Overview

Dataset statistics

Number of variables12
Number of observations52
Missing cells77
Missing cells (%)12.3%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory5.2 KiB
Average record size in memory102.5 B

Variable types

Categorical4
Text4
Numeric2
Unsupported1
DateTime1

Dataset

Description성남시 버스정류장 등에 설치되어 있는 온기나눔쉼터(온열의자, 바람막이) 설치 현황(설치장소, 주소, 관리기관)입니다.
URLhttps://www.data.go.kr/data/15043220/fileData.do

Alerts

항목명 has constant value ""Constant
기준년도 has constant value ""Constant
시군명 has constant value ""Constant
관리기관 has constant value ""Constant
데이터기준일자 has constant value ""Constant
소재지도로명주소 has 25 (48.1%) missing valuesMissing
관리기관 전화번호 has 52 (100.0%) missing valuesMissing
설치장소명 has unique valuesUnique
소재지지번주소 has unique valuesUnique
관리기관 전화번호 is an unsupported type, check if it needs cleaning or further analysisUnsupported

Reproduction

Analysis started2023-12-11 23:22:11.972620
Analysis finished2023-12-11 23:22:13.056676
Duration1.08 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

항목명
Categorical

CONSTANT 

Distinct1
Distinct (%)1.9%
Missing0
Missing (%)0.0%
Memory size548.0 B
온열의자
52 

Length

Max length4
Median length4
Mean length4
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
온열의자 52
100.0%

Length

2023-12-12T08:22:13.135446image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T08:22:13.240075image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
온열의자 52
100.0%

기준년도
Categorical

CONSTANT 

Distinct1
Distinct (%)1.9%
Missing0
Missing (%)0.0%
Memory size548.0 B
2023
52 

Length

Max length4
Median length4
Mean length4
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row2023
2nd row2023
3rd row2023
4th row2023
5th row2023

Common Values

ValueCountFrequency (%)
2023 52
100.0%

Length

2023-12-12T08:22:13.337483image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T08:22:13.456876image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2023 52
100.0%

시군명
Categorical

CONSTANT 

Distinct1
Distinct (%)1.9%
Missing0
Missing (%)0.0%
Memory size548.0 B
성남시
52 

Length

Max length3
Median length3
Mean length3
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
성남시 52
100.0%

Length

2023-12-12T08:22:13.590710image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T08:22:13.700394image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
성남시 52
100.0%

읍면동명
Text

Distinct38
Distinct (%)73.1%
Missing0
Missing (%)0.0%
Memory size548.0 B
2023-12-12T08:22:13.881668image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length5
Median length3
Mean length3.5384615
Min length3

Characters and Unicode

Total characters184
Distinct characters49
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

Unique26 ?
Unique (%)50.0%

Sample

1st row수진동
2nd row양지동
3rd row금광동
4th row야탑동
5th row정자동
ValueCountFrequency (%)
하대원동 3
 
5.8%
서현1동 3
 
5.8%
성남동 2
 
3.8%
신흥2동 2
 
3.8%
단대동 2
 
3.8%
양지동 2
 
3.8%
백현동 2
 
3.8%
고등동 2
 
3.8%
도촌동 2
 
3.8%
운중동 2
 
3.8%
Other values (28) 30
57.7%
2023-12-12T08:22:14.250478image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
동 52
28.3%
대 9
 
4.9%
2 8
 
4.3%
1 8
 
4.3%
원 7
 
3.8%
현 6
 
3.3%
신 5
 
2.7%
3 5
 
2.7%
흥 5
 
2.7%
서 4
 
2.2%
Other values (39) 75
40.8%

Most occurring categories

ValueCountFrequency (%)
Other Letter 163
88.6%
Decimal Number 21
 
11.4%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
동 52
31.9%
대 9
 
5.5%
원 7
 
4.3%
현 6
 
3.7%
신 5
 
3.1%
흥 5
 
3.1%
서 4
 
2.5%
상 4
 
2.5%
정 4
 
2.5%
금 4
 
2.5%
Other values (36) 63
38.7%
Decimal Number
ValueCountFrequency (%)
2 8
38.1%
1 8
38.1%
3 5
23.8%

