Overview

Dataset statistics

Number of variables16
Number of observations128
Missing cells79
Missing cells (%)3.9%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory17.0 KiB
Average record size in memory136.0 B

Variable types

Categorical10
Text3
Numeric3

Dataset

Description안양시 관내 상업용 현수막 지정게시대 설치현황(관내 상업용 현수막 지정 게시대명칭, 관내 상업용 현수막 지정 게시대 행정동, 관내 상업용 현수막 지정 게시대 부착일수, 관내 상업용 현수막 지정 게시대 금액 등)데이터 정보입니다.
URLhttps://www.data.go.kr/data/15055486/fileData.do

Alerts

시군명 has constant value ""Constant
현수막규격(높이) has constant value ""Constant
데이터기준일자 has constant value ""Constant
용도구분 is highly overall correlated with 게시면수(행정용) and 3 other fieldsHigh correlation
관리기관전화번호 is highly overall correlated with 경도 and 3 other fieldsHigh correlation
부착일수 is highly overall correlated with 게시면수(행정용) and 3 other fieldsHigh correlation
위도 is highly overall correlated with 읍면동명High correlation
경도 is highly overall correlated with 읍면동명 and 1 other fieldsHigh correlation
게시면수(행정용) is highly overall correlated with 용도구분 and 2 other fieldsHigh correlation
읍면동명 is highly overall correlated with 위도 and 2 other fieldsHigh correlation
현수막규격(너비) is highly overall correlated with 게시면수(행정용)High correlation
관리기관명 is highly overall correlated with 읍면동명 and 3 other fieldsHigh correlation
게시대수 is highly imbalanced (61.6%)Imbalance
소재지도로명주소 has 19 (14.8%) missing valuesMissing
게시면수(행정용) has 60 (46.9%) missing valuesMissing

Reproduction

Analysis started2023-12-12 23:10:52.383638
Analysis finished2023-12-12 23:10:55.155082
Duration2.77 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

시군명
Categorical

CONSTANT 

Distinct1
Distinct (%)0.8%
Missing0
Missing (%)0.0%
Memory size1.1 KiB
안양시
128 

Length

Max length3
Median length3
Mean length3
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
안양시 128
100.0%

Length

2023-12-13T08:10:55.216914image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T08:10:55.318618image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
안양시 128
100.0%

읍면동명
Categorical

HIGH CORRELATION 

Distinct30
Distinct (%)23.4%
Missing0
Missing (%)0.0%
Memory size1.1 KiB
안양7동
11 
석수2동
11 
비산3동
 
8
귀인동
 
8
안양5동
 
7
Other values (25)
83 

Length

Max length4
Median length4
Mean length3.6640625
Min length3

Unique

Unique3 ?
Unique (%)2.3%

Sample

1st row달안동
2nd row부흥동
3rd row비산3동
4th row비산3동
5th row귀인동

Common Values

ValueCountFrequency (%)
안양7동 11
 
8.6%
석수2동 11
 
8.6%
비산3동 8
 
6.2%
귀인동 8
 
6.2%
안양5동 7
 
5.5%
안양6동 7
 
5.5%
부림동 6
 
4.7%
평안동 6
 
4.7%
달안동 5
 
3.9%
관양1동 5
 
3.9%
Other values (20) 54
42.2%

Length

2023-12-13T08:10:55.443444image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
안양7동 11
 
8.6%
석수2동 11
 
8.6%
비산3동 8
 
6.2%
귀인동 8
 
6.2%
안양5동 7
 
5.5%
안양6동 7
 
5.5%
부림동 6
 
4.7%
평안동 6
 
4.7%
갈산동 5
 
3.9%
안양2동 5
 
3.9%
Other values (20) 54
42.2%

용도구분
Categorical

HIGH CORRELATION 

Distinct2
Distinct (%)1.6%
Missing0
Missing (%)0.0%
Memory size1.1 KiB
행정용
68 
상업용
60 

Length

Max length3
Median length3
Mean length3
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
행정용 68
53.1%
상업용 60
46.9%

