Overview

Dataset statistics

Number of variables10
Number of observations190
Missing cells190
Missing cells (%)10.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory15.7 KiB
Average record size in memory84.7 B

Variable types

Categorical4
Numeric3
Text3

Dataset

Description서울특별시 보행신호 음성안내 보조장치 설치현황에 대한 데이터로 자치구, 시설물 위치명, 도로명줒소, 지번주소, 설치연도, 설치형태(막대형, 지주부착형), 설치수량, 횡단보도수(면) 등의 항목이 있습니다.
Author서울특별시
URLhttps://www.data.go.kr/data/15080661/fileData.do

Alerts

번호 is highly overall correlated with 설치연도 and 1 other fieldsHigh correlation
설치연도 is highly overall correlated with 번호 and 3 other fieldsHigh correlation
설치수량(조) is highly overall correlated with 황단보도수(면) and 1 other fieldsHigh correlation
자치구 is highly overall correlated with 번호 and 3 other fieldsHigh correlation
설치형태(막대형, 지주부착형 등) is highly overall correlated with 설치연도 and 2 other fieldsHigh correlation
황단보도수(면) is highly overall correlated with 설치수량(조)High correlation
비고 is highly overall correlated with 설치연도 and 3 other fieldsHigh correlation
황단보도수(면) is highly imbalanced (57.2%)Imbalance
비고 is highly imbalanced (83.3%)Imbalance
도로명주소 has 95 (50.0%) missing valuesMissing
지번주소 has 95 (50.0%) missing valuesMissing
번호 has unique valuesUnique

Reproduction

Analysis started2023-12-12 04:40:08.340392
Analysis finished2023-12-12 04:40:10.807675
Duration2.47 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

자치구
Categorical

HIGH CORRELATION 

Distinct20
Distinct (%)10.5%
Missing0
Missing (%)0.0%
Memory size1.6 KiB
광진구
53 
관악구
23 
은평구
22 
성동구
16 
성북구
14 
Other values (15)
62 

Length

Max length4
Median length3
Mean length3.0052632
Min length2

Unique

Unique3 ?
Unique (%)1.6%

Sample

1st row중랑구
2nd row강서구
3rd row강서구
4th row관악구
5th row서초구

Common Values

ValueCountFrequency (%)
광진구 53
27.9%
관악구 23
12.1%
은평구 22
11.6%
성동구 16
 
8.4%
성북구 14
 
7.4%
송파구 12
 
6.3%
노원구 10
 
5.3%
마포구 9
 
4.7%
금천구 5
 
2.6%
강남구 4
 
2.1%
Other values (10) 22
11.6%

Length

2023-12-12T13:40:10.935818image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
광진구 53
27.9%
관악구 23
12.1%
은평구 22
11.6%
성동구 16
 
8.4%
성북구 14
 
7.4%
송파구 12
 
6.3%
노원구 10
 
5.3%
마포구 9
 
4.7%
금천구 5
 
2.6%
용산구 4
 
2.1%
Other values (10) 22
11.6%

번호
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct190
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean95.5
Minimum1
Maximum190
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.8 KiB
2023-12-12T13:40:11.148187image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile10.45
Q148.25
median95.5
Q3142.75
95-th percentile180.55
Maximum190
Range189
Interquartile range (IQR)94.5

Descriptive statistics

Standard deviation54.992424
Coefficient of variation (CV)0.5758369
Kurtosis-1.2
Mean95.5
Median Absolute Deviation (MAD)47.5
Skewness0
Sum18145
Variance3024.1667
MonotonicityStrictly increasing
2023-12-12T13:40:11.369190image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1 1
 
0.5%
132 1
 
0.5%
123 1
 
0.5%
124 1
 
0.5%
125 1
 
0.5%
126 1
 
0.5%
127 1
 
0.5%
128 1
 
0.5%
129 1
 
0.5%
130 1
 
0.5%
Other values (180) 180
94.7%
ValueCountFrequency (%)
1 1
0.5%
2 1
0.5%
3 1
0.5%
4 1
0.5%
5 1
0.5%
6 1
0.5%
7 1
0.5%
8 1
0.5%
9 1
0.5%
10 1
0.5%
ValueCountFrequency (%)
190 1
0.5%
189 1
0.5%
188 1
0.5%
187 1
0.5%
186 1
0.5%
185 1
0.5%
184 1
0.5%
183 1
0.5%
182 1
0.5%
181 1
0.5%