Most occurring scripts

ValueCountFrequency (%)
Hangul 163
88.6%
Common 21
 
11.4%

Most frequent character per script

Hangul
ValueCountFrequency (%)
동 52
31.9%
대 9
 
5.5%
원 7
 
4.3%
현 6
 
3.7%
신 5
 
3.1%
흥 5
 
3.1%
서 4
 
2.5%
상 4
 
2.5%
정 4
 
2.5%
금 4
 
2.5%
Other values (36) 63
38.7%
Common
ValueCountFrequency (%)
2 8
38.1%
1 8
38.1%
3 5
23.8%

Most occurring blocks

ValueCountFrequency (%)
Hangul 163
88.6%
ASCII 21
 
11.4%

Most frequent character per block

Hangul
ValueCountFrequency (%)
동 52
31.9%
대 9
 
5.5%
원 7
 
4.3%
현 6
 
3.7%
신 5
 
3.1%
흥 5
 
3.1%
서 4
 
2.5%
상 4
 
2.5%
정 4
 
2.5%
금 4
 
2.5%
Other values (36) 63
38.7%
ASCII
ValueCountFrequency (%)
2 8
38.1%
1 8
38.1%
3 5
23.8%

설치장소명
Text

UNIQUE 

Distinct52
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size548.0 B
2023-12-12T08:22:14.481138image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length29
Median length21
Mean length15.519231
Min length10

Characters and Unicode

Total characters807
Distinct characters144
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

Unique52 ?
Unique (%)100.0%

Sample

1st row중앙시장,농협(05048)
2nd row은행시장,남한산성시장,은행동청소년문화의집(05134)
3rd row단대쇼핑(06052)
4th row성남세관,고령친화체험관(07269)
5th row주공7단지,한솔종합사회복지관(07092)
ValueCountFrequency (%)
중앙시장,농협(05048 1
 
1.9%
오야동.신촌동행정복지센터(05019 1
 
1.9%
태평3동행정복지센터(05144 1
 
1.9%
영성중학교.하대원동행정복지센터(06025 1
 
1.9%
야탑2동행정복지센터.차병원(07189 1
 
1.9%
판교동행정복지센터(07412 1
 
1.9%
고등마을아파트(05272 1
 
1.9%
고등마을아파트(05271 1
 
1.9%
시흥동행정복지센터(05164 1
 
1.9%
래미안위례,위례고운초등학교앞(05081 1
 
1.9%
Other values (43) 43
81.1%
2023-12-12T08:22:14.852552image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 85
 
10.5%
) 53
 
6.6%
( 53
 
6.6%
1 32
 
4.0%
6 29
 
3.6%
5 26
 
3.2%
7 26
 
3.2%
2 23
 
2.9%
4 20
 
2.5%
동 16
 
2.0%
Other values (134) 444
55.0%

Most occurring categories

ValueCountFrequency (%)
Other Letter 397
49.2%
Decimal Number 275
34.1%
Close Punctuation 53
 
6.6%
Open Punctuation 53
 
6.6%
Other Punctuation 22
 
2.7%
Uppercase Letter 6
 
0.7%
Space Separator 1
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
동 16
 
4.0%
성 14
 
3.5%
지 13
 
3.3%
남 12
 
3.0%
행 10
 
2.5%
시 10
 
2.5%
교 9
 
2.3%
아 8
 
2.0%
관 8
 
2.0%
대 8
 
2.0%
Other values (116) 289
72.8%
Decimal Number
ValueCountFrequency (%)
0 85
30.9%
1 32
 