Length

2023-12-13T08:10:55.592617image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T08:10:55.692174image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
행정용 68
53.1%
상업용 60
46.9%

게시대명
Text

Distinct125
Distinct (%)97.7%
Missing0
Missing (%)0.0%
Memory size1.1 KiB
2023-12-13T08:10:56.001694image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length15
Median length11
Mean length7.7421875
Min length3

Characters and Unicode

Total characters991
Distinct characters157
Distinct categories7 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique123 ?
Unique (%)96.1%

Sample

1st row동안구청 앞
2nd row동안경찰서 앞
3rd row운곡공원 앞
4th row운곡공원 앞(운동장 사거리)
5th row농수산물 삼거리
ValueCountFrequency (%)
앞 45
 
20.5%
행정복지센터 12
 
5.5%
주민센터 11
 
5.0%
옆 3
 
1.4%
입구 3
 
1.4%
석수1동 3
 
1.4%
사거리 3
 
1.4%
학원가사거리 3
 
1.4%
안양3동 2
 
0.9%
학운교 2
 
0.9%
Other values (123) 132
60.3%
2023-12-13T08:10:56.464511image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
91
 
9.2%
앞 52
 
5.2%
리 40
 
4.0%
거 38
 
3.8%
동 32
 
3.2%
사 31
 
3.1%
안 27
 
2.7%
터 26
 
2.6%
센 25
 
2.5%
양 22
 
2.2%
Other values (147) 607
61.3%

Most occurring categories

ValueCountFrequency (%)
Other Letter 832
84.0%
Space Separator 91
 
9.2%
Uppercase Letter 37
 
3.7%
Decimal Number 20
 
2.0%
Close Punctuation 5
 
0.5%
Open Punctuation 4
 
0.4%
Other Punctuation 2
 
0.2%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
앞 52
 
6.2%
리 40
 
4.8%
거 38
 
4.6%
동 32
 
3.8%
사 31
 
3.7%
안 27
 
3.2%
터 26
 
3.1%
센 25
 
3.0%
양 22
 
2.6%
교 22
 
2.6%
Other values (130) 517
62.1%
Decimal Number
ValueCountFrequency (%)
1 5
25.0%
3 5
25.0%
2 4
20.0%
7 2
 
10.0%
6 1
 
5.0%
4 1
 
5.0%
5 1
 
5.0%
9 1
 
5.0%
Uppercase Letter
ValueCountFrequency (%)
A 15
40.5%
B 15
40.5%
C 3
 
8.1%
T 2
 
5.4%
K 2
 
5.4%
Space Separator
ValueCountFrequency (%)
91
100.0%
Close Punctuation
ValueCountFrequency (%)
) 5
100.0%
Open Punctuation
ValueCountFrequency (%)
( 4
100.0%
Other Punctuation
ValueCountFrequency (%)
, 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 832
84.0%
Common 122
 
