Overview

Dataset statistics

Number of variables10
Number of observations53
Missing cells37
Missing cells (%)7.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory4.5 KiB
Average record size in memory87.5 B

Variable types

Categorical2
Text3
Numeric5

Dataset

Description성폭력피해상담소 현황
Author행정안전부
URLhttps://data.gg.go.kr/portal/data/service/selectServicePage.do?&infId=IO7N2A0LEPRZIG7XBBZ013966376&infSeq=1

Alerts

폐업일자 is highly overall correlated with 영업상태명High correlation
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
영업상태명 is highly overall correlated with 폐업일자High correlation
폐업일자 has 31 (58.5%) missing valuesMissing
소재지도로명주소 has 4 (7.5%) missing valuesMissing
소재지우편번호 has 2 (3.8%) missing valuesMissing

Reproduction

Analysis started2023-12-10 22:32:48.900772
Analysis finished2023-12-10 22:32:52.489722
Duration3.59 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

시군명
Categorical

HIGH CORRELATION 

Distinct26
Distinct (%)49.1%
Missing0
Missing (%)0.0%
Memory size556.0 B
수원시
6 
부천시
6 
고양시
5 
남양주시
 
3
화성시
 
3
Other values (21)
30 

Length

Max length4
Median length3
Mean length3.1320755
Min length3

Unique

Unique12 ?
Unique (%)22.6%

Sample

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

Common Values

ValueCountFrequency (%)
수원시 6
 
11.3%
부천시 6
 
11.3%
고양시 5
 
9.4%
남양주시 3
 
5.7%
화성시 3
 
5.7%
시흥시 2
 
3.8%
파주시 2
 
3.8%
안양시 2
 
3.8%
안산시 2
 
3.8%
용인시 2
 
3.8%
Other values (16) 20
37.7%

Length

2023-12-11T07:32:52.553108image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
수원시 6
 
11.3%
부천시 6
 
11.3%
고양시 5
 
9.4%
남양주시 3
 
5.7%
화성시 3
 
5.7%
용인시 2
 
3.8%
동두천시 2
 
3.8%
구리시 2
 
3.8%
포천시 2
 
3.8%
의정부시 2
 
3.8%
Other values (16) 20
37.7%

사업장명
Text

Distinct51
Distinct (%)96.2%
Missing0
Missing (%)0.0%
Memory size556.0 B
2023-12-11T07:32:52.784595image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length29
Median length21
Mean length11.698113
Min length6

Characters and Unicode

Total characters620
Distinct characters116
Distinct categories6 ?
Distinct scripts3 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique49 ?
Unique (%)92.5%

Sample

1st row일산가족상담센터
2nd row고양로뎀성폭력상담소
3rd row(사)고양여성민우회 성폭력상담소
4th row한마음가족상담센터
5th row로뎀성폭력상담소
ValueCountFrequency (%)
성폭력상담소 7
 
7.6%
부설 5
 
5.4%
상담센터 3
 
3.3%
상담소 3
 
3.3%
구리성폭력상담소 2
 
2.2%
사단법인 2
 
2.2%
동두천성폭력상담소 2
 
2.2%
성폭력 2
 
2.2%
용인성폭력상담소 1
 
1.1%
정다운 1
 
1.1%
Other values (64) 64
69.6%
2023-12-11T07:32:53.197387image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
상 54
 