시설물 위치명
Text

Distinct168
Distinct (%)88.4%
Missing0
Missing (%)0.0%
Memory size1.6 KiB
2023-12-12T13:40:11.729201image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length16
Median length14
Mean length5.8473684
Min length3

Characters and Unicode

Total characters1111
Distinct characters184
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

Unique150 ?
Unique (%)78.9%

Sample

1st row상봉역앞(6번출구, 5번출구)
2nd row월정초등학교
3rd row송화초등학교
4th row신림초등학교
5th row청계산SH702동앞(연등)
ValueCountFrequency (%)
앞 12
 
5.2%
주변 5
 
2.1%
신양초등학교 4
 
1.7%
정문 4
 
1.7%
자료없음 4
 
1.7%
중광초등학교 3
 
1.3%
교차로 3
 
1.3%
혜화초교 2
 
0.9%
광진초등학교 2
 
0.9%
강변역 2
 
0.9%
Other values (175) 192
82.4%
2023-12-12T13:40:12.308304image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
교 139
 
12.5%
초 132
 
11.9%
등 64
 
5.8%
학 63
 
5.7%
44
 
4.0%
신 24
 
2.2%
중 16
 
1.4%
광 16
 
1.4%
구 15
 
1.4%
성 15
 
1.4%
Other values (174) 583
52.5%

Most occurring categories

ValueCountFrequency (%)
Other Letter 1032
92.9%
Space Separator 44
 
4.0%
Decimal Number 17
 
1.5%
Other Punctuation 6
 
0.5%
Close Punctuation 5
 
0.5%
Open Punctuation 5
 
0.5%
Uppercase Letter 2
 
0.2%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
교 139
 
13.5%
초 132
 
12.8%
등 64
 
6.2%
학 63
 
6.1%
신 24
 
2.3%
중 16
 
1.6%
광 16
 
1.6%
구 15
 
1.5%
성 15
 
1.5%
앞 14
 
1.4%
Other values (160) 534
51.7%
Decimal Number
ValueCountFrequency (%)
1 6
35.3%
2 5
29.4%
5 2
 
11.8%
4 1
 
5.9%
6 1
 
5.9%
0 1
 
5.9%
7 1
 
5.9%
Other Punctuation
ValueCountFrequency (%)
, 5
83.3%
@ 1
 
16.7%
Uppercase Letter
ValueCountFrequency (%)
H 1
50.0%
S 1
50.0%
Space Separator
ValueCountFrequency (%)
44
100.0%
Close Punctuation
ValueCountFrequency (%)
) 5
100.0%
Open Punctuation
ValueCountFrequency (%)
( 5
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 1032
92.9%
Common 77
 
6.9%
Latin 2
 
0.2%

Most frequent character per script

Hangul
ValueCountFrequency (%)
교 139
 
13.5%
초 132
 
12.8%
등 64
 
6.2%
학 63
 
6.1%
신 24
 
2.3%
중 16
 
1.6%
광 16
 
1.6%
구 15
 
1.5%
성 15
 
1.5%
앞 14
 
1.4%
Other values (160) 534
51.7%
Common
ValueCountFrequency (%)
44
57.1%
1 6
 
7.8%
) 5
 
6.5%
, 5
 
6.5%
( 5
 
6.5%
2 5
 
6.5%
5 2
 
2.6%
4 1
 
1.3%
6 1
 
1.3%
0 1
 
1.3%
Other values (2) 2
 
2.6%
Latin
ValueCountFrequency (%)
H 1
50.0%
S 1
50.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 1032
92.9%
ASCII 79
 
7.1%

Most frequent character per block

Hangul
ValueCountFrequency (%)
교 139
 
13.5%
초 132
 
12.8%
등 64
 
6.2%
학 63
 
6.1%
신 24
 
2.3%
중 16
 
1.6%
광 16
 
1.6%
구 15
 
1.5%
성 15
 
1.5%
앞 14
 
1.4%
Other values (160) 534
51.7%
ASCII
ValueCountFrequency (%)
44
55.7%
1 6
 
7.6%
) 5
 
6.3%
, 5
 
6.3%
( 5
 
6.3%
2 5
 
6.3%
5 2
 
2.5%
4 1
 
1.3%
6 1
 
1.3%
0 1
 
1.3%
Other values (4) 4
 
5.1%

도로명주소
Text

MISSING 

Distinct94
Distinct (%)98.9%
Missing95
Missing (%)50.0%
Memory size1.6 KiB
2023-12-12T13:40:13.134091image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length30
Median length29
Mean length18.842105
Min length15

