Overview

Dataset statistics

Number of variables11
Number of observations64
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory5.9 KiB
Average record size in memory94.1 B

Variable types

Categorical4
Text4
Numeric3

Alerts

집계년도 has constant value ""Constant
비고사항 is highly overall correlated with 시군명 and 1 other fieldsHigh correlation
단체구분명 is highly overall correlated with 비고사항High correlation
시군명 is highly overall correlated with 소재지우편번호 and 3 other fieldsHigh 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
단체명 has unique valuesUnique

Reproduction

Analysis started2024-05-03 18:32:37.877906
Analysis finished2024-05-03 18:32:47.699518
Duration9.82 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

집계년도
Categorical

CONSTANT 

Distinct1
Distinct (%)1.6%
Missing0
Missing (%)0.0%
Memory size644.0 B
2024
64 

Length

Max length4
Median length4
Mean length4
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row2024
2nd row2024
3rd row2024
4th row2024
5th row2024

Common Values

ValueCountFrequency (%)
2024 64
100.0%

Length

2024-05-03T18:32:47.974512image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-03T18:32:48.505456image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2024 64
100.0%

시군명
Categorical

HIGH CORRELATION 

Distinct31
Distinct (%)48.4%
Missing0
Missing (%)0.0%
Memory size644.0 B
수원시
13 
성남시
 
3
평택시
 
3
의정부시
 
3
안산시
 
3
Other values (26)
39 

Length

Max length4
Median length3
Mean length3.09375
Min length3

Unique

Unique14 ?
Unique (%)21.9%

Sample

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

Common Values

ValueCountFrequency (%)
수원시 13
20.3%
성남시 3
 
4.7%
평택시 3
 
4.7%
의정부시 3
 
4.7%
안산시 3
 
4.7%
부천시 3
 
4.7%
이천시 2
 
3.1%
용인시 2
 
3.1%
하남시 2
 
3.1%
김포시 2
 
3.1%
Other values (21) 28
43.8%

Length

2024-05-03T18:32:48.797334image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
수원시 13
20.3%
평택시 3
 
4.7%
의정부시 3
 
4.7%
안산시 3
 
4.7%
부천시 3
 
4.7%
성남시 3
 
4.7%
과천시 2
 
3.1%
시흥시 2
 
3.1%
양평군 2
 
3.1%
안양시 2
 
3.1%
Other values (21) 28
43.8%

단체명
Text

UNIQUE 

Distinct64
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size644.0 B
2024-05-03T18:32:49.333265image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length10
Median length4
Mean length4.953125
Min length4

Characters and Unicode

Total characters317
Distinct characters67
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

Unique64 ?
Unique (%)100.0%

Sample

1st row가평지회
2nd row고양지회
3rd row과천지부
4th row과천지회
5th row광명지회
ValueCountFrequency (%)
가평지회 1
 
1.6%
고양지회 1
 
1.6%
용인지부 1
 
1.6%
안산지회 1
 
1.6%
안산지부 1
 
1.6%
영화인협회도지회 1
 
1.6%
안성지회 1
 
1.6%
연예예술인협회 1
 
1.6%
안양지회 1
 
1.6%
양주지회 1
 
1.6%
Other values (54) 54
84.4%
2024-05-03T18:32:50.248640image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
지 57
18.0%
회 57
18.0%
부 20
 
6.3%
도 11
 
3.5%
협 11
 
3.5%
천 9
 
2.8%
양 7
 
2.2%
주 7
 
2.2%
인 6
 
1.9%
연 6
 
1.9%
Other values (57) 126
39.7%

Most occurring categories

ValueCountFrequency (%)
Other Letter 317
100.0%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
지 57
18.0%
회 57
18.0%
부 20
 