8.7%
담 54
 
8.7%
성 50
 
8.1%
소 40
 
6.5%
39
 
6.3%
폭 33
 
5.3%
력 33
 
5.3%
부 16
 
2.6%
터 15
 
2.4%
센 15
 
2.4%
Other values (106) 271
43.7%

Most occurring categories

ValueCountFrequency (%)
Other Letter 556
89.7%
Space Separator 39
 
6.3%
Uppercase Letter 15
 
2.4%
Open Punctuation 4
 
0.6%
Close Punctuation 4
 
0.6%
Other Punctuation 2
 
0.3%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
상 54
 
9.7%
담 54
 
9.7%
성 50
 
9.0%
소 40
 
7.2%
폭 33
 
5.9%
력 33
 
5.9%
부 16
 
2.9%
터 15
 
2.7%
센 15
 
2.7%
설 10
 
1.8%
Other values (97) 236
42.4%
Uppercase Letter
ValueCountFrequency (%)
C 5
33.3%
Y 4
26.7%
A 3
20.0%
W 3
20.0%
Other Punctuation
ValueCountFrequency (%)
, 1
50.0%
· 1
50.0%
Space Separator
ValueCountFrequency (%)
39
100.0%
Open Punctuation
ValueCountFrequency (%)
( 4
100.0%
Close Punctuation
ValueCountFrequency (%)
) 4
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 556
89.7%
Common 49
 
7.9%
Latin 15
 
2.4%

Most frequent character per script

Hangul
ValueCountFrequency (%)
상 54
 
9.7%
담 54
 
9.7%
성 50
 
9.0%
소 40
 
7.2%
폭 33
 
5.9%
력 33
 
5.9%
부 16
 
2.9%
터 15
 
2.7%
센 15
 
2.7%
설 10
 
1.8%
Other values (97) 236
42.4%
Common
ValueCountFrequency (%)
39
79.6%
( 4
 
8.2%
) 4
 
8.2%
, 1
 
2.0%
· 1
 
2.0%
Latin
ValueCountFrequency (%)
C 5
33.3%
Y 4
26.7%
A 3
20.0%
W 3
20.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 556
89.7%
ASCII 63
 
10.2%
None 1
 
0.2%

Most frequent character per block

Hangul
ValueCountFrequency (%)
상 54
 
9.7%
담 54
 
9.7%
성 50
 
9.0%
소 40
 
7.2%
폭 33
 
5.9%
력 33
 
5.9%
부 16
 
2.9%
터 15
 
2.7%
센 15
 
2.7%
설 10
 
1.8%
Other values (97) 236
42.4%
ASCII
ValueCountFrequency (%)
39
61.9%
C 5
 
7.9%
Y 4
 
6.3%
( 4
 
6.3%
) 4
 
6.3%
A 3
 
4.8%
W 3
 
4.8%
, 1
 
1.6%
None
ValueCountFrequency (%)
· 1
100.0%

인허가일자
Real number (ℝ)

Distinct51
Distinct (%)96.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean20067593
Minimum19950810
Maximum20170712
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size609.0 B
2023-12-11T07:32:53.351747image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum19950810
5-th percentile19981040
Q120030507
median20070820
Q320100511
95-th percentile20160218
Maximum20170712
Range219902
Interquartile range (IQR)70004

Descriptive statistics

Standard deviation51516.08
Coefficient of variation (CV)0.002567128
Kurtosis-0.4478624
Mean20067593
Median Absolute Deviation (MAD)30390
Skewness-0.078432286
Sum1.0635824 × 109
Variance2.6539065 × 109
MonotonicityNot monotonic
2023-12-11T07:32:53.503308image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
20080721 2
 
3.8%
20110708 2
 
3.8%
20110224 1
 
1.9%
20050415 1
 
1.9%
20090212 1
 
1.9%
19981126 1
 
1.9%
20051125 1
 
1.9%
19980512 1
 
1.9%
20070501 1
 
1.9%
20050713 1
 
1.9%
Other values (41) 41
77.4%
ValueCountFrequency (%)
19950810 1
1.9%
19980512 1
1.9%
19980910 1
1.9%
19981126 1
1.9%
19990830 1
1.9%
20000315 1
1.9%
20001215 1
1.9%
20010416 1
1.9%
20011114 1
1.9%
20020109 1
1.9%
ValueCountFrequency (%)
20170712 1
1.9%
20161017 1
1.9%
20160222 1
1.9%
20160216 1
1.9%
20140828 1
1.9%
20140304 1
1.9%
20110708 2
3.8%
20110224 1
1.9%
20110119 1
1.9%
20110110 1
1.9%