Characters and Unicode

Total characters1790
Distinct characters144
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

Unique93 ?
Unique (%)97.9%

Sample

1st row서울특별시 중랑구 망우로 293
2nd row서울특별시 강서구 방화대로 319
3rd row서울특별시 관악구 문성로 214
4th row서울특별시 서초구 청계산로 11길
5th row서울특별시 서초구 나루터로 15
ValueCountFrequency (%)
서울특별시 95
24.4%
관악구 23
 
5.9%
은평구 19
 
4.9%
성북구 12
 
3.1%
마포구 9
 
2.3%
앞 7
 
1.8%
문성로 6
 
1.5%
금천구 5
 
1.3%
성동구 5
 
1.3%
연서로 4
 
1.0%
Other values (166) 205
52.6%
2023-12-12T13:40:13.795057image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
296
16.5%
서 105
 
5.9%
구 96
 
5.4%
로 96
 
5.4%
특 95
 
5.3%
별 95
 
5.3%
시 95
 
5.3%
울 95
 
5.3%
1 60
 
3.4%
3 38
 
2.1%
Other values (134) 719
40.2%

Most occurring categories

ValueCountFrequency (%)
Other Letter 1178
65.8%
Space Separator 296
 
16.5%
Decimal Number 272
 
15.2%
Close Punctuation 17
 
0.9%
Open Punctuation 17
 
0.9%
Dash Punctuation 10
 
0.6%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
서 105
 
8.9%
구 96
 
8.1%
로 96
 
8.1%
특 95
 
8.1%
별 95
 
8.1%
시 95
 
8.1%
울 95
 
8.1%
성 30
 
2.5%
관 25
 
2.1%
악 25
 
2.1%
Other values (120) 421
35.7%
Decimal Number
ValueCountFrequency (%)
1 60
22.1%
3 38
14.0%
2 38
14.0%
6 26
9.6%
4 24
 
8.8%
5 22
 
8.1%
7 18
 
6.6%
9 17
 
6.2%
0 17
 
6.2%
8 12
 
4.4%
Space Separator
ValueCountFrequency (%)
296
100.0%
Close Punctuation
ValueCountFrequency (%)
) 17
100.0%
Open Punctuation
ValueCountFrequency (%)
( 17
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 10
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 1178
65.8%
Common 612
34.2%

Most frequent character per script

Hangul
ValueCountFrequency (%)
서 105
 
8.9%
구 96
 
8.1%
로 96
 
8.1%
특 95
 
8.1%
별 95
 
8.1%
시 95
 
8.1%
울 95
 
8.1%
성 30
 
2.5%
관 25
 
2.1%
악 25
 
2.1%
Other values (120) 421
35.7%
Common
ValueCountFrequency (%)
296
48.4%
1 60
 
9.8%
3 38
 
6.2%
2 38
 
6.2%
6 26
 
4.2%
4 24
 
3.9%
5 22
 
3.6%
7 18
 
2.9%
) 17
 
2.8%
9 17
 
2.8%
Other values (4) 56
 
9.2%

Most occurring blocks

ValueCountFrequency (%)
Hangul 1178
65.8%
ASCII 612
34.2%

Most frequent character per block

ASCII
ValueCountFrequency (%)
296
48.4%
1 60
 
9.8%
3 38
 
6.2%
2 38
 
6.2%
6 26
 
4.2%
4 24
 
3.9%
5 22
 
3.6%
7 18
 
2.9%
) 17
 
2.8%
9 17
 
2.8%
Other values (4) 56
 
9.2%
Hangul
ValueCountFrequency (%)
서 105
 
8.9%
구 96
 
8.1%
로 96
 
8.1%
특 95
 
8.1%
별 95
 
8.1%
시 95
 
8.1%
울 95
 
8.1%
성 30
 
2.5%
관 25
 
2.1%
악 25
 
2.1%
Other values (120) 421
35.7%

지번주소
Text

MISSING 

Distinct94
Distinct (%)98.9%
Missing95
Missing (%)50.0%
Memory size1.6 KiB
2023-12-12T13:40:14.187432image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length28
Median length24
Mean length19.242105
Min length16

Characters and Unicode

Total characters1828
Distinct characters82
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

