Overview

Dataset statistics

Number of variables9
Number of observations61
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory4.6 KiB
Average record size in memory77.2 B

Variable types

Categorical1
Text5
Numeric3

Dataset

Description중증장애인자립생활지원센터 현황
Author경기복지재단(경기도장애인복지종합지원센터)
URLhttps://data.gg.go.kr/portal/data/service/selectServicePage.do?&infId=7HEDD5D8PYLOXHX1R65R25373284&infSeq=1

Alerts

소재지우편번호 is highly overall correlated with WGS84위도 and 1 other fieldsHigh correlation
WGS84위도 is highly overall correlated with 소재지우편번호 and 1 other fieldsHigh correlation
WGS84경도 is highly overall correlated with 시군명High correlation
시군명 is highly overall correlated with 소재지우편번호 and 2 other fieldsHigh correlation
기관명 has unique valuesUnique
WGS84위도 has unique valuesUnique
WGS84경도 has unique valuesUnique
전화번호 has unique valuesUnique

Reproduction

Analysis started2024-04-11 03:10:48.082123
Analysis finished2024-04-11 03:10:51.183177
Duration3.1 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

시군명
Categorical

HIGH CORRELATION 

Distinct30
Distinct (%)49.2%
Missing0
Missing (%)0.0%
Memory size620.0 B
고양시
6 
파주시
 
3
의정부시
 
3
김포시
 
3
용인시
 
3
Other values (25)
43 

Length

Max length4
Median length3
Mean length3.0819672
Min length3

Unique

Unique13 ?
Unique (%)21.3%

Sample

1st row가평군
2nd row가평군
3rd row고양시
4th row고양시
5th row고양시

Common Values

ValueCountFrequency (%)
고양시 6
 
9.8%
파주시 3
 
4.9%
의정부시 3
 
4.9%
김포시 3
 
4.9%
용인시 3
 
4.9%
부천시 3
 
4.9%
성남시 3
 
4.9%
수원시 3
 
4.9%
시흥시 3
 
4.9%
안산시 3
 
4.9%
Other values (20) 28
45.9%

Length

2024-04-11T12:10:51.247471image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
고양시 6
 
9.8%
의정부시 3
 
4.9%
김포시 3
 
4.9%
용인시 3
 
4.9%
부천시 3
 
4.9%
성남시 3
 
4.9%
수원시 3
 
4.9%
시흥시 3
 
4.9%
안산시 3
 
4.9%
화성시 3
 
4.9%
Other values (20) 28
45.9%

기관명
Text

UNIQUE 

Distinct61
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size620.0 B
2024-04-11T12:10:51.443503image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length28
Median length19
Mean length12.885246
Min length9

Characters and Unicode

Total characters786
Distinct characters112
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

Unique61 ?
Unique (%)100.0%

Sample

1st row가평군장애인자립생활지원센터
2nd row열린가평장애인자립생활센터
3rd row고양시장애인자립생활지원센터
4th row아람장애인자립생활지원센터
5th row일산사랑장애인자립생활센터
ValueCountFrequency (%)
의정부장애인자립생활센터 2
 
3.2%
의정부세움자립생활센터 1
 
1.6%
안산장애인자립생활센터 1
 
1.6%
밀알장애인자립생활센터 1
 
1.6%
안양시장애인자립생활센터 1
 
1.6%
디딤돌장애인자립생활센터 1
 
1.6%
양주시장애인자립생활센터 1
 
1.6%
양평장애인자립생활센터 1
 
1.6%
여주시장애인자립생활지원센터 1
 
1.6%
연천장애인자립생활센터 1
 
1.6%
Other values (52) 52
82.5%
2024-04-11T12:10:51.780983image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
터 63
 
8.0%
자 62
 
7.9%
활 61
 
7.8%
센 61
 
7.8%
인 61
 
7.8%
립 61
 
7.8%
생 61
 
7.8%
장 58
 
7.4%
애 58
 
7.4%
시 17
 
2.2%
Other values (102) 223
28.4%

Most occurring categories

ValueCountFrequency (%)
Other Letter 780
99.2%
Close Punctuation 2
 
0.3%
Open Punctuation 2
 
0.3%
Space Separator 2
 
0.3%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
터 63
 
8.1%
자 62
 
7.9%
활 61
 
7.8%
센 61
 
7.8%
인 61
 
7.8%
립 61
 
7.8%
생 61
 
7.8%
장 58
 
7.4%
애 58
 
7.4%
시 17
 
2.2%
Other values (99) 217
27.8%
Close Punctuation
ValueCountFrequency (%)
) 2
100.0%
Open Punctuation
ValueCountFrequency (%)
( 2
100.0%
Space Separator
ValueCountFrequency (%)
2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 780
99.2%
Common 6
 