11.6%
6 29
 
10.5%
5 26
 
9.5%
7 26
 
9.5%
2 23
 
8.4%
4 20
 
7.3%
3 15
 
5.5%
9 12
 
4.4%
8 7
 
2.5%
Uppercase Letter
ValueCountFrequency (%)
K 3
50.0%
T 2
33.3%
A 1
 
16.7%
Other Punctuation
ValueCountFrequency (%)
, 15
68.2%
. 7
31.8%
Close Punctuation
ValueCountFrequency (%)
) 53
100.0%
Open Punctuation
ValueCountFrequency (%)
( 53
100.0%
Space Separator
ValueCountFrequency (%)
1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 404
50.1%
Hangul 397
49.2%
Latin 6
 
0.7%

Most frequent character per script

Hangul
ValueCountFrequency (%)
동 16
 
4.0%
성 14
 
3.5%
지 13
 
3.3%
남 12
 
3.0%
행 10
 
2.5%
시 10
 
2.5%
교 9
 
2.3%
아 8
 
2.0%
관 8
 
2.0%
대 8
 
2.0%
Other values (116) 289
72.8%
Common
ValueCountFrequency (%)
0 85
21.0%
) 53
13.1%
( 53
13.1%
1 32
 
7.9%
6 29
 
7.2%
5 26
 
6.4%
7 26
 
6.4%
2 23
 
5.7%
4 20
 
5.0%
, 15
 
3.7%
Other values (5) 42
10.4%
Latin
ValueCountFrequency (%)
K 3
50.0%
T 2
33.3%
A 1
 
16.7%

Most occurring blocks

ValueCountFrequency (%)
ASCII 410
50.8%
Hangul 397
49.2%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 85
20.7%
) 53
12.9%
( 53
12.9%
1 32
 
7.8%
6 29
 
7.1%
5 26
 
6.3%
7 26
 
6.3%
2 23
 
5.6%
4 20
 
4.9%
, 15
 
3.7%
Other values (8) 48
11.7%
Hangul
ValueCountFrequency (%)
동 16
 
4.0%
성 14
 
3.5%
지 13
 
3.3%
남 12
 
3.0%
행 10
 
2.5%
시 10
 
2.5%
교 9
 
2.3%
아 8
 
2.0%
관 8
 
2.0%
대 8
 
2.0%
Other values (116) 289
72.8%

소재지도로명주소
Text

MISSING 

Distinct27
Distinct (%)100.0%
Missing25
Missing (%)48.1%
Memory size548.0 B
2023-12-12T08:22:15.028944image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length13
Median length10
Mean length8.2962963
Min length6

Characters and Unicode

Total characters224
Distinct characters50
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

Unique27 ?
Unique (%)100.0%

Sample

1st row수정로 126
2nd row산성대로 529-2
3rd row산성대로 372번길 18
4th row야탑로 205번길4
5th row내정로 94
ValueCountFrequency (%)
산성대로 5
 
8.9%
둔촌대로 3
 
5.4%
수정로 2
 
3.6%
내정로 2
 
3.6%
남문로 1
 
1.8%
54 1
 
1.8%
244-2 1
 
1.8%
야탑로69번길 1
 
1.8%
2 1
 
1.8%
여수대로56번길 1
 
1.8%
Other values (38) 38
67.9%
2023-12-12T08:22:15.334093image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
29
 
12.9%
로 27
 
12.1%
2 17
 
7.6%
5 12
 
5.4%
4 11
 
4.9%
1 11
 
4.9%
6 11
 
4.9%
대 9
 
4.0%
번 7
 
3.1%
길 7
 
3.1%
Other values (40) 83
37.1%

Most occurring categories

ValueCountFrequency (%)
Other Letter 108
48.2%
Decimal Number 84
37.5%
Space Separator 29
 
12.9%
Dash Punctuation 3
 
1.3%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
로 27
25.0%
대 9
 
8.3%
번 7
 
6.5%
길 7
 
6.5%
성 5
 
4.6%
산 5
 
4.6%
정 5
 
4.6%
촌 3
 
2.8%
둔 3
 
2.8%
수 3
 
2.8%
Other values (28) 34
31.5%
Decimal Number
ValueCountFrequency (%)
2 17
20.2%
5 12
14.3%
4 11
13.1%
1 11
13.1%
6 11
13.1%
3 6
 