Unique93 ?
Unique (%)97.9%

Sample

1st row서울특별시 강서구 화곡1동 374
2nd row서울특별시 광진구 능동 339-2
3rd row서울특별시 광진구 구의동 216-15
4th row서울특별시 광진구 중곡동 292
5th row서울특별시 광진구 중곡동 140-29
ValueCountFrequency (%)
서울특별시 95
24.9%
광진구 52
 
13.6%
자양동 13
 
3.4%
구의동 12
 
3.1%
송파구 12
 
3.1%
성동구 11
 
2.9%
노원구 10
 
2.6%
중곡동 9
 
2.4%
광장동 7
 
1.8%
화양동 4
 
1.0%
Other values (127) 156
40.9%
2023-12-12T13:40:14.686427image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
298
16.3%
구 107
 
5.9%
동 106
 
5.8%
서 96
 
5.3%
특 95
 
5.2%
별 95
 
5.2%
시 95
 
5.2%
울 95
 
5.2%
- 79
 
4.3%
광 60
 
3.3%
Other values (72) 702
38.4%

Most occurring categories

ValueCountFrequency (%)
Other Letter 1057
57.8%
Decimal Number 388
 
21.2%
Space Separator 298
 
16.3%
Dash Punctuation 79
 
4.3%
Close Punctuation 3
 
0.2%
Open Punctuation 3
 
0.2%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
구 107
10.1%
동 106
10.0%
서 96
9.1%
특 95
9.0%
별 95
9.0%
시 95
9.0%
울 95
9.0%
광 60
 
5.7%
진 54
 
5.1%
양 17
 
1.6%
Other values (58) 237
22.4%
Decimal Number
ValueCountFrequency (%)
1 56
14.4%
2 52
13.4%
3 50
12.9%
5 44
11.3%
6 42
10.8%
4 38
9.8%
7 33
8.5%
0 28
7.2%
8 24
6.2%
9 21
 
5.4%
Space Separator
ValueCountFrequency (%)
298
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 79
100.0%
Close Punctuation
ValueCountFrequency (%)
) 3
100.0%
Open Punctuation
ValueCountFrequency (%)
( 3
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 1057
57.8%
Common 771
42.2%

Most frequent character per script

Hangul
ValueCountFrequency (%)
구 107
10.1%
동 106
10.0%
서 96
9.1%
특 95
9.0%
별 95
9.0%
시 95
9.0%
울 95
9.0%
광 60
 
5.7%
진 54
 
5.1%
양 17
 
1.6%
Other values (58) 237
22.4%
Common
ValueCountFrequency (%)
298
38.7%
- 79
 
10.2%
1 56
 
7.3%
2 52
 
6.7%
3 50
 
6.5%
5 44
 
5.7%
6 42
 
5.4%
4 38
 
4.9%
7 33
 
4.3%
0 28
 
3.6%
Other values (4) 51
 
6.6%

Most occurring blocks

ValueCountFrequency (%)
Hangul 1057
57.8%
ASCII 771
42.2%

Most frequent character per block

ASCII
ValueCountFrequency (%)
298
38.7%
- 79
 
10.2%
1 56
 
7.3%
2 52
 
6.7%
3 50
 
6.5%
5 44
 
5.7%
6 42
 
5.4%
4 38
 
4.9%
7 33
 
4.3%
0 28
 
3.6%
Other values (4) 51
 
6.6%
Hangul
ValueCountFrequency (%)
구 107
10.1%
동 106
10.0%
서 96
9.1%
특 95
9.0%
별 95
9.0%
시 95
9.0%
울 95
9.0%
광 60
 
5.7%
진 54
 
5.1%
양 17
 
1.6%
Other values (58) 237
22.4%

설치연도
Real number (ℝ)

HIGH CORRELATION 

Distinct7
Distinct (%)3.7%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2019.0421
Minimum2013
Maximum2020
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.8 KiB
2023-12-12T13:40:14.803871image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum2013
5-th percentile2015
Q12019
median2020
Q32020
95-th percentile2020
Maximum2020
Range7
Interquartile range (IQR)1

Descriptive statistics

Standard deviation1.5930789
Coefficient of variation (CV)0.00078902707
Kurtosis3.3211164
Mean2019.0421
Median Absolute Deviation (MAD)0
Skewness-2.0137653
Sum383618
Variance2.5379003
MonotonicityNot monotonic
2023-12-12T13:40:14.898464image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=7)
ValueCountFrequency (%)
2020 109
57.4%
2019 44
23.2%
2015 15
 