6.3%
도 11
 
3.5%
협 11
 
3.5%
천 9
 
2.8%
양 7
 
2.2%
주 7
 
2.2%
인 6
 
1.9%
연 6
 
1.9%
Other values (57) 126
39.7%

Most occurring scripts

ValueCountFrequency (%)
Hangul 317
100.0%

Most frequent character per script

Hangul
ValueCountFrequency (%)
지 57
18.0%
회 57
18.0%
부 20
 
6.3%
도 11
 
3.5%
협 11
 
3.5%
천 9
 
2.8%
양 7
 
2.2%
주 7
 
2.2%
인 6
 
1.9%
연 6
 
1.9%
Other values (57) 126
39.7%

Most occurring blocks

ValueCountFrequency (%)
Hangul 317
100.0%

Most frequent character per block

Hangul
ValueCountFrequency (%)
지 57
18.0%
회 57
18.0%
부 20
 
6.3%
도 11
 
3.5%
협 11
 
3.5%
천 9
 
2.8%
양 7
 
2.2%
주 7
 
2.2%
인 6
 
1.9%
연 6
 
1.9%
Other values (57) 126
39.7%

단체구분명
Categorical

HIGH CORRELATION 

Distinct3
Distinct (%)4.7%
Missing0
Missing (%)0.0%
Memory size644.0 B
시군예총
31 
민예총
22 
도예총
11 

Length

Max length4
Median length3
Mean length3.484375
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row시군예총
2nd row시군예총
3rd row민예총
4th row시군예총
5th row시군예총

Common Values

ValueCountFrequency (%)
시군예총 31
48.4%
민예총 22
34.4%
도예총 11
 
17.2%

Length

2024-05-03T18:32:50.641007image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-03T18:32:50.919573image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
시군예총 31
48.4%
민예총 22
34.4%
도예총 11
 
17.2%

대표자명
Text

Distinct62
Distinct (%)96.9%
Missing0
Missing (%)0.0%
Memory size644.0 B
2024-05-03T18:32:51.373818image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length3
Median length3
Mean length3
Min length3

Characters and Unicode

Total characters192
Distinct characters85
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

Unique60 ?
Unique (%)93.8%

Sample

1st row유경한
2nd row유양수
3rd row정영미
4th row조월신
5th row이주형
ValueCountFrequency (%)
강연희 2
 
3.1%
오현규 2
 
3.1%
이증희 1
 
1.6%
장윤영 1
 
1.6%
유경한 1
 
1.6%
백인숙 1
 
1.6%
윤여길 1
 
1.6%
김진국 1
 
1.6%
민경호 1
 
1.6%
박남춘 1
 
1.6%
Other values (52) 52
81.2%
2024-05-03T18:32:52.240303image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
이 12
 
6.2%
김 11
 
5.7%
박 7
 
3.6%
희 6
 
3.1%
오 6
 
3.1%
경 5
 
2.6%
정 5
 
2.6%
한 4
 
2.1%
재 4
 
2.1%
영 4
 
2.1%
Other values (75) 128
66.7%

Most occurring categories

ValueCountFrequency (%)
Other Letter 192
100.0%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
이 12
 
6.2%
김 11
 
5.7%
박 7
 
3.6%
희 6
 
3.1%
오 6
 
3.1%
경 5
 
2.6%
정 5
 
2.6%
한 4
 
2.1%
재 4
 
2.1%
영 4
 
2.1%
Other values (75) 128
66.7%

Most occurring scripts

ValueCountFrequency (%)
Hangul 192
100.0%

Most frequent character per script

Hangul
ValueCountFrequency (%)
이 12
 
6.2%
김 11
 
5.7%
박 7
 
3.6%
희 6
 
3.1%
오 6
 
3.1%
경 5
 
2.6%
정 5
 
2.6%
한 4
 
2.1%
재 4
 
2.1%
영 4
 
2.1%
Other values (75) 128
66.7%

Most occurring blocks

ValueCountFrequency (%)
Hangul 192
100.0%

Most frequent character per block

Hangul
ValueCountFrequency (%)
이 12
 
6.2%
김 11
 
5.7%
박 7
 
3.6%
희 6
 
3.1%
오 6
 
3.1%
경 5
 
2.6%
정 5
 
2.6%
한 4
 
2.1%
재 4
 
2.1%
영 4
 
2.1%
Other values (75) 128
66.7%

비고사항
Categorical

HIGH CORRELATION 

Distinct10
Distinct (%)15.6%
Missing0
Missing (%)0.0%
Memory size644.0 B
<NA>
33 
사진,국악,음악,문인,미술,연예,연극,무용,영화
14 
사진,국악,음악,문인,미술,연예,연극,무용
7 
사진,국악,음악,문인,미술,연예,연극,영화
 
3
국악,음악,문인,미술,연예,연극,무용,영화
 
2
Other values (5)
5 

Length

Max length26
Median length4
Mean length13.859375
Min length4

Unique

Unique5 ?
Unique (%)7.8%

Sample

1st row사진,국악,음악,문인,미술,연예,연극,영화
2nd row사진,국악,음악,문인,미술,연예,연극,무용,영화
3rd row<NA>
4th row사진,국악,음악,문인,미술,연예,연극,무용
5th row사진,국악,음악,문인,미술,연예,연극,무용

