3 1
 
3.6%
Other Punctuation
ValueCountFrequency (%)
. 82
44.6%
/ 76
41.3%
: 24
 
13.0%
? 2
 
1.1%
Math Symbol
ValueCountFrequency (%)
= 2
100.0%
Uppercase Letter
ValueCountFrequency (%)
M 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 581
73.1%
Common 214
 
26.9%

Most frequent character per script

Latin
ValueCountFrequency (%)
t 64
11.0%
s 60
10.3%
r 59
10.2%
p 56
9.6%
o 51
8.8%
w 48
8.3%
g 37
 
6.4%
h 31
 
5.3%
k 29
 
5.0%
a 28
 
4.8%
Other values (14) 118
20.3%
Common
ValueCountFrequency (%)
. 82
38.3%
/ 76
35.5%
: 24
 
11.2%
0 7
 
3.3%
1 6
 
2.8%
2 4
 
1.9%
7 4
 
1.9%
5 3
 
1.4%
8 2
 
0.9%
? 2
 
0.9%
Other values (3) 4
 
1.9%

Most occurring blocks

ValueCountFrequency (%)
ASCII 795
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
. 82
 
10.3%
/ 76
 
9.6%
t 64
 
8.1%
s 60
 
7.5%
r 59
 
7.4%
p 56
 
7.0%
o 51
 
6.4%
w 48
 
6.0%
g 37
 
4.7%
h 31
 
3.9%
Other values (27) 231
29.1%

Interactions

2023-12-11T06:24:26.942098image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:24:26.510604image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:24:26.731107image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:24:27.005700image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:24:26.589950image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:24:26.800219image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:24:27.073678image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:24:26.657335image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:24:26.874289image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-11T06:24:31.454791image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
시군명기관명소재지지번주소소재지도로명주소소재지우편번호WGS84위도WGS84경도전화번호홈페이지URL
시군명1.0001.0001.0001.0001.0001.0001.0001.0000.974
기관명1.0001.0001.0001.0001.0001.0001.0001.0001.000
소재지지번주소1.0001.0001.0001.0001.0001.0001.0001.0001.000
소재지도로명주소1.0001.0001.0001.0001.0001.0001.0001.0001.000
소재지우편번호1.0001.0001.0001.0001.0000.8040.6081.0000.817
WGS84위도1.0001.0001.0001.0000.8041.0000.0001.0000.788
WGS84경도1.0001.0001.0001.0000.6080.0001.0001.0000.798
전화번호1.0001.0001.0001.0001.0001.0001.0001.0001.000
홈페이지URL0.9741.0001.0001.0000.8170.7880.7981.0001.000
2023-12-11T06:24:31.540582image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
소재지우편번호WGS84위도WGS84경도
소재지우편번호1.000-0.9070.071
WGS84위도-0.9071.000-0.105
WGS84경도0.071-0.1051.000

Missing values

2023-12-11T06:24:27.176205image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-11T06:24:27.321388image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Nullity matrix is a data-dense display which lets you quickly visually pick out patterns in data completion.

Sample

시군명기관명소재지지번주소소재지도로명주소소재지우편번호WGS84위도WGS84경도전화번호홈페이지URL
0가평군가평군장애인체육회경기도 가평군 가평읍 대곡리 316번지경기도 가평군 가평읍 문화로 1311241637.824874127.507218031-8078-7976https://gpsports.or.kr/kpc/main
1고양시고양시장애인체육회경기도 고양시 일산서구 대화동 2320번지경기도 고양시 일산서구 중앙로 16011022337.675685126.742542031-912-6328www.goyangdpsports.com
2과천시과천시장애인체육회경기도 과천시 관문동 3번지경기도 과천시 중앙로 2941383037.440255126.99698502-6953-1288www.gcsad.or.kr
3광명시광명시장애인체육회경기도 광명시 하안동 577번지경기도 광명시 오리로 7031425937.461933126.87140502-899-7825https://ggsports.gg.go.kr/
4광주시광주시장애인체육회경기도 광주시 양벌동 36-1경기도 광주시 양벌동 36-11279437.395056127.2578031-764-2100http://psgju.co.kr/
5구리시구리시장애인체육회경기도 구리시 인창동 430번지경기도 구리시 동구릉로136번길 571191537.599942127.116398031-556-4758https://blog.nave.com/grgg4758
6군포시군포시장애인체육회경기도 군포시 금정동 871번지경기도 군포시 산본로 2671586237.354281126.936402031-399-8842http://www.gpsad.or.kr
7김포시김포시장애인체육회경기도 김포시 사우동 290번지경기도 김포시 돌문로15번길 201011037.617439126.720024031-983-8689http://www.gimposports.or.kr/
8남양주시남양주시장애인체육회경기도 남양주시 이패동 산87번지경기도 남양주시 다산지금로 911224437.606839127.176618031-556-0993http://www.nyjsad.org/
9동두천시동두천시장애인체육회경기도 동두천시 탑동동 799번지경기도 동두천시 천보산로 6881136037.900817127.070502031-860-2748www.ddcsoprts.kr
시군명기관명소재지지번주소소재지도로명주소소재지우편번호WGS84위도WGS84경도전화번호홈페이지URL
22오산시오산시장애인체육회경기도 오산시 오산동 345번지경기도 오산시 오산천로 2711813137.15626127.071423031-373-6242http://ossad.co.kr
23용인시용인시장애인체육회경기도 용인시 처인구 삼가동 28-6번지경기도 용인시 처인구 동백죽전대로 611699737.249623127.165161031-335-5645http://www.yisad.or.kr/
24의왕시의왕시장애인체육회경기도 의왕시 고천동 328-10번지경기도 의왕시 시청로 961607437.350678126.96816031-427-2727http://uwsad.or.kr/
25의정부시의정부시장애인체육회경기도 의정부시 녹양동 174-1번지경기도 의정부시 체육로 901160637.757569127.029095031-850-5757http://ujbsports5757.or.kr/
26이천시이천시장애인체육회경기도 이천시 부발읍 무촌리 52번지경기도 이천시 부발읍 중부대로 16961732137.287221127.495624031-631-7939http://icsad.co.kr/
27파주시파주시장애인체육회경기도 파주시 금릉동 186-5번지경기도 파주시 중앙로 1601093337.756092126.785733031-949-9552https://ggsports.gg.go.kr/
28평택시평택시장애인체육회경기도 평택시 합정동 392번지경기도 평택시 평남로 6161790336.98852127.108255031-663-7330ptsports.or.kr
29포천시포천시장애인체육회경기도 포천시 군내면 구읍리 691번지경기도 포천시 군내면 호국로 15181115437.888475127.200548031-532-4027www.posad.or.kr
30하남시하남시장애인체육회경기도 하남시 망월동 200번지경기도 하남시 아리수로 6001291237.566737127.193786031-796-5123http://www.allsports.or.kr/page/?pid=aboutus2
31화성시화성시장애인체육회경기도 화성시 향남읍 도이리 668번지경기도 화성시 향남읍 향남로 4701858837.137863126.922411070-7784-2320http://hssad.or.kr/