7.9%
2018 14
 
7.4%
2017 5
 
2.6%
2013 2
 
1.1%
2014 1
 
0.5%
ValueCountFrequency (%)
2013 2
 
1.1%
2014 1
 
0.5%
2015 15
 
7.9%
2017 5
 
2.6%
2018 14
 
7.4%
2019 44
23.2%
2020 109
57.4%
ValueCountFrequency (%)
2020 109
57.4%
2019 44
23.2%
2018 14
 
7.4%
2017 5
 
2.6%
2015 15
 
7.9%
2014 1
 
0.5%
2013 2
 
1.1%

설치형태(막대형, 지주부착형 등)
Categorical

HIGH CORRELATION 

Distinct3
Distinct (%)1.6%
Missing0
Missing (%)0.0%
Memory size1.6 KiB
지주부착형
144 
막대형
42 
지주부착
 
4

Length

Max length5
Median length5
Mean length4.5368421
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
지주부착형 144
75.8%
막대형 42
 
22.1%
지주부착 4
 
2.1%

Length

2023-12-12T13:40:15.054671image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T13:40:15.187194image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
지주부착형 144
75.8%
막대형 42
 
22.1%
지주부착 4
 
2.1%

설치수량(조)
Real number (ℝ)

HIGH CORRELATION 

Distinct6
Distinct (%)3.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2.4157895
Minimum1
Maximum8
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.8 KiB
2023-12-12T13:40:15.299727image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q12
median2
Q32
95-th percentile6
Maximum8
Range7
Interquartile range (IQR)0

Descriptive statistics

Standard deviation1.3136496
Coefficient of variation (CV)0.54377653
Kurtosis7.068499
Mean2.4157895
Median Absolute Deviation (MAD)0
Skewness2.647802
Sum459
Variance1.7256753
MonotonicityNot monotonic
2023-12-12T13:40:15.430898image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=6)
ValueCountFrequency (%)
2 148
77.9%
4 14
 
7.4%
1 12
 
6.3%
6 9
 
4.7%
8 4
 
2.1%
3 3
 
1.6%
ValueCountFrequency (%)
1 12
 
6.3%
2 148
77.9%
3 3
 
1.6%
4 14
 
7.4%
6 9
 
4.7%
8 4
 
2.1%
ValueCountFrequency (%)
8 4
 
2.1%
6 9
 
4.7%
4 14
 
7.4%
3 3
 
1.6%
2 148
77.9%
1 12
 
6.3%

황단보도수(면)
Categorical

HIGH CORRELATION  IMBALANCE 

Distinct4
Distinct (%)2.1%
Missing0
Missing (%)0.0%
Memory size1.6 KiB
1
160 
2
 
16
3
 
9
4
 
5

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
1 160
84.2%
2 16
 
8.4%
3 9
 
4.7%
4 5
 
2.6%

Length

2023-12-12T13:40:15.555532image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T13:40:15.656655image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
1 160
84.2%
2 16
 
8.4%
3 9
 
4.7%
4 5
 
2.6%

비고
Categorical

HIGH CORRELATION  IMBALANCE 

Distinct3
Distinct (%)1.6%
Missing0
Missing (%)0.0%
Memory size1.6 KiB
<NA>
183 
시립용산노인종합복지관
 
4
서울민주주의위원회 지역공동체담당관
 
3

Length

Max length18
Median length4
Mean length4.3684211
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row<NA>
2nd row<NA>
3rd row<NA>
4th row<NA>
5th row<NA>

Common Values

ValueCountFrequency (%)
<NA> 183
96.3%
시립용산노인종합복지관 4
 
2.1%
서울민주주의위원회 지역공동체담당관 3
 
1.6%

Length

2023-12-12T13:40:15.764287image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T13:40:15.861106image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 183
94.8%
시립용산노인종합복지관 4
 