영업상태명
Categorical

HIGH CORRELATION 

Distinct2
Distinct (%)3.8%
Missing0
Missing (%)0.0%
Memory size556.0 B
운영중
31 
폐업 등
22 

Length

Max length4
Median length3
Mean length3.4150943
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row운영중
2nd row운영중
3rd row운영중
4th row운영중
5th row폐업 등

Common Values

ValueCountFrequency (%)
운영중 31
58.5%
폐업 등 22
41.5%

Length

2023-12-11T07:32:53.625551image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T07:32:53.715608image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
운영중 31
41.3%
폐업 22
29.3%
등 22
29.3%

폐업일자
Real number (ℝ)

HIGH CORRELATION  MISSING 

Distinct20
Distinct (%)90.9%
Missing31
Missing (%)58.5%
Infinite0
Infinite (%)0.0%
Mean20115191
Minimum20070830
Maximum20160203
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size609.0 B
2023-12-11T07:32:53.805508image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum20070830
5-th percentile20081095
Q120100746
median20120515
Q320130842
95-th percentile20149804
Maximum20160203
Range89373
Interquartile range (IQR)30096.75

Descriptive statistics

Standard deviation23131.103
Coefficient of variation (CV)0.0011499321
Kurtosis-0.60762751
Mean20115191
Median Absolute Deviation (MAD)19555
Skewness0.017378376
Sum4.425342 × 108
Variance5.3504793 × 108
MonotonicityNot monotonic
2023-12-11T07:32:53.931201image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=20)
ValueCountFrequency (%)
20140211 2
 
3.8%
20101101 2
 
3.8%
20080620 1
 
1.9%
20070830 1
 
1.9%
20090123 1
 
1.9%
20160203 1
 
1.9%
20150309 1
 
1.9%
20121101 1
 
1.9%
20100813 1
 
1.9%
20100723 1
 
1.9%
Other values (10) 10
 
18.9%
(Missing) 31
58.5%
ValueCountFrequency (%)
20070830 1
1.9%
20080620 1
1.9%
20090123 1
1.9%
20090303 1
1.9%
20100531 1
1.9%
20100723 1
1.9%
20100813 1
1.9%
20101101 2
3.8%
20101103 1
1.9%
20120223 1
1.9%
ValueCountFrequency (%)
20160203 1
1.9%
20150309 1
1.9%
20140211 2
3.8%
20131231 1
1.9%
20131016 1
1.9%
20130321 1
1.9%
20130111 1
1.9%
20121213 1
1.9%
20121101 1
1.9%
20120807 1
1.9%

소재지도로명주소
Text

MISSING 

Distinct48
Distinct (%)98.0%
Missing4
Missing (%)7.5%
Memory size556.0 B
2023-12-11T07:32:54.191497image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length46
Median length37
Mean length26.183673
Min length14

Characters and Unicode

Total characters1283
Distinct characters158
Distinct categories7 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique47 ?
Unique (%)95.9%

Sample

1st row경기도 고양시 일산동구 중앙로 1172
2nd row경기도 고양시 덕양구 고양시청로 19
3rd row경기도 고양시 일산동구 무궁화로 32-21
4th row경기도 고양시 덕양구 용현로 9
5th row경기도 고양시 덕양구 고양시청로 19
ValueCountFrequency (%)
경기도 49
 
18.1%
수원시 5
 
1.8%
부천시 5
 
1.8%
고양시 5
 
1.8%
3층 4
 
1.5%
덕양구 3
 
1.1%
남양주시 3
 
1.1%
19 3
 
1.1%
팔달구 3
 
1.1%
화성시 3
 
1.1%
Other values (167) 188
69.4%
2023-12-11T07:32:54.623513image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
233
 