Common Values

ValueCountFrequency (%)
<NA> 33
51.6%
사진,국악,음악,문인,미술,연예,연극,무용,영화 14
21.9%
사진,국악,음악,문인,미술,연예,연극,무용 7
 
10.9%
사진,국악,음악,문인,미술,연예,연극,영화 3
 
4.7%
국악,음악,문인,미술,연예,연극,무용,영화 2
 
3.1%
사진,국악,음악,문인,미술,연극,무용,연예,영화 1
 
1.6%
사진,국악,음악,문인,미술,연예,연극 1
 
1.6%
사진,국악,음악,문인,미술,연예,연극,무용,건축 1
 
1.6%
사진,국악,음악,문인,미술,연예,영화 1
 
1.6%
사진,국악,문인,미술,연예,연극,무용,영화 1
 
1.6%

Length

2024-05-03T18:32:52.679313image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-03T18:32:53.066076image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 33
51.6%
사진,국악,음악,문인,미술,연예,연극,무용,영화 14
21.9%
사진,국악,음악,문인,미술,연예,연극,무용 7
 
10.9%
사진,국악,음악,문인,미술,연예,연극,영화 3
 
4.7%
국악,음악,문인,미술,연예,연극,무용,영화 2
 
3.1%
사진,국악,음악,문인,미술,연극,무용,연예,영화 1
 
1.6%
사진,국악,음악,문인,미술,연예,연극 1
 
1.6%
사진,국악,음악,문인,미술,연예,연극,무용,건축 1
 
1.6%
사진,국악,음악,문인,미술,연예,영화 1
 
1.6%
사진,국악,문인,미술,연예,연극,무용,영화 1
 
1.6%

소재지우편번호
Real number (ℝ)

HIGH CORRELATION 

Distinct50
Distinct (%)78.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean14585.312
Minimum10022
Maximum18459
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size708.0 B
2024-05-03T18:32:53.523877image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum10022
5-th percentile10911.7
Q112613.5
median14639.5
Q316488
95-th percentile18131
Maximum18459
Range8437
Interquartile range (IQR)3874.5

Descriptive statistics

Standard deviation2427.6135
Coefficient of variation (CV)0.16644234
Kurtosis-1.2289402
Mean14585.312
Median Absolute Deviation (MAD)1905.5
Skewness-0.11672136
Sum933460
Variance5893307.4
MonotonicityNot monotonic
2024-05-03T18:32:53.897222image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
16488 10
 
15.6%
14034 2
 
3.1%
18131 2
 
3.1%
12238 2
 
3.1%
17062 2
 
3.1%
13290 2
 
3.1%
11623 1
 
1.6%
12585 1
 
1.6%
12547 1
 
1.6%
12628 1
 
1.6%
Other values (40) 40
62.5%
ValueCountFrequency (%)
10022 1
1.6%
10110 1
1.6%
10471 1
1.6%
10894 1
1.6%
11012 1
1.6%
11151 1
1.6%
11340 1
1.6%
11517 1
1.6%
11623 1
1.6%
11670 1
1.6%
ValueCountFrequency (%)
18459 1
1.6%
18304 1
1.6%
18271 1
1.6%
18131 2
3.1%
17901 1
1.6%
17822 1
1.6%
17589 1
1.6%
17379 1
1.6%
17351 1
1.6%
17062 2
3.1%

소재지지번주소
Text

Distinct52
Distinct (%)81.2%
Missing0
Missing (%)0.0%
Memory size644.0 B
2024-05-03T18:32:54.549649image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length40
Median length23
Mean length21.21875
Min length15

Characters and Unicode

Total characters1358
Distinct characters119
Distinct categories5 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique47 ?
Unique (%)73.4%

Sample

1st row경기도 가평군 가평읍 대곡리 316번지
2nd row경기도 고양시 덕양구 성사동 826번지
3rd row경기도 과천시 문원동 15-30번지
4th row경기도 과천시 중앙동 6-2번지
5th row경기도 광명시 철산동 222-1번지
ValueCountFrequency (%)
경기도 64
 