2.1%
서울민주주의위원회 3
 
1.6%
지역공동체담당관 3
 
1.6%

Interactions

2023-12-12T13:40:09.877461image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:40:08.968500image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:40:09.351919image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:40:10.075820image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:40:09.094922image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:40:09.468262image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:40:10.249737image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:40:09.220919image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:40:09.695775image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-12T13:40:15.955983image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
자치구번호도로명주소지번주소설치연도설치형태(막대형, 지주부착형 등)설치수량(조)황단보도수(면)비고
자치구1.0000.9731.0001.0000.9460.9550.1600.0000.850
번호0.9731.0001.0000.9640.7490.5600.2760.2360.270
도로명주소1.0001.0001.000NaN1.0001.0001.0001.000NaN
지번주소1.0000.964NaN1.0001.0001.0001.0001.0001.000
설치연도0.9460.7491.0001.0001.0000.8970.1290.0670.850
설치형태(막대형, 지주부착형 등)0.9550.5601.0001.0000.8971.0000.0000.0000.850
설치수량(조)0.1600.2761.0001.0000.1290.0001.0000.9960.890
황단보도수(면)0.0000.2361.0001.0000.0670.0000.9961.0000.000
비고0.8500.270NaN1.0000.8500.8500.8900.0001.000
2023-12-12T13:40:16.094346image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
자치구황단보도수(면)비고설치형태(막대형, 지주부착형 등)
자치구1.0000.0000.6340.848
황단보도수(면)0.0001.0000.0000.000
비고0.6340.0001.0000.634
설치형태(막대형, 지주부착형 등)0.8480.0000.6341.000
2023-12-12T13:40:16.191897image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
번호설치연도설치수량(조)자치구설치형태(막대형, 지주부착형 등)황단보도수(면)비고
번호1.0000.5770.0210.7110.3960.1390.050
설치연도0.5771.0000.1270.7030.6150.0640.634
설치수량(조)0.0210.1271.0000.0680.0000.9520.500
자치구0.7110.7030.0681.0000.8480.0000.634
설치형태(막대형, 지주부착형 등)0.3960.6150.0000.8481.0000.0000.634
황단보도수(면)0.1390.0640.9520.0000.0001.0000.000
비고0.0500.6340.5000.6340.6340.0001.000

Missing values

2023-12-12T13:40:10.419234image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-12T13:40:10.592765image/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.
2023-12-12T13:40:10.728591image/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

자치구번호시설물 위치명도로명주소지번주소설치연도설치형태(막대형, 지주부착형 등)설치수량(조)황단보도수(면)비고
0중랑구1상봉역앞(6번출구, 5번출구)서울특별시 중랑구 망우로 293<NA>2015막대형21<NA>
1강서구2월정초등학교<NA>서울특별시 강서구 화곡1동 3742015막대형21<NA>
2강서구3송화초등학교서울특별시 강서구 방화대로 319<NA>2015막대형21<NA>
3관악구4신림초등학교서울특별시 관악구 문성로 214<NA>2015막대형21<NA>
4서초구5청계산SH702동앞(연등)서울특별시 서초구 청계산로 11길<NA>2014막대형21<NA>
5서초구6신동초교서울특별시 서초구 나루터로 15<NA>2019지주부착형21<NA>
6관악구7관악초교서울특별시 관악구 쑥고개로 55<NA>2019지주부착형21<NA>
7관악구8청롱초교서울특별시 관악구 관악로 118<NA>2019지주부착형21<NA>
8관악구9인헌초교서울특별시 관악구 낙성대로 24<NA>2019지주부착형21<NA>
9관악구10원당초교서울특별시 관악구 봉천로 509<NA>2019지주부착형21<NA>
자치구번호시설물 위치명도로명주소지번주소설치연도설치형태(막대형, 지주부착형 등)설치수량(조)황단보도수(면)비고
180성북구181삼선초등학교서울특별시 성북구 보문로29길 106 앞(학교정문)<NA>2020지주부착형32<NA>
181성북구182석계초등학교서울특별시 성북구 한천로58길 273(학교정문)<NA>2020지주부착형21<NA>
182성북구183석관초등학교서울특별시 성북구 돌곶이로22길 21(학교정문)<NA>2020지주부착형21<NA>
183성북구184장곡초등학교서울특별시 성북구 장월로 113(통학로)<NA>2020지주부착형21<NA>
184성북구185숭인초등학교서울특별시 성북구 오패산로16길 37(학교정문)<NA>2020지주부착형21<NA>
185성북구186숭곡초등학교서울특별시 성북구 오패산로3길 147앞(통학로)<NA>2020지주부착형21<NA>
186성북구187숭례초등학교서울특별시 성북구 종암로 45앞(학교후문앞)<NA>2020지주부착형21<NA>
187성북구188일신초등학교서울특별시 성북구 월곡로 74(학교정문)<NA>2020지주부착형21<NA>
188성북구189미아초등학교서울특별시 성북구 삼양로 77(학교정문)<NA>2020지주부착형21<NA>
189성북구190석관초등학교서울특별시 성북구 돌곶이로 74(통학로)<NA>2020지주부착형63<NA>