7.1%
0 5
 
6.0%
7 4
 
4.8%
9 4
 
4.8%
8 3
 
3.6%
Space Separator
ValueCountFrequency (%)
29
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 3
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 116
51.8%
Hangul 108
48.2%

Most frequent character per script

Hangul
ValueCountFrequency (%)
로 27
25.0%
대 9
 
8.3%
번 7
 
6.5%
길 7
 
6.5%
성 5
 
4.6%
산 5
 
4.6%
정 5
 
4.6%
촌 3
 
2.8%
둔 3
 
2.8%
수 3
 
2.8%
Other values (28) 34
31.5%
Common
ValueCountFrequency (%)
29
25.0%
2 17
14.7%
5 12
10.3%
4 11
 
9.5%
1 11
 
9.5%
6 11
 
9.5%
3 6
 
5.2%
0 5
 
4.3%
7 4
 
3.4%
9 4
 
3.4%
Other values (2) 6
 
5.2%

Most occurring blocks

ValueCountFrequency (%)
ASCII 116
51.8%
Hangul 108
48.2%

Most frequent character per block

ASCII
ValueCountFrequency (%)
29
25.0%
2 17
14.7%
5 12
10.3%
4 11
 
9.5%
1 11
 
9.5%
6 11
 
9.5%
3 6
 
5.2%
0 5
 
4.3%
7 4
 
3.4%
9 4
 
3.4%
Other values (2) 6
 
5.2%
Hangul
ValueCountFrequency (%)
로 27
25.0%
대 9
 
8.3%
번 7
 
6.5%
길 7
 
6.5%
성 5
 
4.6%
산 5
 
4.6%
정 5
 
4.6%
촌 3
 
2.8%
둔 3
 
2.8%
수 3
 
2.8%
Other values (28) 34
31.5%

소재지지번주소
Text

UNIQUE 

Distinct52
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size548.0 B
2023-12-12T08:22:15.541763image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length22
Median length20
Mean length20.038462
Min length18

Characters and Unicode

Total characters1042
Distinct characters65
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

Unique52 ?
Unique (%)100.0%

Sample

1st row경기도 성남시 수정구 수진동 20
2nd row경기도 성남시 수정구 양지동 877
3rd row경기도 성남시 중원구 금광동 14
4th row경기도 성남시 분당구 야탑동 264-3
5th row경기도 성남시 분당구 정자동 101
ValueCountFrequency (%)
경기도 52
20.0%
성남시 52
20.0%
분당구 19
 
7.3%
수정구 17
 
6.5%
중원구 16
 
6.2%
신흥동 5
 
1.9%
상대원동 4
 
1.5%
야탑동 3
 
1.2%
금광동 3
 
1.2%
정자동 3
 
1.2%
Other values (78) 86
33.1%
2023-12-12T08:22:15.858963image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
208
20.0%
성 54
 
5.2%
남 54
 
5.2%
구 53
 
5.1%
도 53
 
5.1%
시 53
 
5.1%
기 52
 
5.0%
동 52
 
5.0%
경 52
 
5.0%
2 32
 
3.1%
Other values (55) 379
36.4%

Most occurring categories

ValueCountFrequency (%)
Other Letter 630
60.5%
Space Separator 208
 
20.0%
Decimal Number 182
 
17.5%
Dash Punctuation 22
 
2.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
성 54
 
8.6%
남 54
 
8.6%
구 53
 
8.4%
도 53
 
8.4%
시 53
 
8.4%
기 52
 
8.3%
동 52
 
8.3%
경 52
 
8.3%
원 23
 
3.7%
정 21
 
3.3%
Other values (43) 163
25.9%
Decimal Number
ValueCountFrequency (%)
2 32
17.6%
1 29
15.9%
5 25
13.7%
4 20
11.0%
3 19
10.4%
8 13
7.1%
9 13
7.1%
6 11
 