21.5%
수원시 12
 
4.0%
팔달구 11
 
3.7%
인계동 10
 
3.4%
1116-1번지 9
 
3.0%
성남시 4
 
1.3%
용인시 3
 
1.0%
처인구 3
 
1.0%
화성시 3
 
1.0%
수정구 3
 
1.0%
Other values (148) 175
58.9%
2024-05-03T18:32:55.754843image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
233
17.2%
1 81
 
6.0%
경 64
 
4.7%
기 64
 
4.7%
도 64
 
4.7%
지 64
 
4.7%
번 62
 
4.6%
시 62
 
4.6%
동 57
 
4.2%
- 41
 
3.0%
Other values (109) 566
41.7%

Most occurring categories

ValueCountFrequency (%)
Other Letter 828
61.0%
Decimal Number 254
 
18.7%
Space Separator 233
 
17.2%
Dash Punctuation 41
 
3.0%
Uppercase Letter 2
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
경 64
 
7.7%
기 64
 
7.7%
도 64
 
7.7%
지 64
 
7.7%
번 62
 
7.5%
시 62
 
7.5%
동 57
 
6.9%
구 27
 
3.3%
수 18
 
2.2%
인 16
 
1.9%
Other values (95) 330
39.9%
Decimal Number
ValueCountFrequency (%)
1 81
31.9%
4 26
 
10.2%
3 26
 
10.2%
6 23
 
9.1%
7 21
 
8.3%
2 21
 
8.3%
5 15
 
5.9%
0 15
 
5.9%
8 15
 
5.9%
9 11
 
4.3%
Uppercase Letter
ValueCountFrequency (%)
L 1
50.0%
H 1
50.0%
Space Separator
ValueCountFrequency (%)
233
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 41
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 828
61.0%
Common 528
38.9%
Latin 2
 
0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
경 64
 
7.7%
기 64
 
7.7%
도 64
 
7.7%
지 64
 
7.7%
번 62
 
7.5%
시 62
 
7.5%
동 57
 
6.9%
구 27
 
3.3%
수 18
 
2.2%
인 16
 
1.9%
Other values (95) 330
39.9%
Common
ValueCountFrequency (%)
233
44.1%
1 81
 
15.3%
- 41
 
7.8%
4 26
 
4.9%
3 26
 
4.9%
6 23
 
4.4%
7 21
 
4.0%
2 21
 
4.0%
5 15
 
2.8%
0 15
 
2.8%
Other values (2) 26
 
4.9%
Latin
ValueCountFrequency (%)
L 1
50.0%
H 1
50.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 828
61.0%
ASCII 530
39.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
233
44.0%
1 81
 
15.3%
- 41
 
7.7%
4 26
 
4.9%
3 26
 
4.9%
6 23
 
4.3%
7 21
 
4.0%
2 21
 
4.0%
5 15
 
2.8%
0 15
 
2.8%
Other values (4) 28
 
5.3%
Hangul
ValueCountFrequency (%)
경 64
 
7.7%
기 64
 
7.7%
도 64
 
7.7%
지 64
 
7.7%
번 62
 
7.5%
시 62
 
7.5%
동 57
 
6.9%
구 27
 
3.3%
수 18
 
2.2%
인 16
 
1.9%
Other values (95) 330
39.9%

소재지도로명주소
Text

Distinct52
Distinct (%)81.2%
Missing0
Missing (%)0.0%
Memory size644.0 B
2024-05-03T18:32:56.465729image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length27
Median length23
Mean length18.921875
Min length13

Characters and Unicode

Total characters1211
Distinct characters132
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

Unique47 ?
Unique (%)73.4%

Sample

1st row경기도 가평군 가평읍 문화로 131
2nd row경기도 고양시 덕양구 어울림로 33
3rd row경기도 과천시 공원마을3길 45
4th row경기도 과천시 통영로 5
5th row경기도 광명시 시청로 20
ValueCountFrequency (%)
경기도 64
 
21.8%
수원시 12
 
4.1%
팔달구 11
 
3.8%
인계로 9
 
3.1%
178 9
 
3.1%
성남시 4
 
1.4%
10 4
 
1.4%
화성시 3
 
1.0%
5 3
 
1.0%
수정구 3
 
1.0%
Other values (138) 171
58.4%
2024-05-03T18:32:57.484920image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
229
18.9%
경 68
 