12.3%
Latin 37
 
3.7%

Most frequent character per script

Hangul
ValueCountFrequency (%)
앞 52
 
6.2%
리 40
 
4.8%
거 38
 
4.6%
동 32
 
3.8%
사 31
 
3.7%
안 27
 
3.2%
터 26
 
3.1%
센 25
 
3.0%
양 22
 
2.6%
교 22
 
2.6%
Other values (130) 517
62.1%
Common
ValueCountFrequency (%)
91
74.6%
) 5
 
4.1%
1 5
 
4.1%
3 5
 
4.1%
2 4
 
3.3%
( 4
 
3.3%
7 2
 
1.6%
, 2
 
1.6%
6 1
 
0.8%
4 1
 
0.8%
Other values (2) 2
 
1.6%
Latin
ValueCountFrequency (%)
A 15
40.5%
B 15
40.5%
C 3
 
8.1%
T 2
 
5.4%
K 2
 
5.4%

Most occurring blocks

ValueCountFrequency (%)
Hangul 832
84.0%
ASCII 159
 
16.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
91
57.2%
A 15
 
9.4%
B 15
 
9.4%
) 5
 
3.1%
1 5
 
3.1%
3 5
 
3.1%
2 4
 
2.5%
( 4
 
2.5%
C 3
 
1.9%
T 2
 
1.3%
Other values (7) 10
 
6.3%
Hangul
ValueCountFrequency (%)
앞 52
 
6.2%
리 40
 
4.8%
거 38
 
4.6%
동 32
 
3.8%
사 31
 
3.7%
안 27
 
3.2%
터 26
 
3.1%
센 25
 
3.0%
양 22
 
2.6%
교 22
 
2.6%
Other values (130) 517
62.1%

소재지도로명주소
Text

MISSING 

Distinct87
Distinct (%)79.8%
Missing19
Missing (%)14.8%
Memory size1.1 KiB
2023-12-13T08:10:56.814955image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length30
Median length27
Mean length19.623853
Min length15

Characters and Unicode

Total characters2139
Distinct characters78
Distinct categories6 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique71 ?
Unique (%)65.1%

Sample

1st row경기도 안양시 동안구 동안로 158
2nd row경기도 안양시 동안구 동안로159번길 43
3rd row경기도 안양시 동안구 249-6
4th row경기도 안양시 동안구 평촌대로 367번길29(비산동)]
5th row경기도 안양시 동안구 평촌대로 367번길29(비산동)]
ValueCountFrequency (%)
경기도 109
20.1%
안양시 109
20.1%
만안구 55
 
10.1%
동안구 54
 
9.9%
안양로 17
 
3.1%
평촌대로 7
 
1.3%
시민대로 6
 
1.1%
관악대로 6
 
1.1%
경수대로 5
 
0.9%
연현로 5
 
0.9%
Other values (114) 170
31.3%
2023-12-13T08:10:57.389780image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
435
20.3%
안 254
11.9%
양 134
 
6.3%
시 116
 
5.4%
경 114
 
5.3%
구 109
 
5.1%
기 109
 
5.1%
도 109
 
5.1%
로 107
 
5.0%
동 61
 
2.9%
Other values (68) 591
27.6%

Most occurring categories

ValueCountFrequency (%)
Other Letter 1381
64.6%
Space Separator 435
 
20.3%
Decimal Number 313
 
14.6%
Dash Punctuation 4
 
0.2%
Close Punctuation 4
 
0.2%
Open Punctuation 2
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
안 254
18.4%
양 134
9.7%
시 116
8.4%
경 114
8.3%
구 109
7.9%
기 109
7.9%
도 109
7.9%
로 107
7.7%
동 61
 
4.4%
만 57
 
4.1%
Other values (53) 211
15.3%
Decimal Number
ValueCountFrequency (%)
2 57
18.2%
1 55
17.6%
3 43
13.7%
4 29
9.3%
5 29
9.3%
9 25
8.0%
6 23
7.3%
7 19
 
6.1%
8 18
 
5.8%
0 15
 
4.8%
Close Punctuation
ValueCountFrequency (%)
] 2
50.0%
) 2
50.0%
Space Separator
ValueCountFrequency (%)
435
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 4
100.0%
Open Punctuation
ValueCountFrequency (%)
( 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 1381
64.6%
Common 758
35.4%

Most frequent character per script

Hangul
ValueCountFrequency (%)
안 254
18.4%
양 134
9.7%
시 116
8.4%
경 114
8.3%
구 109
7.9%
기 109
7.9%
도 109
7.9%
로 107
7.7%
동 61
 
4.4%
만 57
 
4.1%
Other values (53) 211
15.3%
Common
ValueCountFrequency (%)
435
57.4%
2 57
 
7.5%
1 55
 
7.3%
3 43
 
5.7%
4 29
 
3.8%
5 29
 
3.8%
9 25
 
3.3%
6 23
 
3.0%
7 19
 
2.5%
8 18
 
2.4%
Other values (5) 25
 
3.3%

Most occurring blocks

ValueCountFrequency (%)
Hangul 1381
64.6%
ASCII 758
35.4%

Most frequent character per block

ASCII
ValueCountFrequency (%)
435
57.4%
2 57
 
7.5%
1 55
 
7.3%
3 43
 
5.7%
4 29
 
3.8%
5 29
 
3.8%
9 25
 
3.3%
6 23
 
3.0%
7 19
 
2.5%
8 18
 
2.4%
Other values (5) 25
 
3.3%
Hangul
ValueCountFrequency (%)
안 254
18.4%
양 134
9.7%
시 116
8.4%
경 114
8.3%
구 109
7.9%
기 109
7.9%
도 109
7.9%
로 107
7.7%
동 61
 