6.0%
0 11
 
6.0%
7 9
 
4.9%
Space Separator
ValueCountFrequency (%)
208
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 22
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 630
60.5%
Common 412
39.5%

Most frequent character per script

Hangul
ValueCountFrequency (%)
성 54
 
8.6%
남 54
 
8.6%
구 53
 
8.4%
도 53
 
8.4%
시 53
 
8.4%
기 52
 
8.3%
동 52
 
8.3%
경 52
 
8.3%
원 23
 
3.7%
정 21
 
3.3%
Other values (43) 163
25.9%
Common
ValueCountFrequency (%)
208
50.5%
2 32
 
7.8%
1 29
 
7.0%
5 25
 
6.1%
- 22
 
5.3%
4 20
 
4.9%
3 19
 
4.6%
8 13
 
3.2%
9 13
 
3.2%
6 11
 
2.7%
Other values (2) 20
 
4.9%

Most occurring blocks

ValueCountFrequency (%)
Hangul 630
60.5%
ASCII 412
39.5%

Most frequent character per block

ASCII
ValueCountFrequency (%)
208
50.5%
2 32
 
7.8%
1 29
 
7.0%
5 25
 
6.1%
- 22
 
5.3%
4 20
 
4.9%
3 19
 
4.6%
8 13
 
3.2%
9 13
 
3.2%
6 11
 
2.7%
Other values (2) 20
 
4.9%
Hangul
ValueCountFrequency (%)
성 54
 
8.6%
남 54
 
8.6%
구 53
 
8.4%
도 53
 
8.4%
시 53
 
8.4%
기 52
 
8.3%
동 52
 
8.3%
경 52
 
8.3%
원 23
 
3.7%
정 21
 
3.3%
Other values (43) 163
25.9%

위도
Real number (ℝ)

Distinct50
Distinct (%)96.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean109.88127
Minimum37.350183
Maximum127.17897
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size600.0 B
2023-12-12T08:22:15.972193image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum37.350183
5-th percentile37.381028
Q1127.09928
median127.13328
Q3127.14708
95-th percentile127.16764
Maximum127.17897
Range89.828784
Interquartile range (IQR)0.04779575

Descriptive statistics

Standard deviation35.707055
Coefficient of variation (CV)0.32496036
Kurtosis0.6082353
Mean109.88127
Median Absolute Deviation (MAD)0.02535
Skewness-1.6082068
Sum5713.8258
Variance1274.9938
MonotonicityNot monotonic
2023-12-12T08:22:16.073545image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
127.1424 2
 
3.8%
37.461283 2
 
3.8%
127.13425 1
 
1.9%
127.1243 1
 
1.9%
127.14545 1
 
1.9%
127.126717 1
 
1.9%
127.0977 1
 
1.9%
127.098467 1
 
1.9%
127.09955 1
 
1.9%
127.108267 1
 
1.9%
Other values (40) 40
76.9%
ValueCountFrequency (%)
37.350183 1
1.9%
37.373733 1
1.9%
37.377517 1
1.9%
37.3839 1
1.9%
37.3915 1
1.9%
37.423067 1
1.9%
37.44185 1
1.9%
37.442167 1
1.9%
37.461283 2
3.8%
127.068 1
1.9%
ValueCountFrequency (%)
127.178967 1
1.9%
127.178783 1
1.9%
127.171083 1
1.9%
127.164817 1
1.9%
127.1644 1
1.9%
127.164383 1
1.9%
127.164317 1
1.9%
127.163033 1
1.9%
127.162783 1
1.9%
127.158967 1
1.9%

경도
Real number (ℝ)

Distinct51
Distinct (%)98.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean54.674686
Minimum37.349933
Maximum127.17572
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size600.0 B
2023-12-12T08:22:16.182286image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum37.349933
5-th percentile37.35993
Q137.409579
median37.439767
Q337.457971
95-th percentile127.1581
Maximum127.17572
Range89.825784
Interquartile range (IQR)0.04839125