5.6%
기 65
 
5.4%
도 64
 
5.3%
시 63
 
5.2%
로 59
 
4.9%
1 51
 
4.2%
2 28
 
2.3%
구 27
 
2.2%
3 26
 
2.1%
Other values (122) 531
43.8%

Most occurring categories

ValueCountFrequency (%)
Other Letter 753
62.2%
Space Separator 229
 
18.9%
Decimal Number 225
 
18.6%
Dash Punctuation 4
 
0.3%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
경 68
 
9.0%
기 65
 
8.6%
도 64
 
8.5%
시 63
 
8.4%
로 59
 
7.8%
구 27
 
3.6%
길 26
 
3.5%
수 22
 
2.9%
번 21
 
2.8%
원 18
 
2.4%
Other values (110) 320
42.5%
Decimal Number
ValueCountFrequency (%)
1 51
22.7%
2 28
12.4%
3 26
11.6%
7 26
11.6%
8 24
10.7%
0 17
 
7.6%
4 15
 
6.7%
5 15
 
6.7%
9 14
 
6.2%
6 9
 
4.0%
Space Separator
ValueCountFrequency (%)
229
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 4
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 753
62.2%
Common 458
37.8%

Most frequent character per script

Hangul
ValueCountFrequency (%)
경 68
 
9.0%
기 65
 
8.6%
도 64
 
8.5%
시 63
 
8.4%
로 59
 
7.8%
구 27
 
3.6%
길 26
 
3.5%
수 22
 
2.9%
번 21
 
2.8%
원 18
 
2.4%
Other values (110) 320
42.5%
Common
ValueCountFrequency (%)
229
50.0%
1 51
 
11.1%
2 28
 
6.1%
3 26
 
5.7%
7 26
 
5.7%
8 24
 
5.2%
0 17
 
3.7%
4 15
 
3.3%
5 15
 
3.3%
9 14
 
3.1%
Other values (2) 13
 
2.8%

Most occurring blocks

ValueCountFrequency (%)
Hangul 753
62.2%
ASCII 458
37.8%

Most frequent character per block

ASCII
ValueCountFrequency (%)
229
50.0%
1 51
 
11.1%
2 28
 
6.1%
3 26
 
5.7%
7 26
 
5.7%
8 24
 
5.2%
0 17
 
3.7%
4 15
 
3.3%
5 15
 
3.3%
9 14
 
3.1%
Other values (2) 13
 
2.8%
Hangul
ValueCountFrequency (%)
경 68
 
9.0%
기 65
 
8.6%
도 64
 
8.5%
시 63
 
8.4%
로 59
 
7.8%
구 27
 
3.6%
길 26
 
3.5%
수 22
 
2.9%
번 21
 
2.8%
원 18
 
2.4%
Other values (110) 320
42.5%

WGS84위도
Real number (ℝ)

HIGH CORRELATION 

Distinct52
Distinct (%)81.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean37.415438
Minimum36.991121
Maximum38.106087
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size708.0 B
2024-05-03T18:32:58.093950image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum36.991121
5-th percentile37.15626
Q137.265759
median37.376445
Q337.541273
95-th percentile37.819491
Maximum38.106087
Range1.1149654
Interquartile range (IQR)0.27551401

Descriptive statistics

Standard deviation0.22476529
Coefficient of variation (CV)0.0060072874
Kurtosis0.61765308
Mean37.415438
Median Absolute Deviation (MAD)0.11068582
Skewness0.7504253
Sum2394.5881
Variance0.050519436
MonotonicityNot monotonic
2024-05-03T18:32:58.671263image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
37.2657588053 9
 
14.1%
37.2317489735 2
 
3.1%
37.4448498671 2
 
3.1%
37.1562601917 2
 
3.1%
37.3871047795 2
 
3.1%
37.5513006474 1
 
1.6%
37.5403130017 1
 
1.6%
37.7924976436 1
 
1.6%
37.5441522546 1
 
1.6%
37.5092443268 1
 
1.6%
Other values (42) 42
65.6%
ValueCountFrequency (%)
36.9911212708 1
1.6%
37.0053750559 1
1.6%
37.0071711409 1
1.6%
37.1562601917 2
3.1%
37.2007035756 1
1.6%
37.2052856278 1
1.6%
37.2249031497 1
1.6%
37.2288422693 1
1.6%
37.2317489735 2
3.1%
37.2614188559 1
1.6%
ValueCountFrequency (%)
38.1060866853 1
1.6%
37.9053331012 1
1.6%
37.8961166398 1
1.6%
37.8242544813 1
1.6%
37.7924976436 1
1.6%
37.7396980895 1
1.6%
37.7393546402 1
1.6%
37.7240923851 1
1.6%
37.7171476474 1
1.6%
37.6505947239 1
1.6%