18.2%
시 54
 
4.2%
기 51
 
4.0%
도 50
 
3.9%
경 49
 
3.8%
로 47
 
3.7%
1 44
 
3.4%
2 35
 
2.7%
동 34
 
2.7%
) 28
 
2.2%
Other values (148) 658
51.3%

Most occurring categories

ValueCountFrequency (%)
Other Letter 750
58.5%
Space Separator 233
 
18.2%
Decimal Number 212
 
16.5%
Close Punctuation 28
 
2.2%
Open Punctuation 28
 
2.2%
Other Punctuation 23
 
1.8%
Dash Punctuation 9
 
0.7%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
시 54
 
7.2%
기 51
 
6.8%
도 50
 
6.7%
경 49
 
6.5%
로 47
 
6.3%
동 34
 
4.5%
양 20
 
2.7%
구 20
 
2.7%
길 20
 
2.7%
번 16
 
2.1%
Other values (133) 389
51.9%
Decimal Number
ValueCountFrequency (%)
1 44
20.8%
2 35
16.5%
3 26
12.3%
5 22
10.4%
0 18
8.5%
4 17
 
8.0%
6 17
 
8.0%
9 15
 
7.1%
7 11
 
5.2%
8 7
 
3.3%
Space Separator
ValueCountFrequency (%)
233
100.0%
Close Punctuation
ValueCountFrequency (%)
) 28
100.0%
Open Punctuation
ValueCountFrequency (%)
( 28
100.0%
Other Punctuation
ValueCountFrequency (%)
, 23
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 9
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 750
58.5%
Common 533
41.5%

Most frequent character per script

Hangul
ValueCountFrequency (%)
시 54
 
7.2%
기 51
 
6.8%
도 50
 
6.7%
경 49
 
6.5%
로 47
 
6.3%
동 34
 
4.5%
양 20
 
2.7%
구 20
 
2.7%
길 20
 
2.7%
번 16
 
2.1%
Other values (133) 389
51.9%
Common
ValueCountFrequency (%)
233
43.7%
1 44
 
8.3%
2 35
 
6.6%
) 28
 
5.3%
( 28
 
5.3%
3 26
 
4.9%
, 23
 
4.3%
5 22
 
4.1%
0 18
 
3.4%
4 17
 
3.2%
Other values (5) 59
 
11.1%

Most occurring blocks

ValueCountFrequency (%)
Hangul 750
58.5%
ASCII 533
41.5%

Most frequent character per block

ASCII
ValueCountFrequency (%)
233
43.7%
1 44
 
8.3%
2 35
 
6.6%
) 28
 
5.3%
( 28
 
5.3%
3 26
 
4.9%
, 23
 
4.3%
5 22
 
4.1%
0 18
 
3.4%
4 17
 
3.2%
Other values (5) 59
 
11.1%
Hangul
ValueCountFrequency (%)
시 54
 
7.2%
기 51
 
6.8%
도 50
 
6.7%
경 49
 
6.5%
로 47
 
6.3%
동 34
 
4.5%
양 20
 
2.7%
구 20
 
2.7%
길 20
 
2.7%
번 16
 
2.1%
Other values (133) 389
51.9%

소재지지번주소
Text

Distinct51
Distinct (%)96.2%
Missing0
Missing (%)0.0%
Memory size556.0 B
2023-12-11T07:32:54.881697image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length38
Median length32
Mean length26.773585
Min length14

Characters and Unicode

Total characters1419
Distinct characters158
Distinct categories6 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique49 ?
Unique (%)92.5%

Sample

1st row경기도 고양시 일산동구 마두동 802-1번지 뉴삼창마트 A동 503호
2nd row경기도 고양시 덕양구 주교동 602-11번지 404호
3rd row경기도 고양시 일산동구 장항동 776-1번지 메탈릭타워 602동 2호
4th row경기도 고양시 덕양구 행신동 765번지 해동BD 510호
5th row경기도 고양시 덕양구 주교동 602-11번지 404호
ValueCountFrequency (%)
경기도 53
 
18.0%
수원시 6
 
2.0%
부천시 6
 
2.0%
고양시 5
 
1.7%
3층 5
 
1.7%
중동 4
 
1.4%
팔달구 4
 
1.4%
101호 3
 
1.0%
화성시 3
 
1.0%
남양주시 3
 
1.0%
Other values (178) 203
68.8%
2023-12-11T07:32:55.297572image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
242
 