0.8%

Most frequent character per script

Hangul
ValueCountFrequency (%)
터 63
 
8.1%
자 62
 
7.9%
활 61
 
7.8%
센 61
 
7.8%
인 61
 
7.8%
립 61
 
7.8%
생 61
 
7.8%
장 58
 
7.4%
애 58
 
7.4%
시 17
 
2.2%
Other values (99) 217
27.8%
Common
ValueCountFrequency (%)
) 2
33.3%
( 2
33.3%
2
33.3%

Most occurring blocks

ValueCountFrequency (%)
Hangul 780
99.2%
ASCII 6
 
0.8%

Most frequent character per block

Hangul
ValueCountFrequency (%)
터 63
 
8.1%
자 62
 
7.9%
활 61
 
7.8%
센 61
 
7.8%
인 61
 
7.8%
립 61
 
7.8%
생 61
 
7.8%
장 58
 
7.4%
애 58
 
7.4%
시 17
 
2.2%
Other values (99) 217
27.8%
ASCII
ValueCountFrequency (%)
) 2
33.3%
( 2
33.3%
2
33.3%

소재지지번주소
Text

Distinct60
Distinct (%)98.4%
Missing0
Missing (%)0.0%
Memory size620.0 B
2024-04-11T12:10:52.036285image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length25
Median length23
Mean length20.770492
Min length16

Characters and Unicode

Total characters1267
Distinct characters124
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

Unique59 ?
Unique (%)96.7%

Sample

1st row경기도 가평군 가평읍 대곡리 316번지
2nd row경기도 가평군 청평면 청평리 80-5번지
3rd row경기도 고양시 일산서구 주엽동 72-2번지
4th row경기도 고양시 일산동구 장항동 856-3번지
5th row경기도 고양시 일산동구 중산동 7번지
ValueCountFrequency (%)
경기도 61
 
22.1%
고양시 6
 
2.2%
수원시 3
 
1.1%
용인시 3
 
1.1%
안산시 3
 
1.1%
화성시 3
 
1.1%
시흥시 3
 
1.1%
일산동구 3
 
1.1%
주엽동 3
 
1.1%
일산서구 3
 
1.1%
Other values (158) 185
67.0%
2024-04-11T12:10:52.397189image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
215
 
17.0%
기 64
 
5.1%
도 62
 
4.9%
경 61
 
4.8%
지 61
 
4.8%
번 61
 
4.8%
시 60
 
4.7%
동 57
 
4.5%
1 43
 
3.4%
- 43
 
3.4%
Other values (114) 540
42.6%

Most occurring categories

ValueCountFrequency (%)
Other Letter 772
60.9%
Decimal Number 237
 
18.7%
Space Separator 215
 
17.0%
Dash Punctuation 43
 
3.4%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
기 64
 
8.3%
도 62
 
8.0%
경 61
 
7.9%
지 61
 
7.9%
번 61
 
7.9%
시 60
 
7.8%
동 57
 
7.4%
구 24
 
3.1%
산 15
 
1.9%
양 15
 
1.9%
Other values (102) 292
37.8%
Decimal Number
ValueCountFrequency (%)
1 43
18.1%
3 34
14.3%
2 30
12.7%
7 29
12.2%
5 23
9.7%
8 20
8.4%
6 20
8.4%
4 18
7.6%
0 12
 
5.1%
9 8
 
3.4%
Space Separator
ValueCountFrequency (%)
215
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 43
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 772
60.9%
Common 495
39.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
기 64
 
8.3%
도 62
 
8.0%
경 61
 
7.9%
지 61
 
7.9%
번 61
 
7.9%
시 60
 
7.8%
동 57
 
7.4%
구 24
 
3.1%
산 15
 
1.9%
양 15
 
1.9%
Other values (102) 292
37.8%
Common
ValueCountFrequency (%)
215
43.4%
1 43
 
8.7%
- 43
 
8.7%
3 34
 
6.9%
2 30
 
6.1%
7 29
 
5.9%
5 23
 
4.6%
8 20
 
4.0%
6 20
 
4.0%
4 18
 
3.6%
Other values (2) 20
 
4.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 772
60.9%
ASCII 495
39.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
215
43.4%
1 43
 