4.4%
만 57
 
4.1%
Other values (53) 211
15.3%

소재지지번주소
Text

Distinct104
Distinct (%)81.2%
Missing0
Missing (%)0.0%
Memory size1.1 KiB
2023-12-13T08:10:57.734264image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length33
Median length30
Mean length21.523438
Min length12

Characters and Unicode

Total characters2755
Distinct characters71
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

Unique84 ?
Unique (%)65.6%

Sample

1st row경기도 안양시 동안구 비산동 1111
2nd row경기도 안양시 동안구 비산동 1105
3rd row경기도 안양시 동안구 비산동 249-6
4th row경기도 안양시 동안구 비산동 249-6
5th row경기도 안양시 동안구 평촌동 985
ValueCountFrequency (%)
경기도 128
19.8%
안양시 128
19.8%
동안구 69
10.7%
만안구 58
 
9.0%
안양동 38
 
5.9%
비산동 21
 
3.2%
평촌동 17
 
2.6%
석수동 15
 
2.3%
관양동 13
 
2.0%
호계동 12
 
1.9%
Other values (116) 148
22.9%
2023-12-13T08:10:58.216607image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
544
19.7%
안 295
 
10.7%
동 196
 
7.1%
양 183
 
6.6%
도 129
 
4.7%
시 129
 
4.7%
기 128
 
4.6%
경 128
 
4.6%
구 127
 
4.6%
1 125
 
4.5%
Other values (61) 771
28.0%

Most occurring categories

ValueCountFrequency (%)
Other Letter 1599
58.0%
Space Separator 544
 
19.7%
Decimal Number 528
 
19.2%
Dash Punctuation 84
 
3.0%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
안 295
18.4%
동 196
12.3%
양 183
11.4%
도 129
8.1%
시 129
8.1%
기 128
8.0%
경 128
8.0%
구 127
7.9%
만 58
 
3.6%
산 22
 
1.4%
Other values (49) 204
12.8%
Decimal Number
ValueCountFrequency (%)
1 125
23.7%
4 56
10.6%
2 54
10.2%
5 50
 
9.5%
3 50
 
9.5%
9 47
 
8.9%
0 42
 
8.0%
8 37
 
7.0%
6 37
 
7.0%
7 30
 
5.7%
Space Separator
ValueCountFrequency (%)
544
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 84
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 1599
58.0%
Common 1156
42.0%

Most frequent character per script

Hangul
ValueCountFrequency (%)
안 295
18.4%
동 196
12.3%
양 183
11.4%
도 129
8.1%
시 129
8.1%
기 128
8.0%
경 128
8.0%
구 127
7.9%
만 58
 
3.6%
산 22
 
1.4%
Other values (49) 204
12.8%
Common
ValueCountFrequency (%)
544
47.1%
1 125
 
10.8%
- 84
 
7.3%
4 56
 
4.8%
2 54
 
4.7%
5 50
 
4.3%
3 50
 
4.3%
9 47
 
4.1%
0 42
 
3.6%
8 37
 
3.2%
Other values (2) 67
 
5.8%

Most occurring blocks

ValueCountFrequency (%)
Hangul 1599
58.0%
ASCII 1156
42.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
544
47.1%
1 125
 