Descriptive statistics

Standard deviation35.704335
Coefficient of variation (CV)0.65303229
Kurtosis0.60823182
Mean54.674686
Median Absolute Deviation (MAD)0.024308
Skewness1.6082054
Sum2843.0837
Variance1274.7996
MonotonicityNot monotonic
2023-12-12T08:22:16.285101image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
127.167033 2
 
3.8%
37.4415 1
 
1.9%
37.371017 1
 
1.9%
37.445683 1
 
1.9%
37.4282 1
 
1.9%
37.409967 1
 
1.9%
37.389217 1
 
1.9%
37.430383 1
 
1.9%
37.430267 1
 
1.9%
37.422267 1
 
1.9%
Other values (41) 41
78.8%
ValueCountFrequency (%)
37.349933 1
1.9%
37.3591 1
1.9%
37.359783 1
1.9%
37.36005 1
1.9%
37.368233 1
1.9%
37.371017 1
1.9%
37.377367 1
1.9%
37.388717 1
1.9%
37.389217 1
1.9%
37.389267 1
1.9%
ValueCountFrequency (%)
127.175717 1
1.9%
127.167033 2
3.8%
127.150783 1
1.9%
127.15045 1
1.9%
127.15025 1
1.9%
127.132267 1
1.9%
127.11975 1
1.9%
127.106817 1
1.9%
127.077667 1
1.9%
37.470733 1
1.9%

관리기관
Categorical

CONSTANT 

Distinct1
Distinct (%)1.9%
Missing0
Missing (%)0.0%
Memory size548.0 B
성남시청+성남도시개발공사
52 

Length

Max length13
Median length13
Mean length13
Min length13

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row성남시청+성남도시개발공사
2nd row성남시청+성남도시개발공사
3rd row성남시청+성남도시개발공사
4th row성남시청+성남도시개발공사
5th row성남시청+성남도시개발공사

Common Values

ValueCountFrequency (%)
성남시청+성남도시개발공사 52
100.0%

Length

2023-12-12T08:22:16.378502image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T08:22:16.452257image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
성남시청+성남도시개발공사 52
100.0%

관리기관 전화번호
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing52
Missing (%)100.0%
Memory size600.0 B

데이터기준일자
Date

CONSTANT 

Distinct1
Distinct (%)1.9%
Missing0
Missing (%)0.0%
Memory size548.0 B
Minimum2023-05-31 00:00:00
Maximum2023-05-31 00:00:00
2023-12-12T08:22:16.513265image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:22:16.583173image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=1)

Interactions

2023-12-12T08:22:12.540523image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:22:12.388703image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:22:12.649644image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:22:12.459280image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-12T08:22:16.640176image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
읍면동명설치장소명소재지도로명주소소재지지번주소위도경도
읍면동명1.0001.0001.0001.0000.0000.000
설치장소명1.0001.0001.0001.0001.0001.000
소재지도로명주소1.0001.0001.0001.0001.0001.000
소재지지번주소1.0001.0001.0001.0001.0001.000
위도0.0001.0001.0001.0001.0000.995
경도0.0001.0001.0001.0000.9951.000
2023-12-12T08:22:16.725204image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
위도경도
위도1.000-0.186
경도-0.1861.000

Missing values

2023-12-12T08:22:12.778034image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-12T08:22:12.970438image/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