8.7%
- 43
 
8.7%
3 34
 
6.9%
2 30
 
6.1%
7 29
 
5.9%
5 23
 
4.6%
8 20
 
4.0%
6 20
 
4.0%
4 18
 
3.6%
Other values (2) 20
 
4.0%
Hangul
ValueCountFrequency (%)
기 64
 
8.3%
도 62
 
8.0%
경 61
 
7.9%
지 61
 
7.9%
번 61
 
7.9%
시 60
 
7.8%
동 57
 
7.4%
구 24
 
3.1%
산 15
 
1.9%
양 15
 
1.9%
Other values (102) 292
37.8%

소재지도로명주소
Text

Distinct60
Distinct (%)98.4%
Missing0
Missing (%)0.0%
Memory size620.0 B
2024-04-11T12:10:52.636968image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length24
Median length21
Mean length18.819672
Min length14

Characters and Unicode

Total characters1148
Distinct characters126
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

Unique59 ?
Unique (%)96.7%

Sample

1st row경기도 가평군 가평읍 문화로 131
2nd row경기도 가평군 청평면 강변로 31-18
3rd row경기도 고양시 일산서구 중앙로 1406
4th row경기도 고양시 일산동구 정발산로 33
5th row경기도 고양시 일산동구 성석로 48
ValueCountFrequency (%)
경기도 61
 
22.1%
고양시 6
 
2.2%
중앙로 4
 
1.4%
시흥시 3
 
1.1%
수원시 3
 
1.1%
용인시 3
 
1.1%
성남시 3
 
1.1%
원미구 3
 
1.1%
부천시 3
 
1.1%
안산시 3
 
1.1%
Other values (156) 184
66.7%
2024-04-11T12:10:52.985284image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
215
18.7%
기 64
 
5.6%
경 63
 
5.5%
도 62
 
5.4%
시 60
 
5.2%
로 57
 
5.0%
1 48
 
4.2%
3 25
 
2.2%
구 24
 
2.1%
4 24
 
2.1%
Other values (116) 506
44.1%

Most occurring categories

ValueCountFrequency (%)
Other Letter 722
62.9%
Space Separator 215
 
18.7%
Decimal Number 207
 
18.0%
Dash Punctuation 4
 
0.3%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
기 64
 
8.9%
경 63
 
8.7%
도 62
 
8.6%
시 60
 
8.3%
로 57
 
7.9%
구 24
 
3.3%
길 21
 
2.9%
번 17
 
2.4%
천 15
 
2.1%
산 13
 
1.8%
Other values (104) 326
45.2%
Decimal Number
ValueCountFrequency (%)
1 48
23.2%
3 25
12.1%
4 24
11.6%
9 21
10.1%
5 19
 
9.2%
6 17
 
8.2%
2 17
 
8.2%
0 16
 
7.7%
8 11
 
5.3%
7 9
 
4.3%
Space Separator
ValueCountFrequency (%)
215
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 4
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 722
62.9%
Common 426
37.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
기 64
 
8.9%
경 63
 
8.7%
도 62
 
8.6%
시 60
 
8.3%
로 57
 
7.9%
구 24
 
3.3%
길 21
 
2.9%
번 17
 
2.4%
천 15
 
2.1%
산 13
 
1.8%
Other values (104) 326
45.2%
Common
ValueCountFrequency (%)
215
50.5%
1 48
 
11.3%
3 25
 
5.9%
4 24
 
5.6%
9 21
 
4.9%
5 19
 
4.5%
6 17
 
4.0%
2 17
 
4.0%
0 16
 
3.8%
8 11
 
2.6%
Other values (2) 13
 
3.1%

Most occurring blocks

ValueCountFrequency (%)
Hangul 722
62.9%
ASCII 426
37.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
215
50.5%
1 48
 
11.3%
3 25
 
5.9%
4 24
 
5.6%
9 21
 
4.9%
5 19
 
4.5%
6 17
 
4.0%
2 17
 
4.0%
0 16
 
3.8%
8 11
 
2.6%
Other values (2) 13
 
3.1%
Hangul
ValueCountFrequency (%)
기 64
 
8.9%
경 63
 
8.7%
도 62
 
8.6%
시 60
 
8.3%
로 57
 
7.9%
구 24
 
3.3%
길 21
 
2.9%
번 17
 
2.4%
천 15
 
2.1%
산 13
 
1.8%
Other values (104) 326
45.2%

소재지우편번호
Real number (ℝ)