WGS84경도
Real number (ℝ)

HIGH CORRELATION 

Distinct52
Distinct (%)81.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean127.07162
Minimum126.56054
Maximum127.63701
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size708.0 B
2024-05-03T18:32:59.135316image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum126.56054
5-th percentile126.75356
Q1126.95185
median127.03748
Q3127.19886
95-th percentile127.50091
Maximum127.63701
Range1.0764674
Interquartile range (IQR)0.24701164

Descriptive statistics

Standard deviation0.21554584
Coefficient of variation (CV)0.0016962548
Kurtosis0.67080175
Mean127.07162
Median Absolute Deviation (MAD)0.10737246
Skewness0.46336726
Sum8132.5835
Variance0.046460009
MonotonicityNot monotonic
2024-05-03T18:32:59.639471image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
127.0368671868 9
 
14.1%
127.1988571909 2
 
3.1%
127.1390489311 2
 
3.1%
127.0714232264 2
 
3.1%
126.9317884452 2
 
3.1%
127.2037915193 1
 
1.6%
127.211022898 1
 
1.6%
126.9519815437 1
 
1.6%
127.3196020976 1
 
1.6%
127.5132950178 1
 
1.6%
Other values (42) 42
65.6%
ValueCountFrequency (%)
126.5605379467 1
1.6%
126.7180615692 1
1.6%
126.7351609269 1
1.6%
126.7512642743 1
1.6%
126.7665645738 1
1.6%
126.7851685786 1
1.6%
126.7868836352 1
1.6%
126.8099722144 1
1.6%
126.82176276 1
1.6%
126.833118036 1
1.6%
ValueCountFrequency (%)
127.6370053112 1
1.6%
127.630153922 1
1.6%
127.5132950178 1
1.6%
127.5085221351 1
1.6%
127.45776095 1
1.6%
127.4259344649 1
1.6%
127.3196020976 1
1.6%
127.3090610633 1
1.6%
127.2727829285 1
1.6%
127.2572046977 1
1.6%

Interactions

2024-05-03T18:32:45.792976image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-03T18:32:43.980551image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-03T18:32:45.009483image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-03T18:32:46.212514image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-03T18:32:44.424982image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-03T18:32:45.245691image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-03T18:32:46.502084image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-03T18:32:44.728881image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-03T18:32:45.522187image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-05-03T18:32:59.955936image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
시군명단체명단체구분명대표자명비고사항소재지우편번호소재지지번주소소재지도로명주소WGS84위도WGS84경도
시군명1.0001.0000.0000.9991.0000.9780.9970.9970.9680.934
단체명1.0001.0001.0001.0001.0001.0001.0001.0001.0001.000
단체구분명0.0001.0001.0000.812NaN0.0470.0000.0000.3020.000
대표자명0.9991.0000.8121.0001.0000.9400.9840.9840.9740.930
비고사항1.0001.000NaN1.0001.0000.4191.0001.0000.6610.619
소재지우편번호0.9781.0000.0470.9400.4191.0001.0001.0000.9070.688
소재지지번주소0.9971.0000.0000.9841.0001.0001.0001.0001.0001.000
소재지도로명주소0.9971.0000.0000.9841.0001.0001.0001.0001.0001.000
WGS84위도0.9681.0000.3020.9740.6610.9071.0001.0001.0000.521
WGS84경도0.9341.0000.0000.9300.6190.6881.0001.0000.5211.000
2024-05-03T18:33:00.286133image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
비고사항단체구분명시군명
비고사항1.0001.0001.000
단체구분명1.0001.0000.000
시군명1.0000.0001.000
2024-05-03T18:33:00.542315image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
소재지우편번호WGS84위도WGS84경도시군명단체구분명비고사항
소재지우편번호1.000-0.935-0.0120.6640.0000.166
WGS84위도-0.9351.000-0.0540.6270.1720.351
WGS84경도-0.012-0.0541.0000.5290.0000.341
시군명0.6640.6270.5291.0000.0001.000
단체구분명0.0000.1720.0000.0001.0001.000
비고사항0.1660.3510.3411.0001.0001.000