17.1%
1 64
 
4.5%
동 58
 
4.1%
기 55
 
3.9%
시 55
 
3.9%
도 54
 
3.8%
경 53
 
3.7%
지 52
 
3.7%
번 50
 
3.5%
- 42
 
3.0%
Other values (148) 694
48.9%

Most occurring categories

ValueCountFrequency (%)
Other Letter 833
58.7%
Decimal Number 297
 
20.9%
Space Separator 242
 
17.1%
Dash Punctuation 42
 
3.0%
Uppercase Letter 3
 
0.2%
Other Punctuation 2
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
동 58
 
7.0%
기 55
 
6.6%
시 55
 
6.6%
도 54
 
6.5%
경 53
 
6.4%
지 52
 
6.2%
번 50
 
6.0%
호 24
 
2.9%
구 23
 
2.8%
양 17
 
2.0%
Other values (132) 392
47.1%
Decimal Number
ValueCountFrequency (%)
1 64
21.5%
4 39
13.1%
0 36
12.1%
3 35
11.8%
2 27
9.1%
5 26
8.8%
6 23
 
7.7%
7 20
 
6.7%
8 16
 
5.4%
9 11
 
3.7%
Uppercase Letter
ValueCountFrequency (%)
A 1
33.3%
D 1
33.3%
B 1
33.3%
Space Separator
ValueCountFrequency (%)
242
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 42
100.0%
Other Punctuation
ValueCountFrequency (%)
, 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 833
58.7%
Common 583
41.1%
Latin 3
 
0.2%

Most frequent character per script

Hangul
ValueCountFrequency (%)
동 58
 
7.0%
기 55
 
6.6%
시 55
 
6.6%
도 54
 
6.5%
경 53
 
6.4%
지 52
 
6.2%
번 50
 
6.0%
호 24
 
2.9%
구 23
 
2.8%
양 17
 
2.0%
Other values (132) 392
47.1%
Common
ValueCountFrequency (%)
242
41.5%
1 64
 
11.0%
- 42
 
7.2%
4 39
 
6.7%
0 36
 
6.2%
3 35
 
6.0%
2 27
 
4.6%
5 26
 
4.5%
6 23
 
3.9%
7 20
 
3.4%
Other values (3) 29
 
5.0%
Latin
ValueCountFrequency (%)
A 1
33.3%
D 1
33.3%
B 1
33.3%

Most occurring blocks

ValueCountFrequency (%)
Hangul 833
58.7%
ASCII 586
41.3%

Most frequent character per block

ASCII
ValueCountFrequency (%)
242
41.3%
1 64
 
10.9%
- 42
 
7.2%
4 39
 
6.7%
0 36
 
6.1%
3 35
 
6.0%
2 27
 
4.6%
5 26
 
4.4%
6 23
 
3.9%
7 20
 
3.4%
Other values (6) 32
 
5.5%
Hangul
ValueCountFrequency (%)
동 58
 
7.0%
기 55
 
6.6%
시 55
 
6.6%
도 54
 
6.5%
경 53
 
6.4%
지 52
 
6.2%
번 50
 
6.0%
호 24
 
2.9%
구 23
 
2.8%
양 17
 
2.0%
Other values (132) 392
47.1%

소재지우편번호
Real number (ℝ)

HIGH CORRELATION  MISSING 

Distinct46
Distinct (%)90.2%
Missing2
Missing (%)3.8%
Infinite0
Infinite (%)0.0%
Mean13929.431
Minimum10059
Maximum18413
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size609.0 B
2023-12-11T07:32:55.478519image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum10059
5-th percentile10437
Q111604
median14263
Q316178.5
95-th percentile18107
Maximum18413
Range8354
Interquartile range (IQR)4574.5

Descriptive statistics

Standard deviation2560.3968
Coefficient of variation (CV)0.18381201
Kurtosis-1.2697104
Mean13929.431
Median Absolute Deviation (MAD)2258
Skewness0.14439389
Sum710401
Variance6555631.8
MonotonicityNot monotonic
2023-12-11T07:32:55.598866image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=46)
ValueCountFrequency (%)
14548 3
 
