Overview

Dataset statistics

Number of variables7
Number of observations25
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory1.6 KiB
Average record size in memory65.3 B

Variable types

Categorical2
Text3
Numeric2

Dataset

Description파일 다운로드
Author구로구
URLhttps://data.seoul.go.kr/dataList/OA-21863/F/1/datasetView.do

Reproduction

Analysis started2023-12-11 04:48:28.441781
Analysis finished2023-12-11 04:48:29.358487
Duration0.92 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

설치연도
Categorical

Distinct5
Distinct (%)20.0%
Missing0
Missing (%)0.0%
Memory size332.0 B
2019
9 
2020
7 
2017
5 
2018
3 
2016
1 

Length

Max length4
Median length4
Mean length4
Min length4

Unique

Unique1 ?
Unique (%)4.0%

Sample

1st row2016
2nd row2017
3rd row2017
4th row2017
5th row2017

Common Values

ValueCountFrequency (%)
2019 9
36.0%
2020 7
28.0%
2017 5
20.0%
2018 3
 
12.0%
2016 1
 
4.0%

Length

2023-12-11T13:48:29.436884image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T13:48:29.551354image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2019 9
36.0%
2020 7
28.0%
2017 5
20.0%
2018 3
 
12.0%
2016 1
 
4.0%

설치장소
Text

Distinct23
Distinct (%)92.0%
Missing0
Missing (%)0.0%
Memory size332.0 B
2023-12-11T13:48:29.729083image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length10
Median length3
Mean length3.92
Min length3

Characters and Unicode

Total characters98
Distinct characters46
Distinct categories2 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique21 ?
Unique (%)84.0%

Sample

1st row온수초
2nd row오류남초
3rd row덕의초
4th row구일초
5th row신도림초
ValueCountFrequency (%)
매봉초 2
 
8.0%
오류남초 2
 
8.0%
고원초 1
 
4.0%
온수초 1
 
4.0%
정진학교 1
 
4.0%
코레일오류동어린이집 1
 
4.0%
lg전자구로어린이집 1
 
4.0%
구로남초 1
 
4.0%
항동초 1
 
4.0%
하늘숲초 1
 
4.0%
Other values (13) 13
52.0%
2023-12-11T13:48:30.056861image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
초 22
22.4%
구 6
 
6.1%
로 5
 
5.1%
오 4
 
4.1%
류 3
 
3.1%
남 3
 
3.1%
신 3
 
3.1%
동 3
 
3.1%
매 2
 
2.0%
어 2
 
2.0%
Other values (36) 45
45.9%

Most occurring categories

ValueCountFrequency (%)
Other Letter 96
98.0%
Uppercase Letter 2
 
2.0%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
초 22
22.9%
구 6
 
6.2%
로 5
 
5.2%
오 4
 
4.2%
류 3
 
3.1%
남 3
 
3.1%
신 3
 
3.1%
동 3
 
3.1%
매 2
 
2.1%
어 2
 
2.1%
Other values (34) 43
44.8%
Uppercase Letter
ValueCountFrequency (%)
L 1
50.0%
G 1
50.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 96
98.0%
Latin 2
 
2.0%

Most frequent character per script

Hangul
ValueCountFrequency (%)
초 22
22.9%
구 6
 
6.2%
로 5
 
5.2%
오 4
 
4.2%
류 3
 
3.1%
남 3
 
3.1%
신 3
 
3.1%
동 3
 
3.1%
매 2
 
2.1%
어 2
 
2.1%
Other values (34) 43
44.8%
Latin
ValueCountFrequency (%)
L 1
50.0%
G 1
50.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 96
98.0%
ASCII 2
 
2.0%

Most frequent character per block

Hangul
ValueCountFrequency (%)
초 22
22.9%
구 6
 
6.2%
로 5
 
5.2%
오 4
 
4.2%
류 3
 
3.1%
남 3
 
3.1%
신 3
 
3.1%
동 3
 
3.1%
매 2
 
2.1%
어 2
 
2.1%
Other values (34) 43
44.8%
ASCII
ValueCountFrequency (%)
L 1
50.0%
G 1
50.0%