HIGH CORRELATION 

Distinct59
Distinct (%)96.7%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean13625.934
Minimum10032
Maximum18537
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size681.0 B
2024-04-11T12:10:53.125544image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum10032
5-th percentile10319
Q111329
median13337
Q315494
95-th percentile18123
Maximum18537
Range8505
Interquartile range (IQR)4165

Descriptive statistics

Standard deviation2601.0764
Coefficient of variation (CV)0.1908916
Kurtosis-1.1176449
Mean13625.934
Median Absolute Deviation (MAD)2157
Skewness0.34092914
Sum831182
Variance6765598.5
MonotonicityNot monotonic
2024-04-11T12:10:53.259323image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
10387 2
 
3.3%
14995 2
 
3.3%
12416 1
 
1.6%
11813 1
 
1.6%
11509 1
 
1.6%
11492 1
 
1.6%
12553 1
 
1.6%
12629 1
 
1.6%
11031 1
 
1.6%
18123 1
 
1.6%
Other values (49) 49
80.3%
ValueCountFrequency (%)
10032 1
1.6%
10083 1
1.6%
10111 1
1.6%
10319 1
1.6%
10386 1
1.6%
10387 2
3.3%
10401 1
1.6%
10402 1
1.6%
10896 1
1.6%
10922 1
1.6%
ValueCountFrequency (%)
18537 1
1.6%
18467 1
1.6%
18412 1
1.6%
18123 1
1.6%
17907 1
1.6%
17373 1
1.6%
17350 1
1.6%
17153 1
1.6%
17006 1
1.6%
16995 1
1.6%

WGS84위도
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct61
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean37.506471
Minimum36.991527
Maximum38.015144
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size681.0 B
2024-04-11T12:10:53.386887image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum36.991527
5-th percentile37.20691
Q137.310176
median37.489509
Q337.683975
95-th percentile37.902987
Maximum38.015144
Range1.0236166
Interquartile range (IQR)0.37379945

Descriptive statistics

Standard deviation0.22836284
Coefficient of variation (CV)0.0060886252
Kurtosis-0.79306567
Mean37.506471
Median Absolute Deviation (MAD)0.18162543
Skewness0.17590137
Sum2287.8947
Variance0.052149589
MonotonicityNot monotonic
2024-04-11T12:10:53.510427image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
37.82549149 1
 
1.6%
37.75195377 1
 
1.6%
37.402715 1
 
1.6%
37.38684777 1
 
1.6%
37.79503101 1
 
1.6%
37.79468347 1
 
1.6%
37.491664 1
 
1.6%
37.291684 1
 
1.6%
38.01514362 1
 
1.6%
37.16375765 1
 
1.6%
Other values (51) 51
83.6%
ValueCountFrequency (%)
36.991527 1
1.6%
37.16375765 1
1.6%
37.201549 1
1.6%
37.20690956 1
1.6%
37.21175857 1
1.6%
37.23722241 1
1.6%
37.2425951 1
1.6%
37.26054451 1
1.6%
37.27020333 1
1.6%
37.271271 1
1.6%
ValueCountFrequency (%)
38.01514362 1
1.6%
37.93739621 1
1.6%
37.90481488 1
1.6%
37.90298671 1
1.6%
37.82549149 1
1.6%
37.79503101 1
1.6%
37.79468347 1
1.6%
37.754459 1
1.6%
37.75195377 1
1.6%
37.74639049 1
1.6%

WGS84경도
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct61
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean127.00787
Minimum126.60041
Maximum127.64106
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size681.0 B
2024-04-11T12:10:53.634190image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum126.60041
5-th percentile126.74128
Q1126.79174
median127.00723
Q3127.13932
95-th percentile127.45826
Maximum127.64106
Range1.0406531
Interquartile range (IQR)0.3475798

Descriptive statistics

Standard deviation0.2317788
Coefficient of variation (CV)0.0018249167
Kurtosis0.012269271
Mean127.00787
Median Absolute Deviation (MAD)0.184639
Skewness0.62854452
Sum7747.4803
Variance0.05372141
MonotonicityNot monotonic
2024-04-11T12:10:53.755822image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
127.5070577 1
 