10.8%
- 84
 
7.3%
4 56
 
4.8%
2 54
 
4.7%
5 50
 
4.3%
3 50
 
4.3%
9 47
 
4.1%
0 42
 
3.6%
8 37
 
3.2%
Other values (2) 67
 
5.8%
Hangul
ValueCountFrequency (%)
안 295
18.4%
동 196
12.3%
양 183
11.4%
도 129
8.1%
시 129
8.1%
기 128
8.0%
경 128
8.0%
구 127
7.9%
만 58
 
3.6%
산 22
 
1.4%
Other values (49) 204
12.8%

위도
Real number (ℝ)

HIGH CORRELATION 

Distinct108
Distinct (%)84.4%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean37.396152
Minimum37.367685
Maximum37.432571
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.3 KiB
2023-12-13T08:10:58.394490image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum37.367685
5-th percentile37.37693
Q137.38698
median37.395213
Q337.402797
95-th percentile37.41996
Maximum37.432571
Range0.064886
Interquartile range (IQR)0.0158175

Descriptive statistics

Standard deviation0.012699246
Coefficient of variation (CV)0.00033958696
Kurtosis0.47304695
Mean37.396152
Median Absolute Deviation (MAD)0.0078075
Skewness0.4940518
Sum4786.7075
Variance0.00016127084
MonotonicityNot monotonic
2023-12-13T08:10:58.574830image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
37.38398 3
 
2.3%
37.396283 2
 
1.6%
37.403295 2
 
1.6%
37.40105 2
 
1.6%
37.402954 2
 
1.6%
37.383103 2
 
1.6%
37.382892 2
 
1.6%
37.390137 2
 
1.6%
37.408253 2
 
1.6%
37.393791 2
 
1.6%
Other values (98) 107
83.6%
ValueCountFrequency (%)
37.367685 1
0.8%
37.370149 1
0.8%
37.371516 2
1.6%
37.376145 1
0.8%
37.376471 1
0.8%
37.376918 1
0.8%
37.376953 1
0.8%
37.379838 1
0.8%
37.379862 1
0.8%
37.379983 1
0.8%
ValueCountFrequency (%)
37.432571 2
1.6%
37.426656 1
0.8%
37.425453 2
1.6%
37.420138 2
1.6%
37.419628 2
1.6%
37.419625 1
0.8%
37.415937 1
0.8%
37.41287 1
0.8%
37.41112 1
0.8%
37.410746 1
0.8%

경도
Real number (ℝ)

HIGH CORRELATION 

Distinct109
Distinct (%)85.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean126.9407
Minimum126.89881
Maximum126.97708
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.3 KiB
2023-12-13T08:10:58.752208image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum126.89881
5-th percentile126.90423
Q1126.92505
median126.945
Q3126.95985
95-th percentile126.97213
Maximum126.97708
Range0.078271
Interquartile range (IQR)0.034795

Descriptive statistics

Standard deviation0.022391408
Coefficient of variation (CV)0.00017639266
Kurtosis-1.1793795
Mean126.9407
Median Absolute Deviation (MAD)0.019001
Skewness-0.19653012
Sum16248.41
Variance0.00050137515
MonotonicityNot monotonic
2023-12-13T08:10:58.930724image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
126.936201 3
 
2.3%
126.91062 3
 
2.3%
126.961329 2
 
1.6%
126.913188 2
 
1.6%
126.930688 2
 
1.6%
126.95287 2
 
1.6%
126.925443 2
 
1.6%
126.964366 2
 
1.6%
126.970485 2
 
1.6%
126.925052 2
 
1.6%
Other values (99) 106
82.8%
ValueCountFrequency (%)
126.898813 1
0.8%
126.901514 1
0.8%
126.901524 1
0.8%
126.902227 2
1.6%
126.903601 1
0.8%
126.904229 2
1.6%
126.906977 1
0.8%
126.907025 1
0.8%
126.907289 2
1.6%
126.908583 2
1.6%
ValueCountFrequency (%)
126.977084 1
0.8%
126.976742 2
1.6%
126.976568 1
0.8%
126.976262 1
0.8%
126.972244 1
0.8%
126.972161 1
0.8%
126.972074 1
0.8%
126.971 1
0.8%
126.970485 2
1.6%
126.970173 1
0.8%