Missing values

2024-05-03T18:32:46.869421image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-05-03T18:32:47.458952image/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

집계년도시군명단체명단체구분명대표자명비고사항소재지우편번호소재지지번주소소재지도로명주소WGS84위도WGS84경도
02024가평군가평지회시군예총유경한사진,국악,음악,문인,미술,연예,연극,영화12416경기도 가평군 가평읍 대곡리 316번지경기도 가평군 가평읍 문화로 13137.824254127.508522
12024고양시고양지회시군예총유양수사진,국악,음악,문인,미술,연예,연극,무용,영화10471경기도 고양시 덕양구 성사동 826번지경기도 고양시 덕양구 어울림로 3337.650595126.83479
22024과천시과천지부민예총정영미<NA>13828경기도 과천시 문원동 15-30번지경기도 과천시 공원마을3길 4537.430196127.003146
32024과천시과천지회시군예총조월신사진,국악,음악,문인,미술,연예,연극,무용13807경기도 과천시 중앙동 6-2번지경기도 과천시 통영로 537.428207126.98911
42024광명시광명지회시군예총이주형사진,국악,음악,문인,미술,연예,연극,무용14234경기도 광명시 철산동 222-1번지경기도 광명시 시청로 2037.478975126.865201
52024광주시광주지회시군예총이상오국악,음악,문인,미술,연예,연극,무용,영화12739경기도 광주시 송정동 388-1번지경기도 광주시 중앙로319번길 10-2737.429062127.257205
62024구리시구리지회시군예총김보영사진,국악,음악,문인,미술,연예,연극,무용11940경기도 구리시 수택동 848번지경기도 구리시 체육관로 7437.591473127.138625
72024군포시군포지회시군예총이상훈사진,국악,음악,문인,미술,연예,연극,무용15820경기도 군포시 산본동 1101번지경기도 군포시 고산로 59937.365784126.927466
82024김포시김포지부민예총박희정<NA>10022경기도 김포시 월곶면 군하리 4-8번지경기도 김포시 월곶면 점동로 20-2137.717148126.560538
92024김포시김포지회시군예총유영화사진,국악,음악,문인,미술,연극,무용,연예,영화10110경기도 김포시 사우동 259-4번지경기도 김포시 사우중로 2637.617179126.718062
집계년도시군명단체명단체구분명대표자명비고사항소재지우편번호소재지지번주소소재지도로명주소WGS84위도WGS84경도
542024이천시이천지부민예총강연희<NA>17351경기도 이천시 증포동 94-3번지경기도 이천시 갈산로 4037.288913127.457761
552024파주시파주지회시군예총이상주사진,국악,음악,문인,미술,연예,연극,무용,영화10894경기도 파주시 와동동 1358번지경기도 파주시 와석순환로 41537.724092126.751264
562024평택시평택지부민예총오윤희<NA>17822경기도 평택시 고덕면 동고리 149-1번지경기도 평택시 고덕면 동고2길 2037.005375127.045881
572024평택시사진작가협회도지회도예총김시묵<NA>13515경기도 성남시 분당구 야탑동 493-15번지경기도 성남시 분당구 판교로572번길 1037.407059127.137343
582024평택시평택지회시군예총서강호사진,국악,음악,문인,미술,연예,연극,무용,영화17901경기도 평택시 비전동 847번지경기도 평택시 중앙로 27736.991121127.114077
592024포천시포천지회시군예총황의출사진,국악,문인,미술,연예,연극,무용,영화11151경기도 포천시 군내면 하성북리 610번지경기도 포천시 군내면 청성로 11137.896117127.212447
602024하남시하남지회시군예총김부경사진,국악,음악,문인,미술,연예,연극,무용,영화12932경기도 하남시 덕풍동 224-10번지경기도 하남시 덕풍로81번길 1237.551301127.203792
612024하남시하남지부민예총장윤영<NA>12950경기도 하남시 신장동 407-5번지경기도 하남시 하남대로784번길 1037.540313127.211023
622024화성시화성지부민예총김정오<NA>18304경기도 화성시 봉담읍 수영리 692번지 화성봉담2LH3단지 308동 1층경기도 화성시 봉담읍 상리3길 13537.224903126.951438
632024화성시화성지회시군예총박종섭사진,국악,음악,문인,미술,연예,연극,무용,영화18459경기도 화성시 반송동 108번지경기도 화성시 노작로 13437.200704127.075015