설치개소
Categorical

Distinct3
Distinct (%)12.0%
Missing0
Missing (%)0.0%
Memory size332.0 B
1
19 
2
5 
3
 
1

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique1 ?
Unique (%)4.0%

Sample

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

Common Values

ValueCountFrequency (%)
1 19
76.0%
2 5
 
20.0%
3 1
 
4.0%

Length

2023-12-11T13:48:30.185655image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T13:48:30.278308image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
1 19
76.0%
2 5
 
20.0%
3 1
 
4.0%

도로명주소
Text

Distinct23
Distinct (%)92.0%
Missing0
Missing (%)0.0%
Memory size332.0 B
2023-12-11T13:48:30.462729image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length21
Median length19
Mean length18.48
Min length15

Characters and Unicode

Total characters462
Distinct characters47
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique21 ?
Unique (%)84.0%

Sample

1st row서울특별시 구로구 부일로 893
2nd row서울특별시 구로구 서해안로24길 22
3rd row서울특별시 구로구 고척로 213
4th row서울특별시 구로구 구일로 68
5th row서울특별시 구로구 신도림로19길 44
ValueCountFrequency (%)
서울특별시 25
25.0%
구로구 25
25.0%
고척로21길 2
 
2.0%
55 2
 
2.0%
서해안로24길 2
 
2.0%
22 2
 
2.0%
76 1
 
1.0%
26 1
 
1.0%
도림로20길 1
 
1.0%
57 1
 
1.0%
Other values (38) 38
38.0%
2023-12-11T13:48:30.811963image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
75
16.2%
구 53
11.5%
로 52
11.3%
서 27
 
5.8%
울 25
 
5.4%
시 25
 
5.4%
특 25
 
5.4%
별 25
 
5.4%
2 17
 
3.7%
길 16
 
3.5%
Other values (37) 122
26.4%

Most occurring categories

ValueCountFrequency (%)
Other Letter 304
65.8%
Decimal Number 83
 
18.0%
Space Separator 75
 
16.2%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
구 53
17.4%
로 52
17.1%
서 27
8.9%
울 25
8.2%
시 25
8.2%
특 25
8.2%
별 25
8.2%
길 16
 
5.3%
척 4
 
1.3%
고 4
 
1.3%
Other values (26) 48
15.8%
Decimal Number
ValueCountFrequency (%)
2 17
20.5%
1 14
16.9%
4 9
10.8%
3 8
9.6%
5 7
8.4%
7 7
8.4%
6 7
8.4%
9 6
 
7.2%
8 4
 
4.8%
0 4
 
4.8%
Space Separator
ValueCountFrequency (%)
75
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 304
65.8%
Common 158
34.2%

Most frequent character per script

Hangul
ValueCountFrequency (%)
구 53
17.4%
로 52
17.1%
서 27
8.9%
울 25
8.2%
시 25
8.2%
특 25
8.2%
별 25
8.2%
길 16
 
5.3%
척 4
 
1.3%
고 4
 
1.3%
Other values (26) 48
15.8%
Common
ValueCountFrequency (%)
75
47.5%
2 17
 
10.8%
1 14
 
8.9%
4 9
 
5.7%
3 8
 
5.1%
5 7
 
4.4%
7 7
 
4.4%
6 7
 
4.4%
9 6
 
3.8%
8 4
 
2.5%

Most occurring blocks

ValueCountFrequency (%)
Hangul 304
65.8%
ASCII 158
34.2%

Most frequent character per block

ASCII
ValueCountFrequency (%)
75
47.5%
2 17
 
10.8%
1 14
 
8.9%
4 9
 
5.7%
3 8
 
5.1%
5 7
 
4.4%
7 7
 
4.4%
6 7
 
4.4%
9 6
 
3.8%
8 4
 
2.5%
Hangul
ValueCountFrequency (%)
구 53
17.4%
로 52
17.1%
서 27
8.9%
울 25
8.2%
시 25
8.2%
특 25
8.2%
별 25
8.2%
길 16
 