1.6%
127.068442 1
 
1.6%
126.9500835 1
 
1.6%
126.9317289 1
 
1.6%
126.990917 1
 
1.6%
127.0778934 1
 
1.6%
127.488781 1
 
1.6%
127.641065 1
 
1.6%
127.0711184 1
 
1.6%
127.0537091 1
 
1.6%
Other values (51) 51
83.6%
ValueCountFrequency (%)
126.6004119 1
1.6%
126.6677667 1
1.6%
126.7208962 1
1.6%
126.7412839 1
1.6%
126.752167 1
1.6%
126.7551166 1
1.6%
126.7585232 1
1.6%
126.7591607 1
1.6%
126.7637766 1
1.6%
126.7638789 1
1.6%
ValueCountFrequency (%)
127.641065 1
1.6%
127.5070577 1
1.6%
127.488781 1
1.6%
127.4582599 1
1.6%
127.449167 1
1.6%
127.4171022 1
1.6%
127.2443482 1
1.6%
127.2199336 1
1.6%
127.2104702 1
1.6%
127.2076848 1
1.6%

전화번호
Text

UNIQUE 

Distinct61
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size620.0 B
2024-04-11T12:10:53.977559image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length14
Median length12
Mean length12.081967
Min length11

Characters and Unicode

Total characters737
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

Unique61 ?
Unique (%)100.0%

Sample

1st row031-582-0585
2nd row031-584-4255
3rd row031-911-8080
4th row031-908-7712
5th row031-927-9945
ValueCountFrequency (%)
031-582-0585 1
 
1.6%
031-407-8173 1
 
1.6%
070-4204-5515 1
 
1.6%
031-444-0440 1
 
1.6%
031-847-3431 1
 
1.6%
031-841-6121 1
 
1.6%
031-775-6672 1
 
1.6%
031-885-0748 1
 
1.6%
031-832-9711 1
 
1.6%
031-377-1145 1
 
1.6%
Other values (51) 51
83.6%
2024-04-11T12:10:54.313724image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
- 122
16.6%
0 116
15.7%
3 98
13.3%
1 88
11.9%
4 54
7.3%
7 53
7.2%
2 50
6.8%
5 48
 
6.5%
8 43
 
5.8%
9 41
 
5.6%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 615
83.4%
Dash Punctuation 122
 
16.6%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 116
18.9%
3 98
15.9%
1 88
14.3%
4 54
8.8%
7 53
8.6%
2 50
8.1%
5 48
7.8%
8 43
 
7.0%
9 41
 
6.7%
6 24
 
3.9%
Dash Punctuation
ValueCountFrequency (%)
- 122
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 737
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
- 122
16.6%
0 116
15.7%
3 98
13.3%
1 88
11.9%
4 54
7.3%
7 53
7.2%
2 50
6.8%
5 48
 
6.5%
8 43
 
5.8%
9 41
 
5.6%

Most occurring blocks

ValueCountFrequency (%)
ASCII 737
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
- 122
16.6%
0 116
15.7%
3 98
13.3%
1 88
11.9%
4 54
7.3%
7 53
7.2%
2 50
6.8%
5 48
 
6.5%
8 43
 
5.8%
9 41
 
5.6%

홈페이지URL
Text

Distinct60
Distinct (%)98.4%
Missing0
Missing (%)0.0%
Memory size620.0 B
2024-04-11T12:10:54.514684image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length37
Median length29
Mean length25.032787
Min length8

Characters and Unicode

Total characters1527
Distinct characters39
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique59 ?
Unique (%)96.7%

Sample

1st rowhttps://blog.naver.com/gpil2020
2nd rowhttps://cafe.daum.net/gpcil
3rd rowhttp://cafe.daum.net/GcIL
4th rowhttp://aramcil.com/new/
5th rowhttps://blog.naver.com/ilsanlove7
ValueCountFrequency (%)
https 2
 
3.3%
https://blog.naver.com/gpil2020 1
 
1.6%
http://yjil.kr 1
 
1.6%
http://uwilc.com 1
 
1.6%
http://cafe.daum.net/ascil 1
 
1.6%
http://www.mcil.co.kr 1
 
1.6%
http://www.aycil.org 1
 
1.6%
https://cafe.naver.com/dddcil 1
 
1.6%
http://yjcil.or.kr 1
 
1.6%
https://cafe.daum.net/ypcil 1
 
1.6%
Other values (50) 50
82.0%
2024-04-11T12:10:54.837390image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
/ 172
 