항목명기준년도시군명읍면동명설치장소명소재지도로명주소소재지지번주소위도경도관리기관관리기관 전화번호데이터기준일자
0온열의자2023성남시수진동중앙시장,농협(05048)수정로 126경기도 성남시 수정구 수진동 20127.1342537.4415성남시청+성남도시개발공사<NA>2023-05-31
1온열의자2023성남시양지동은행시장,남한산성시장,은행동청소년문화의집(05134)산성대로 529-2경기도 성남시 수정구 양지동 877127.164437.458633성남시청+성남도시개발공사<NA>2023-05-31
2온열의자2023성남시금광동단대쇼핑(06052)산성대로 372번길 18경기도 성남시 중원구 금광동 14127.15896737.4448성남시청+성남도시개발공사<NA>2023-05-31
3온열의자2023성남시야탑동성남세관,고령친화체험관(07269)야탑로 205번길4경기도 성남시 분당구 야탑동 264-3127.142437.408417성남시청+성남도시개발공사<NA>2023-05-31
4온열의자2023성남시정자동주공7단지,한솔종합사회복지관(07092)내정로 94경기도 성남시 분당구 정자동 101127.11496737.368233성남시청+성남도시개발공사<NA>2023-05-31
5온열의자2023성남시운중동대장동입구(07645)<NA>경기도 성남시 분당구 대장동 320-16127.06837.3591성남시청+성남도시개발공사<NA>2023-05-31
6온열의자2023성남시상대원동보통골동양공업사(06140)갈마치로 203번길 12경기도 성남시 중원구 상대원동 344-3127.17896737.4351성남시청+성남도시개발공사<NA>2023-05-31
7온열의자2023성남시도촌동도촌동9단지앞(06199)<NA>경기도 성남시 중원구 도촌동 648127.16278337.411817성남시청+성남도시개발공사<NA>2023-05-31
8온열의자2023성남시단대동성남혜은학교(05103)희망로 516경기도 성남시 수정구 단대동 191127.15291737.449833성남시청+성남도시개발공사<NA>2023-05-31
9온열의자2023성남시복정동동서울대학교(05025)<NA>경기도 성남시 수정구 복정동 440-1127.125637.460433성남시청+성남도시개발공사<NA>2023-05-31
항목명기준년도시군명읍면동명설치장소명소재지도로명주소소재지지번주소위도경도관리기관관리기관 전화번호데이터기준일자
42온열의자2023성남시단대동남한산성입구역,법원검찰청(05121)산성대로 445경기도 성남시 수정구 단대동 95-537.461283127.167033성남시청+성남도시개발공사<NA>2023-05-31
43온열의자2023성남시양지동을지대학교,생활관(05135)산성대로 571경기도 성남시 수정구 양지동 211-137.461283127.167033성남시청+성남도시개발공사<NA>2023-05-31
44온열의자2023성남시신흥3동성남우체국(05097)<NA>경기도 성남시 수정구 신흥동 248037.442167127.15045성남시청+성남도시개발공사<NA>2023-05-31
45온열의자2023성남시중앙동성남우체국(06206)<NA>경기도 성남시 중원구 중앙동 50437.44185127.150783성남시청+성남도시개발공사<NA>2023-05-31
46온열의자2023성남시도촌동갈현동(06129)<NA>경기도 성남시 중원구 갈현동 207-1037.423067127.175717성남시청+성남도시개발공사<NA>2023-05-31
47온열의자2023성남시수내2동파크타운,롯데아파트(07134)내정로 170경기도 성남시 분당구 수내동 58-137.373733127.11975성남시청+성남도시개발공사<NA>2023-05-31
48온열의자2023성남시서현1동우성상가(07433)<NA>경기도 성남시 분당구 서현동 9237.377517127.132267성남시청+성남도시개발공사<NA>2023-05-31
49온열의자2023성남시서현1동새마을연수원사거리(07350)<NA>경기도 성남시 분당구 율동 28337.3839127.15025성남시청+성남도시개발공사<NA>2023-05-31
50온열의자2023성남시금곡동미금역,2001아울렛(07045)<NA>경기도 성남시 분당구 금곡동 21137.350183127.106817성남시청+성남도시개발공사<NA>2023-05-31
51온열의자2023성남시운중동운중동행정복지센터(07011)<NA>경기도 성남시 분당구 운중동 94437.3915127.077667성남시청+성남도시개발공사<NA>2023-05-31