5.7%
11946 2
 
3.8%
10460 2
 
3.8%
11339 2
 
3.8%
12972 1
 
1.9%
18303 1
 
1.9%
18401 1
 
1.9%
14092 1
 
1.9%
13935 1
 
1.9%
11451 1
 
1.9%
Other values (36) 36
67.9%
(Missing) 2
 
3.8%
ValueCountFrequency (%)
10059 1
1.9%
10401 1
1.9%
10414 1
1.9%
10460 2
3.8%
10526 1
1.9%
10894 1
1.9%
11023 1
1.9%
11145 1
1.9%
11180 1
1.9%
11339 2
3.8%
ValueCountFrequency (%)
18413 1
1.9%
18401 1
1.9%
18303 1
1.9%
17911 1
1.9%
17587 1
1.9%
17418 1
1.9%
17080 1
1.9%
16979 1
1.9%
16521 1
1.9%
16519 1
1.9%

WGS84위도
Real number (ℝ)

HIGH CORRELATION 

Distinct50
Distinct (%)94.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean37.492973
Minimum36.99424
Maximum38.000371
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size609.0 B
2023-12-11T07:32:56.004524image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum36.99424
5-th percentile37.171557
Q137.275959
median37.491653
Q337.661938
95-th percentile37.900985
Maximum38.000371
Range1.0061303
Interquartile range (IQR)0.38597877

Descriptive statistics

Standard deviation0.23815353
Coefficient of variation (CV)0.006351951
Kurtosis-0.63967768
Mean37.492973
Median Absolute Deviation (MAD)0.18117364
Skewness0.084676747
Sum1987.1276
Variance0.056717103
MonotonicityNot monotonic
2023-12-11T07:32:56.146899image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
37.6571617407 2
 
3.8%
37.5892290323 2
 
3.8%
37.9058866517 2
 
3.8%
37.6516574088 1
 
1.9%
37.7489849773 1
 
1.9%
37.310479632 1
 
1.9%
37.0137160482 1
 
1.9%
37.3874441778 1
 
1.9%
37.4055211733 1
 
1.9%
37.8385880741 1
 
1.9%
Other values (40) 40
75.5%
ValueCountFrequency (%)
36.9942404867 1
1.9%
37.0137160482 1
1.9%
37.1211041939 1
1.9%
37.2051925278 1
1.9%
37.2103829444 1
1.9%
37.2200465314 1
1.9%
37.2517704582 1
1.9%
37.2662100568 1
1.9%
37.2666535841 1
1.9%
37.2674866472 1
1.9%
ValueCountFrequency (%)
38.0003708135 1
1.9%
37.9058866517 2
3.8%
37.897718001 1
1.9%
37.8385880741 1
1.9%
37.8229458147 1
1.9%
37.7510936814 1
1.9%
37.7489849773 1
1.9%
37.7489535275 1
1.9%
37.7237876146 1
1.9%
37.7087425637 1
1.9%

WGS84경도
Real number (ℝ)

HIGH CORRELATION 

Distinct50
Distinct (%)94.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean126.98718
Minimum126.62334
Maximum127.62981
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size609.0 B
2023-12-11T07:32:56.318534image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum126.62334
5-th percentile126.75429
Q1126.82738
median127.01876
Q3127.10874
95-th percentile127.26334
Maximum127.62981
Range1.0064673
Interquartile range (IQR)0.2813625

Descriptive statistics

Standard deviation0.18950136
Coefficient of variation (CV)0.0014922873
Kurtosis1.0165744
Mean126.98718
Median Absolute Deviation (MAD)0.12772524
Skewness0.59343468
Sum6730.3206
Variance0.035910765
MonotonicityNot monotonic
2023-12-11T07:32:56.479552image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
126.8317598343 2
 