게시대수
Categorical

IMBALANCE 

Distinct3
Distinct (%)2.3%
Missing0
Missing (%)0.0%
Memory size1.1 KiB
1
111 
2
16 
4
 
1

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique1 ?
Unique (%)0.8%

Sample

1st row1
2nd row1
3rd row1
4th row2
5th row1

Common Values

ValueCountFrequency (%)
1 111
86.7%
2 16
 
12.5%
4 1
 
0.8%

Length

2023-12-13T08:10:59.109928image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T08:10:59.225726image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
1 111
86.7%
2 16
 
12.5%
4 1
 
0.8%

현수막규격(너비)
Categorical

HIGH CORRELATION 

Distinct2
Distinct (%)1.6%
Missing0
Missing (%)0.0%
Memory size1.1 KiB
600
95 
580
33 

Length

Max length3
Median length3
Mean length3
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row600
2nd row600
3rd row600
4th row600
5th row600

Common Values

ValueCountFrequency (%)
600 95
74.2%
580 33
 
25.8%

Length

2023-12-13T08:10:59.355716image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T08:10:59.450878image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
600 95
74.2%
580 33
 
25.8%

현수막규격(높이)
Categorical

CONSTANT 

Distinct1
Distinct (%)0.8%
Missing0
Missing (%)0.0%
Memory size1.1 KiB
70
128 

Length

Max length2
Median length2
Mean length2
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row70
2nd row70
3rd row70
4th row70
5th row70

Common Values

ValueCountFrequency (%)
70 128
100.0%

Length

2023-12-13T08:10:59.549415image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T08:10:59.655441image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
70 128
100.0%

게시면수(행정용)
Real number (ℝ)

HIGH CORRELATION  MISSING 

Distinct6
Distinct (%)8.8%
Missing60
Missing (%)46.9%
Infinite0
Infinite (%)0.0%
Mean4.2941176
Minimum2
Maximum7
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.3 KiB
2023-12-13T08:10:59.755108image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum2
5-th percentile2
Q12
median5.5
Q36
95-th percentile6
Maximum7
Range5
Interquartile range (IQR)4

Descriptive statistics

Standard deviation1.8613013
Coefficient of variation (CV)0.43345373
Kurtosis-1.8040546
Mean4.2941176
Median Absolute Deviation (MAD)1
Skewness-0.24453024
Sum292
Variance3.4644425
MonotonicityNot monotonic
2023-12-13T08:10:59.887649image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=6)
ValueCountFrequency (%)
6 33
25.8%
2 23
 
18.0%
4 6
 
4.7%
3 4
 
3.1%
5 1
 
0.8%
7 1
 
0.8%
(Missing) 60
46.9%
ValueCountFrequency (%)
2 23
18.0%
3 4
 
3.1%
4 6
 
4.7%
5 1
 
0.8%
6 33
25.8%
7 1
 
0.8%
ValueCountFrequency (%)
7 1
 
0.8%
6 33
25.8%
5 1
 
0.8%
4 6
 
4.7%
3 4
 
3.1%
2 23
18.0%

부착일수
Categorical

HIGH CORRELATION 

Distinct2
Distinct (%)1.6%
Missing0
Missing (%)0.0%
Memory size1.1 KiB
15
68 
7
60 

Length

Max length2
Median length2
Mean length1.53125
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row15
2nd row15
3rd row15
4th row15
5th row15

Common Values

ValueCountFrequency (%)
15 68
53.1%
7 60
46.9%

Length

2023-12-13T08:11:00.041144image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T08:11:00.174462image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
15 68
53.1%
7 60
46.9%

관리기관명
Categorical

HIGH CORRELATION 

Distinct29
Distinct (%)22.7%
Missing0
Missing (%)0.0%
Memory size1.1 KiB
광고물협회
60 
만안구청
15 
동안구청
7 
관양1동
 