5.3%
척 4
 
1.3%
고 4
 
1.3%
Other values (26) 48
15.8%

지번주소
Text

Distinct23
Distinct (%)92.0%
Missing0
Missing (%)0.0%
Memory size332.0 B
2023-12-11T13:48:31.006184image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length21
Median length19
Mean length18.92
Min length16

Characters and Unicode

Total characters473
Distinct characters36
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

Unique21 ?
Unique (%)84.0%

Sample

1st row서울특별시 구로구 온수동 9-34
2nd row서울특별시 구로구 오류동 332-59
3rd row서울특별시 구로구 고척동 287-8
4th row서울특별시 구로구 구로동 685-221
5th row서울특별시 구로구 신도림동 302-65
ValueCountFrequency (%)
서울특별시 25
24.8%
구로구 25
24.8%
구로동 8
 
7.9%
오류동 4
 
4.0%
고척동 4
 
4.0%
개봉동 2
 
2.0%
7-37 2
 
2.0%
332-59 2
 
2.0%
천왕동 2
 
2.0%
신도림동 2
 
2.0%
Other values (25) 25
24.8%
2023-12-11T13:48:31.359832image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
76
16.1%
구 58
12.3%
로 33
 
7.0%
서 25
 
5.3%
특 25
 
5.3%
별 25
 
5.3%
시 25
 
5.3%
울 25
 
5.3%
동 25
 
5.3%
- 19
 
4.0%
Other values (26) 137
29.0%

Most occurring categories

ValueCountFrequency (%)
Other Letter 276
58.4%
Decimal Number 102
 
21.6%
Space Separator 76
 
16.1%
Dash Punctuation 19
 
4.0%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
구 58
21.0%
로 33
12.0%
서 25
9.1%
특 25
9.1%
별 25
9.1%
시 25
9.1%
울 25
9.1%
동 25
9.1%
류 4
 
1.4%
고 4
 
1.4%
Other values (14) 27
9.8%
Decimal Number
ValueCountFrequency (%)
3 16
15.7%
2 15
14.7%
1 13
12.7%
6 11
10.8%
5 11
10.8%
8 10
9.8%
7 9
8.8%
9 7
6.9%
0 6
 
5.9%
4 4
 
3.9%
Space Separator
ValueCountFrequency (%)
76
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 19
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 276
58.4%
Common 197
41.6%

Most frequent character per script

Hangul
ValueCountFrequency (%)
구 58
21.0%
로 33
12.0%
서 25
9.1%
특 25
9.1%
별 25
9.1%
시 25
9.1%
울 25
9.1%
동 25
9.1%
류 4
 
1.4%
고 4
 
1.4%
Other values (14) 27
9.8%
Common
ValueCountFrequency (%)
76
38.6%
- 19
 
9.6%
3 16
 
8.1%
2 15
 
7.6%
1 13
 
6.6%
6 11
 
5.6%
5 11
 
5.6%
8 10
 
5.1%
7 9
 
4.6%
9 7
 
3.6%
Other values (2) 10
 
5.1%

Most occurring blocks

ValueCountFrequency (%)
Hangul 276
58.4%
ASCII 197
41.6%

Most frequent character per block

ASCII
ValueCountFrequency (%)
76
38.6%
- 19
 
9.6%
3 16
 
8.1%
2 15
 
7.6%
1 13
 
6.6%
6 11
 
5.6%
5 11
 
5.6%
8 10
 
5.1%
7 9
 
4.6%
9 7
 
3.6%
Other values (2) 10
 
5.1%
Hangul
ValueCountFrequency (%)
구 58
21.0%
로 33
12.0%
서 25
9.1%
특 25
9.1%
별 25
9.1%
시 25
9.1%
울 25
9.1%
동 25
9.1%
류 4
 