3.8%
127.1464824563 2
 
3.8%
127.0443960709 2
 
3.8%
126.7783773082 1
 
1.9%
127.0694863466 1
 
1.9%
126.8273822929 1
 
1.9%
127.2722955536 1
 
1.9%
126.9302865078 1
 
1.9%
126.9530050681 1
 
1.9%
127.0623189539 1
 
1.9%
Other values (40) 40
75.5%
ValueCountFrequency (%)
126.6233385291 1
1.9%
126.7511868118 1
1.9%
126.7516131294 1
1.9%
126.7560747134 1
1.9%
126.7622165994 1
1.9%
126.7693817144 1
1.9%
126.7720776094 1
1.9%
126.7724339551 1
1.9%
126.7734691236 1
1.9%
126.7741870709 1
1.9%
ValueCountFrequency (%)
127.6298058677 1
1.9%
127.3035464517 1
1.9%
127.2722955536 1
1.9%
127.2573678264 1
1.9%
127.2105040579 1
1.9%
127.2009931308 1
1.9%
127.197809108 1
1.9%
127.1464824563 2
3.8%
127.1401420254 1
1.9%
127.1330467128 1
1.9%

Interactions

2023-12-11T07:32:51.590733image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T07:32:49.595092image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T07:32:50.085642image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T07:32:50.592114image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T07:32:51.089319image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T07:32:51.688436image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T07:32:49.691329image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T07:32:50.179260image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T07:32:50.693065image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T07:32:51.211308image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T07:32:51.788395image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T07:32:49.805697image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T07:32:50.277704image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T07:32:50.810201image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T07:32:51.303220image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T07:32:51.885432image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T07:32:49.922087image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T07:32:50.388406image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T07:32:50.890365image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T07:32:51.388574image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T07:32:51.995152image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T07:32:50.003356image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T07:32:50.494050image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T07:32:50.983881image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T07:32:51.490945image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-11T07:32:56.584249image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
시군명사업장명인허가일자영업상태명폐업일자소재지도로명주소소재지지번주소소재지우편번호WGS84위도WGS84경도
시군명1.0001.0000.6960.0000.8131.0001.0001.0000.9840.964
사업장명1.0001.0000.2280.6630.9680.9880.9991.0001.0001.000
인허가일자0.6960.2281.0000.3060.6921.0000.8620.3800.5300.524
영업상태명0.0000.6630.3061.000NaN0.0000.0000.3920.0000.302
폐업일자0.8130.9680.692NaN1.0001.0001.0000.6310.7000.623
소재지도로명주소1.0000.9881.0000.0001.0001.0001.0001.0001.0001.000
소재지지번주소1.0000.9990.8620.0001.0001.0001.0001.0001.0001.000
소재지우편번호1.0001.0000.3800.3920.6311.0001.0001.0000.9330.758
WGS84위도0.9841.0000.5300.0000.7001.0001.0000.9331.0000.744
WGS84경도0.9641.0000.5240.3020.6231.0001.0000.7580.7441.000
2023-12-11T07:32:56.706305image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
시군명영업상태명
시군명1.0000.000
영업상태명0.0001.000
2023-12-11T07:32:56.784796image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
인허가일자폐업일자소재지우편번호WGS84위도WGS84경도시군명영업상태명
인허가일자1.0000.4330.039-0.071-0.1010.3480.268
폐업일자0.4331.000-0.2290.2460.3170.3481.000
소재지우편번호0.039-0.2291.000-0.9080.1210.7810.291
WGS84위도-0.0710.246-0.9081.000-0.0420.7110.000
WGS84경도-0.1010.3170.121-0.0421.0000.6370.207
시군명0.3480.3480.7810.7110.6371.0000.000
영업상태명0.2681.0000.2910.0000.2070.0001.000

Missing values

2023-12-11T07:32:52.136147image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-11T07:32:52.305248image/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.
2023-12-11T07:32:52.420432image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
The correlation heatmap measures nullity correlation: how strongly the presence or absence of one variable affects the presence of another.