4
평안동
 
4
Other values (24)
38 

Length

Max length5
Median length4
Mean length4.3125
Min length3

Unique

Unique15 ?
Unique (%)11.7%

Sample

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

Common Values

ValueCountFrequency (%)
광고물협회 60
46.9%
만안구청 15
 
11.7%
동안구청 7
 
5.5%
관양1동 4
 
3.1%
평안동 4
 
3.1%
부림동 3
 
2.3%
귀인동 3
 
2.3%
갈산동 3
 
2.3%
비산3동 3
 
2.3%
달안동 3
 
2.3%
Other values (19) 23
 
18.0%

Length

2023-12-13T08:11:00.325722image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
광고물협회 60
46.9%
만안구청 15
 
11.7%
동안구청 7
 
5.5%
관양1동 4
 
3.1%
평안동 4
 
3.1%
부림동 3
 
2.3%
귀인동 3
 
2.3%
갈산동 3
 
2.3%
비산3동 3
 
2.3%
달안동 3
 
2.3%
Other values (19) 23
 
18.0%

관리기관전화번호
Categorical

HIGH CORRELATION 

Distinct4
Distinct (%)3.1%
Missing0
Missing (%)0.0%
Memory size1.1 KiB
031-473-6663
60 
031-8045-4252
38 
031-8045-3251
29 
<NA>
 
1

Length

Max length13
Median length13
Mean length12.460938
Min length4

Unique

Unique1 ?
Unique (%)0.8%

Sample

1st row031-8045-4252
2nd row031-8045-4252
3rd row031-8045-4252
4th row031-8045-4252
5th row031-8045-4252

Common Values

ValueCountFrequency (%)
031-473-6663 60
46.9%
031-8045-4252 38
29.7%
031-8045-3251 29
22.7%
<NA> 1
 
0.8%

Length

2023-12-13T08:11:00.500800image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T08:11:00.643356image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
031-473-6663 60
46.9%
031-8045-4252 38
29.7%
031-8045-3251 29
22.7%
na 1
 
0.8%

데이터기준일자
Categorical

CONSTANT 

Distinct1
Distinct (%)0.8%
Missing0
Missing (%)0.0%
Memory size1.1 KiB
2023-07-12
128 

Length

Max length10
Median length10
Mean length10
Min length10

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row2023-07-12
2nd row2023-07-12
3rd row2023-07-12
4th row2023-07-12
5th row2023-07-12

Common Values

ValueCountFrequency (%)
2023-07-12 128
100.0%

Length

2023-12-13T08:11:00.808889image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T08:11:00.925257image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2023-07-12 128
100.0%