1.4%
고 4
 
1.4%
Other values (14) 27
9.8%

위도
Real number (ℝ)

Distinct23
Distinct (%)92.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean37.495433
Minimum37.477016
Maximum37.511984
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size357.0 B
2023-12-11T13:48:31.516660image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum37.477016
5-th percentile37.481997
Q137.489687
median37.495484
Q337.504915
95-th percentile37.506919
Maximum37.511984
Range0.0349685
Interquartile range (IQR)0.015228716

Descriptive statistics

Standard deviation0.0090367952
Coefficient of variation (CV)0.00024101056
Kurtosis-0.70012407
Mean37.495433
Median Absolute Deviation (MAD)0.0065226948
Skewness-0.15048487
Sum937.38583
Variance8.1663667 × 10-5
MonotonicityNot monotonic
2023-12-11T13:48:31.667093image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=23)
ValueCountFrequency (%)
37.4896865179 2
 
8.0%
37.5049152339 2
 
8.0%
37.4940050583 1
 
4.0%
37.4901656647 1
 
4.0%
37.4954835157 1
 
4.0%
37.4860712347 1
 
4.0%
37.4842060247 1
 
4.0%
37.47701589 1
 
4.0%
37.4841594284 1
 
4.0%
37.4889608209 1
 
4.0%
Other values (13) 13
52.0%
ValueCountFrequency (%)
37.47701589 1
4.0%
37.4814559796 1
4.0%
37.4841594284 1
4.0%
37.4842060247 1
4.0%
37.4860712347 1
4.0%
37.4889608209 1
4.0%
37.4896865179 2
8.0%
37.4901656647 1
4.0%
37.493191873 1
4.0%
37.4940050583 1
4.0%
ValueCountFrequency (%)
37.5119843897 1
4.0%
37.5071419203 1
4.0%
37.5060279654 1
4.0%
37.5051066487 1
4.0%
37.5050561026 1
4.0%
37.5049152339 2
8.0%
37.4996600321 1
4.0%
37.4989725505 1
4.0%
37.4988144872 1
4.0%
37.4976112203 1
4.0%

경도
Real number (ℝ)

Distinct23
Distinct (%)92.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean126.85925
Minimum126.82075
Maximum126.89558
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size357.0 B
2023-12-11T13:48:31.869280image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum126.82075
5-th percentile126.82448
Q1126.83911
median126.85735
Q3126.88325
95-th percentile126.89227
Maximum126.89558
Range0.074831437
Interquartile range (IQR)0.044141824

Descriptive statistics

Standard deviation0.024791049
Coefficient of variation (CV)0.00019542169
Kurtosis-1.4868516
Mean126.85925
Median Absolute Deviation (MAD)0.020283098
Skewness0.0094703255
Sum3171.4813
Variance0.00061459611
MonotonicityNot monotonic
2023-12-11T13:48:32.015790image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=23)
ValueCountFrequency (%)
126.8391127262 2
 
8.0%
126.8443652972 2
 
8.0%
126.8259666803 1
 
4.0%
126.8264391944 1
 
4.0%
126.8453292255 1
 
4.0%
126.8769042511 1
 
4.0%
126.8902182029 1
 
4.0%
126.8241102684 1
 
4.0%
126.8414819972 1
 
4.0%
126.8955833396 1
 
4.0%
Other values (13) 13
52.0%
ValueCountFrequency (%)
126.8207519022 1
4.0%
126.8241102684 1
4.0%
126.8259666803 1
4.0%
126.8264391944 1
4.0%
126.8370629317 1
4.0%
126.8391127262 2
8.0%
126.8414819972 1
4.0%
126.8443652972 2
8.0%
126.8453292255 1
4.0%
126.8491198348 1
4.0%
ValueCountFrequency (%)
126.8955833396 1
4.0%
126.8927801947 1
4.0%
126.8902182029 1
4.0%
126.8897631295 1
4.0%
126.888080264 1
4.0%
126.8865542735 1
4.0%
126.8832545502 1
4.0%
126.8795527403 1
4.0%
126.8769042511 1
4.0%
126.873472709 1
4.0%