11.3%
t 141
 
9.2%
. 127
 
8.3%
o 77
 
5.0%
c 76
 
5.0%
w 73
 
4.8%
p 70
 
4.6%
a 69
 
4.5%
h 65
 
4.3%
e 65
 
4.3%
Other values (29) 592
38.8%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 1142
74.8%
Other Punctuation 355
 
23.2%
Decimal Number 17
 
1.1%
Uppercase Letter 13
 
0.9%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
t 141
 
12.3%
o 77
 
6.7%
c 76
 
6.7%
w 73
 
6.4%
p 70
 
6.1%
a 69
 
6.0%
h 65
 
5.7%
e 65
 
5.7%
r 62
 
5.4%
l 56
 
4.9%
Other values (14) 388
34.0%
Decimal Number
ValueCountFrequency (%)
0 5
29.4%
2 4
23.5%
4 3
17.6%
7 1
 
5.9%
8 1
 
5.9%
9 1
 
5.9%
6 1
 
5.9%
1 1
 
5.9%
Uppercase Letter
ValueCountFrequency (%)
I 5
38.5%
L 5
38.5%
G 2
 
15.4%
C 1
 
7.7%
Other Punctuation
ValueCountFrequency (%)
/ 172
48.5%
. 127
35.8%
: 56
 
15.8%

Most occurring scripts

ValueCountFrequency (%)
Latin 1155
75.6%
Common 372
 
24.4%

Most frequent character per script

Latin
ValueCountFrequency (%)
t 141
 
12.2%
o 77
 
6.7%
c 76
 
6.6%
w 73
 
6.3%
p 70
 
6.1%
a 69
 
6.0%
h 65
 
5.6%
e 65
 
5.6%
r 62
 
5.4%
l 56
 
4.8%
Other values (18) 401
34.7%
Common
ValueCountFrequency (%)
/ 172
46.2%
. 127
34.1%
: 56
 
15.1%
0 5
 
1.3%
2 4
 
1.1%
4 3
 
0.8%
7 1
 
0.3%
8 1
 
0.3%
9 1
 
0.3%
6 1
 
0.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1527
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
/ 172
 
11.3%
t 141
 
9.2%
. 127
 
8.3%
o 77
 
5.0%
c 76
 
5.0%
w 73
 
4.8%
p 70
 
4.6%
a 69
 
4.5%
h 65
 
4.3%
e 65
 
4.3%
Other values (29) 592
38.8%

Interactions

2024-04-11T12:10:50.731541image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-11T12:10:50.218458image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-11T12:10:50.498787image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-11T12:10:50.803343image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-11T12:10:50.337204image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-11T12:10:50.577746image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-11T12:10:50.876934image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-11T12:10:50.420315image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-11T12:10:50.659464image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-04-11T12:10:54.927461image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
시군명기관명소재지지번주소소재지도로명주소소재지우편번호WGS84위도WGS84경도전화번호홈페이지URL
시군명1.0001.0001.0001.0000.9990.9970.9911.0000.994
기관명1.0001.0001.0001.0001.0001.0001.0001.0001.000
소재지지번주소1.0001.0001.0001.0001.0001.0001.0001.0000.998
소재지도로명주소1.0001.0001.0001.0001.0001.0001.0001.0000.998
소재지우편번호0.9991.0001.0001.0001.0000.9100.8721.0000.921
WGS84위도0.9971.0001.0001.0000.9101.0000.6241.0000.897
WGS84경도0.9911.0001.0001.0000.8720.6241.0001.0000.986
전화번호1.0001.0001.0001.0001.0001.0001.0001.0001.000
홈페이지URL0.9941.0000.9980.9980.9210.8970.9861.0001.000
2024-04-11T12:10:55.051806image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
소재지우편번호WGS84위도WGS84경도시군명
소재지우편번호1.000-0.8760.2860.742
WGS84위도-0.8761.000-0.1080.703
WGS84경도0.286-0.1081.0000.654
시군명0.7420.7030.6541.000