Sample

시군명사업장명인허가일자영업상태명폐업일자소재지도로명주소소재지지번주소소재지우편번호WGS84위도WGS84경도
0고양시일산가족상담센터20100308운영중<NA>경기도 고양시 일산동구 중앙로 1172경기도 고양시 일산동구 마두동 802-1번지 뉴삼창마트 A동 503호1041437.651657126.778377
1고양시고양로뎀성폭력상담소20080721운영중<NA>경기도 고양시 덕양구 고양시청로 19경기도 고양시 덕양구 주교동 602-11번지 404호1046037.657162126.83176
2고양시(사)고양여성민우회 성폭력상담소20020608운영중<NA>경기도 고양시 일산동구 무궁화로 32-21경기도 고양시 일산동구 장항동 776-1번지 메탈릭타워 602동 2호1040137.661938126.769382
3고양시한마음가족상담센터20100430운영중<NA>경기도 고양시 덕양구 용현로 9경기도 고양시 덕양구 행신동 765번지 해동BD 510호1052637.613578126.835484
4고양시로뎀성폭력상담소20080721폐업 등20090303경기도 고양시 덕양구 고양시청로 19경기도 고양시 덕양구 주교동 602-11번지 404호1046037.657162126.83176
5광명시광명YWCA성폭력상담소20001215운영중<NA>경기도 광명시 오리로 953, 3층 (광명동)경기도 광명시 광명동 158-487번지 3층1426337.478351126.857041
6광주시씨알여성회부설성폭력상담소20030507운영중<NA>경기도 광주시 광주대로129번길 13 (송정동,3층)경기도 광주시 송정동 130-14번지 3층1273937.417836127.257368
7구리시구리성폭력상담소20030205폐업 등20100531경기도 구리시 벌말로129번길 50 (토평동)경기도 구리시 토평동 984번지1194637.589229127.146482
8구리시구리성폭력상담소20100531폐업 등20121213경기도 구리시 벌말로129번길 50 (토평동,구리시종합사회복지관 3층)경기도 구리시 토평동 984번지 구리시종합사회복지관 3층1194637.589229127.146482
9군포시군포여성민우회 성폭력상담소19990830운영중<NA>경기도 군포시 산본로323번길 20-33, 302호 (산본동, 대원프라자)경기도 군포시 산본동 1137-1번지 대원프라자 301,302호1586537.359783126.930674
시군명사업장명인허가일자영업상태명폐업일자소재지도로명주소소재지지번주소소재지우편번호WGS84위도WGS84경도
43이천시행복드림 가정 상담센터20140828폐업 등20150309경기도 이천시 장호원읍 장감로65번길 90경기도 이천시 장호원읍 노탑리 173-15번지1741837.121104127.629806
44파주시파주성폭력상담소 함께20110119운영중<NA>경기도 파주시 와석순환로 415 (와동동)경기도 파주시 와동동 1358번지1089437.723788126.751187
45파주시파주상담센터 뜰20020109폐업 등20101101<NA>경기도 파주시 금촌동 7709-9번지<NA>37.748954126.774407
46평택시평택성폭력상담소19980910운영중<NA>경기도 평택시 평택1로 25 (평택동)경기도 평택시 평택동 66-10번지1791136.99424127.087111
47포천시포천가족성상담센터20011114운영중<NA><NA>경기도 포천시 소흘읍 송우리 494-1번지1118037.822946127.140142
48포천시사단법인 해피패밀리 포천지부 희망상담소20080617폐업 등20160203경기도 포천시 중앙로119번길 18-1 (신읍동)경기도 포천시 신읍동 47-18번지 6통4반1114537.897718127.200993
49하남시하남YWCA부설성폭력상담소20040430운영중<NA>경기도 하남시 신장로205번길 27 (덕풍동,서해상가4층)경기도 하남시 덕풍동 346-4번지 서해상가4층1297237.542512127.197809
50화성시맘 톡톡 상담센터20160222운영중<NA>경기도 화성시 봉담읍 오래3길 11, 1층경기도 화성시 봉담읍 동화리 558-12번지1830337.220047126.954705
51화성시태안성폭력상담소20051028폐업 등20090123경기도 화성시 병점서로 31-6경기도 화성시 병점동 431-91841337.205193127.039639
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