Interactions

2023-12-11T13:48:28.922659image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T13:48:28.704870image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T13:48:29.026803image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T13:48:28.807222image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-11T13:48:32.143657image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
설치연도설치장소설치개소도로명주소지번주소위도경도
설치연도1.0000.8440.0000.8440.8440.0000.000
설치장소0.8441.0001.0001.0001.0001.0001.000
설치개소0.0001.0001.0001.0001.0000.5710.000
도로명주소0.8441.0001.0001.0001.0001.0001.000
지번주소0.8441.0001.0001.0001.0001.0001.000
위도0.0001.0000.5711.0001.0001.0000.000
경도0.0001.0000.0001.0001.0000.0001.000
2023-12-11T13:48:32.270816image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
설치연도설치개소
설치연도1.0000.000
설치개소0.0001.000
2023-12-11T13:48:32.377794image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
위도경도설치연도설치개소
위도1.0000.2630.0000.322
경도0.2631.0000.0000.000
설치연도0.0000.0001.0000.000
설치개소0.3220.0000.0001.000

Missing values

2023-12-11T13:48:29.187405image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-11T13:48:29.307532image/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

설치연도설치장소설치개소도로명주소지번주소위도경도
02016온수초1서울특별시 구로구 부일로 893서울특별시 구로구 온수동 9-3437.494005126.825967
12017오류남초1서울특별시 구로구 서해안로24길 22서울특별시 구로구 오류동 332-5937.489687126.839113
22017덕의초1서울특별시 구로구 고척로 213서울특별시 구로구 고척동 287-837.506028126.857346
32017구일초2서울특별시 구로구 구일로 68서울특별시 구로구 구로동 685-22137.493192126.873473
42017신도림초1서울특별시 구로구 신도림로19길 44서울특별시 구로구 신도림동 302-6537.511984126.883255
52017고산초1서울특별시 구로구 중앙로 6서울특별시 구로구 고척동 76-38037.498973126.864773
62018구로초1서울특별시 구로구 구로중앙로27나길 9서울특별시 구로구 구로동 44337.497462126.886554
72018세곡초2서울특별시 구로구 고척로33길 34서울특별시 구로구 고척동 253-12937.505056126.84912
82018동구로초2서울특별시 구로구 구로중앙로14길 43서울특별시 구로구 구로동 9337.494071126.89278
92019미래초1서울특별시 구로구 새말로 73서울특별시 구로구 구로동 556-137.505107126.88808
설치연도설치장소설치개소도로명주소지번주소위도경도
152019신미림초1서울특별시 구로구 신도림로 26서울특별시 구로구 신도림동 398-2837.507142126.879553
162019영서초1서울특별시 구로구 도림로20길 57서울특별시 구로구 구로동 179-15137.488961126.895583
172019하늘숲초3서울특별시 구로구 오리로 1106서울특별시 구로구 천왕동 산 13-137.484159126.841482
182020항동초2서울특별시 구로구 연동로 178서울특별시 구로구 항동 16037.477016126.82411
192020구로남초1서울특별시 구로구 디지털로27길 76서울특별시 구로구 구로동 25337.484206126.890218
202020LG전자구로어린이집1서울특별시 구로구 가마산로 95서울특별시 구로구 구로동 701-18637.486071126.876904
212020코레일오류동어린이집1서울특별시 구로구 경인로20가길 24서울특별시 구로구 오류동 6637.495484126.845329
222020오류남초1서울특별시 구로구 서해안로24길 22서울특별시 구로구 오류동 332-5937.489687126.839113
232020오정초1서울특별시 구로구 경인로2길 10서울특별시 구로구 오류동 108-2837.490166126.826439
242020매봉초1서울특별시 구로구 고척로21길 55서울특별시 구로구 개봉동 7-3737.504915126.844365