Missing values

2024-04-11T12:10:50.984866image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-04-11T12:10:51.129093image/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
0가평군가평군장애인자립생활지원센터경기도 가평군 가평읍 대곡리 316번지경기도 가평군 가평읍 문화로 1311241637.825491127.507058031-582-0585https://blog.naver.com/gpil2020
1가평군열린가평장애인자립생활센터경기도 가평군 청평면 청평리 80-5번지경기도 가평군 청평면 강변로 31-181245337.734664127.417102031-584-4255https://cafe.daum.net/gpcil
2고양시고양시장애인자립생활지원센터경기도 고양시 일산서구 주엽동 72-2번지경기도 고양시 일산서구 중앙로 14061038637.669381126.763879031-911-8080http://cafe.daum.net/GcIL
3고양시아람장애인자립생활지원센터경기도 고양시 일산동구 장항동 856-3번지경기도 고양시 일산동구 정발산로 331040237.657168126.772559031-908-7712http://aramcil.com/new/
4고양시일산사랑장애인자립생활센터경기도 고양시 일산동구 중산동 7번지경기도 고양시 일산동구 성석로 481031937.684387126.791743031-927-9945https://blog.naver.com/ilsanlove7
5고양시일산서구햇빛촌장애인자립생활지원센터경기도 고양시 일산서구 주엽동 115번지경기도 고양시 일산서구 중앙로 14551038737.670897126.758523031-918-7377http://cafe.daum.net/djdnfjrltnlaxj
6고양시일산장애인자립생활지원센터경기도 고양시 일산동구 장항동 778-2번지경기도 고양시 일산동구 무궁화로 341040137.662622126.768379031-906-3095http://www.ggableforum.or.kr/main.php
7고양시즐거운장애인자립생활지원센터경기도 고양시 일산서구 주엽동 110번지경기도 고양시 일산서구 중앙로 14491038737.67064126.759161031-914-0423http://www.funilct.or.kr/
8과천시울림터과천시장애인자립생활센터경기도 과천시 문원동 15-11번지경기도 과천시 공원마을1길 541382837.430247127.00247802-503-9412http://wgcil.co.kr/
9광명시광명장애인자립생활센터경기도 광명시 소하동 1338-2번지경기도 광명시 소하로109번길 151431637.447289126.88498102-897-7008http://gmcil2008.co.kr/
시군명기관명소재지지번주소소재지도로명주소소재지우편번호WGS84위도WGS84경도전화번호홈페이지URL
51파주시파주자유로장애인자립생활센터경기도 파주시 와동동 1523-6번지경기도 파주시 가람로116번길 311089637.735924126.763777031-945-1305https://freewaycil.modoo.at/
52파주시파주장애인자립생활센터경기도 파주시 금릉동 211-11번지경기도 파주시 중앙로 1931092237.754459126.781949031-953-3763https://www.pajucil.kr/default/
53평택시에바다장애인자립생활지원센터경기도 평택시 합정동 762-7번지경기도 평택시 평택4로 391790736.991527127.100076031-652-6975http://www.eptcil.kr/
54포천시포천나눔의집장애인자립생활센터경기도 포천시 신읍동 210-17번지경기도 포천시 중앙로197번길 171114437.902987127.206016031-531-2023https://cafe.daum.net/pcnanumIL
55포천시포천장애인자립생활센터경기도 포천시 신북면 신평리 605-2번지경기도 포천시 신북면 청신로 20721113837.937396127.219934031-531-6368https://cafe.daum.net/pochonIL
56하남시미사강변장애인자립생활센터경기도 하남시 망월동 1100번지경기도 하남시 미사강변동로 951291337.563091127.191871031-795-0420https://
57하남시하남장애인자립생활센터경기도 하남시 신장동 432-33번지경기도 하남시 신장로 941295937.537114127.207685031-791-7006http://hnil.co.kr/
58화성시화성동부장애인자립생활센터경기도 화성시 병점동 381-17번지경기도 화성시 경기대로 1025-51841237.20691127.035356031-233-0420http://www.hsil2014.com/
59화성시화성동탄장애인자립생활센터경기도 화성시 영천동 878-3번지경기도 화성시 동탄영천로 1011846737.211759127.1028610507-1410-0547https://
60화성시화성서남부장애인자립생활지원센터경기도 화성시 마도면 두곡리 495-19번지경기도 화성시 마도면 화성로 9441853737.201549126.790585031-355-1167https://cafe.daum.net/rgbdaum.net