Interactions

2023-12-13T08:10:54.330384image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T08:10:53.631854image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T08:10:53.982115image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T08:10:54.439575image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T08:10:53.733454image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T08:10:54.107288image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T08:10:54.551961image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T08:10:53.856998image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T08:10:54.236390image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-13T08:11:01.020222image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
읍면동명용도구분소재지도로명주소위도경도게시대수현수막규격(너비)게시면수(행정용)부착일수관리기관명관리기관전화번호
읍면동명1.0000.0001.0000.9490.9620.0000.0000.4230.0000.9530.760
용도구분0.0001.0000.8430.2360.0370.0000.661NaN1.0001.0001.000
소재지도로명주소1.0000.8431.0000.9910.9990.9780.4930.0000.8430.9980.939
위도0.9490.2360.9911.0000.7960.2740.0000.0000.2360.5360.156
경도0.9620.0370.9990.7961.0000.0000.3460.2280.0370.7370.666
게시대수0.0000.0000.9780.2740.0001.0000.0000.0000.0000.0000.000
현수막규격(너비)0.0000.6610.4930.0000.3460.0001.0000.8690.6610.4400.305
게시면수(행정용)0.423NaN0.0000.0000.2280.0000.8691.000NaN0.0000.464
부착일수0.0001.0000.8430.2360.0370.0000.661NaN1.0001.0001.000
관리기관명0.9531.0000.9980.5360.7370.0000.4400.0001.0001.0001.000
관리기관전화번호0.7601.0000.9390.1560.6660.0000.3050.4641.0001.0001.000
2023-12-13T08:11:01.174708image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
용도구분읍면동명관리기관전화번호관리기관명부착일수현수막규격(너비)게시대수
용도구분1.0000.0000.9960.8860.9840.4600.000
읍면동명0.0001.0000.4390.5700.0000.0000.000
관리기관전화번호0.9960.4391.0000.8940.9960.4910.000
관리기관명0.8860.5700.8941.0000.8860.3320.000
부착일수0.9840.0000.9960.8861.0000.4600.000
현수막규격(너비)0.4600.0000.4910.3320.4601.0000.000
게시대수0.0000.0000.0000.0000.0000.0001.000
2023-12-13T08:11:01.312097image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
위도경도게시면수(행정용)읍면동명용도구분게시대수현수막규격(너비)부착일수관리기관명관리기관전화번호
위도1.000-0.4540.0710.6030.1740.1640.0000.1740.1980.088
경도-0.4541.000-0.3380.6430.0140.0000.2560.0140.3320.502
게시면수(행정용)0.071-0.3381.0000.1431.0000.0000.6581.0000.0000.323
읍면동명0.6030.6430.1431.0000.0000.0000.0000.0000.5700.439
용도구분0.1740.0141.0000.0001.0000.0000.4600.9840.8860.996
게시대수0.1640.0000.0000.0000.0001.0000.0000.0000.0000.000
현수막규격(너비)0.0000.2560.6580.0000.4600.0001.0000.4600.3320.491
부착일수0.1740.0141.0000.0000.9840.0000.4601.0000.8860.996
관리기관명0.1980.3320.0000.5700.8860.0000.3320.8861.0000.894
관리기관전화번호0.0880.5020.3230.4390.9960.0000.4910.9960.8941.000

Missing values

2023-12-13T08:10:54.700093image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-13T08:10:54.940193image/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.
2023-12-13T08:10:55.098042image/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

시군명읍면동명용도구분게시대명소재지도로명주소소재지지번주소위도경도게시대수현수막규격(너비)현수막규격(높이)게시면수(행정용)부착일수관리기관명관리기관전화번호데이터기준일자
0안양시달안동행정용동안구청 앞경기도 안양시 동안구 동안로 158경기도 안양시 동안구 비산동 111137.392512126.95121160070615동안구청031-8045-42522023-07-12
1안양시부흥동행정용동안경찰서 앞경기도 안양시 동안구 동안로159번길 43경기도 안양시 동안구 비산동 110537.3912126.948866160070615동안구청031-8045-42522023-07-12
2안양시비산3동행정용운곡공원 앞경기도 안양시 동안구 249-6경기도 안양시 동안구 비산동 249-637.402484126.948624160070615동안구청031-8045-42522023-07-12
3안양시비산3동행정용운곡공원 앞(운동장 사거리)경기도 안양시 동안구 평촌대로 367번길29(비산동)]경기도 안양시 동안구 비산동 249-637.402484126.948624260070215동안구청031-8045-42522023-07-12
4안양시귀인동행정용농수산물 삼거리경기도 안양시 동안구 평촌대로 367번길29(비산동)]경기도 안양시 동안구 평촌동 98537.383323126.967449160070215동안구청031-8045-42522023-07-12
5안양시비산2동행정용학운교경기도 안양시 동안구 관악대로 182경기도 안양시 동안구 비산동 918-337.398688126.944694160070215동안구청031-8045-42522023-07-12
6안양시부흥동행정용평화공원앞경기도 안양시 동안구 시민대로 169-2경기도 안양시 동안구 비산동 114537.39071126.949848160070215동안구청031-8045-42522023-07-12
7안양시비산3동행정용비산3동 주민센터 앞경기도 안양시 동안구 운곡로 34경기도 안양시 동안구 비산동 1061-637.404059126.945566160070615비산3동031-8045-42522023-07-12
8안양시비산3동행정용빙상경기장 앞경기도 안양시 동안구 운곡로경기도 안양시 동안구 비산동 106337.405386126.949789260070215비산3동031-8045-42522023-07-12
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