Overview

Dataset statistics

Number of variables11
Number of observations24
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory2.3 KiB
Average record size in memory97.5 B

Variable types

Text3
Categorical3
Numeric4
DateTime1

Dataset

Description동대문구에 존재하는 상권에 대한 기본정보와 위치정보를 나타내는 데이터입니다. 전통시장 20개 대학상권 4개 총 24개 상권정보를 제공하는 상권 데이터입니다.
Author서울특별시 동대문구
URLhttps://www.data.go.kr/data/15109932/fileData.do

Alerts

시도명 has constant value ""Constant
시군구명 has constant value ""Constant
데이터기준일자 has constant value ""Constant
면적 is highly overall correlated with 업체수High correlation
업체수 is highly overall correlated with 면적High correlation
위도 is highly overall correlated with 읍면동명High correlation
경도 is highly overall correlated with 읍면동명High correlation
읍면동명 is highly overall correlated with 위도 and 1 other fieldsHigh correlation
아이디 has unique valuesUnique
상권명 has unique valuesUnique
면적 has unique valuesUnique
위도 has unique valuesUnique
경도 has unique valuesUnique
이미지명 has unique valuesUnique

Reproduction

Analysis started2023-12-12 05:50:57.566172
Analysis finished2023-12-12 05:51:00.262120
Duration2.7 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

아이디
Text

UNIQUE 

Distinct24
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size324.0 B
2023-12-12T14:51:00.426813image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length3
Median length3
Mean length3
Min length3

Characters and Unicode

Total characters72
Distinct characters12
Distinct categories2 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique24 ?
Unique (%)100.0%

Sample

1st rowM01
2nd rowM02
3rd rowM03
4th rowM04
5th rowM05
ValueCountFrequency (%)
m01 1
 
4.2%
m02 1
 
4.2%
u03 1
 
4.2%
u02 1
 
4.2%
u01 1
 
4.2%
m20 1
 
4.2%
m19 1
 
4.2%
m18 1
 
4.2%
m17 1
 
4.2%
m16 1
 
4.2%
Other values (14) 14
58.3%
2023-12-12T14:51:01.162391image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
M 20
27.8%
0 15
20.8%
1 13
18.1%
2 4
 
5.6%
U 4
 
5.6%
3 3
 
4.2%
4 3
 
4.2%
5 2
 
2.8%
6 2
 
2.8%
7 2
 
2.8%
Other values (2) 4
 
5.6%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 48
66.7%
Uppercase Letter 24
33.3%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 15
31.2%
1 13
27.1%
2 4
 
8.3%
3 3
 
6.2%
4 3
 
6.2%
5 2
 
4.2%
6 2
 
4.2%
7 2
 
4.2%
8 2
 
4.2%
9 2
 
4.2%
Uppercase Letter
ValueCountFrequency (%)
M 20
83.3%
U 4
 
16.7%

Most occurring scripts

ValueCountFrequency (%)
Common 48
66.7%
Latin 24
33.3%

Most frequent character per script

Common
ValueCountFrequency (%)
0 15
31.2%
1 13
27.1%
2 4
 
8.3%
3 3
 
6.2%
4 3
 
6.2%
5 2
 
4.2%
6 2
 
4.2%
7 2
 
4.2%
8 2
 
4.2%
9 2
 
4.2%
Latin
ValueCountFrequency (%)
M 20
83.3%
U 4
 
16.7%

Most occurring blocks

ValueCountFrequency (%)
ASCII 72
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
M 20
27.8%
0 15
20.8%
1 13
18.1%
2 4
 
5.6%
U 4
 
5.6%
3 3
 
4.2%
4 3
 
4.2%
5 2
 
2.8%
6 2
 
2.8%
7 2
 
2.8%
Other values (2) 4
 
5.6%

상권명
Text

UNIQUE 

Distinct24
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size324.0 B
2023-12-12T14:51:01.459716image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length10
Median length8.5
Mean length5.9583333
Min length3

Characters and Unicode

Total characters143
Distinct characters57
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

Unique24 ?
Unique (%)100.0%

Sample

1st row회기시장
2nd row청량종합도매시장
3rd row답십리시장
4th row이문제일시장
5th row청량리수산시장
ValueCountFrequency (%)
회기시장 1
 
3.8%
청량종합도매시장 1
 
3.8%
외대앞 1
 
3.8%
서울시립대 1
 
3.8%
경희대 1
 
3.8%
경희대삼거리 1
 
3.8%
전곡시장 1
 
3.8%
전농로터리시장 1
 
3.8%
경동시장 1
 
3.8%
청량리전통시장 1
 
3.8%
Other values (16) 16
61.5%
2023-12-12T14:51:01.891050image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
시 20
 
14.0%
장 19
 
13.3%
리 10
 
7.0%
청 7
 
4.9%
량 6
 
4.2%
대 5
 
3.5%
경 5
 
3.5%
동 4
 
2.8%
서 3
 
2.1%
전 3
 
2.1%
Other values (47) 61
42.7%

Most occurring categories

ValueCountFrequency (%)
Other Letter 140
97.9%
Space Separator 2
 
1.4%
Decimal Number 1
 
0.7%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
시 20
 
14.3%
장 19
 
13.6%
리 10
 
7.1%
청 7
 
5.0%
량 6
 
4.3%
대 5
 
3.6%
경 5
 
3.6%
동 4
 
2.9%
서 3
 
2.1%
전 3
 
2.1%
Other values (45) 58
41.4%
Space Separator
ValueCountFrequency (%)
2
100.0%
Decimal Number
ValueCountFrequency (%)
1 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 140
97.9%
Common 3
 
2.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
시 20
 
14.3%
장 19
 
13.6%
리 10
 
7.1%
청 7
 
5.0%
량 6
 
4.3%
대 5
 
3.6%
경 5
 
3.6%
동 4
 
2.9%
서 3
 
2.1%
전 3
 
2.1%
Other values (45) 58
41.4%
Common
ValueCountFrequency (%)
2
66.7%
1 1
33.3%

Most occurring blocks

ValueCountFrequency (%)
Hangul 140
97.9%
ASCII 3
 
2.1%

Most frequent character per block

Hangul
ValueCountFrequency (%)
시 20
 
14.3%
장 19
 
13.6%
리 10
 
7.1%
청 7
 
5.0%
량 6
 
4.3%
대 5
 
3.6%
경 5
 
3.6%
동 4
 
2.9%
서 3
 
2.1%
전 3
 
2.1%
Other values (45) 58
41.4%
ASCII
ValueCountFrequency (%)
2
66.7%
1 1
33.3%

시도명
Categorical

CONSTANT 

Distinct1
Distinct (%)4.2%
Missing0
Missing (%)0.0%
Memory size324.0 B
서울특별시
24 

Length

Max length5
Median length5
Mean length5
Min length5

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
서울특별시 24
100.0%

Length

2023-12-12T14:51:02.079056image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T14:51:02.208110image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
서울특별시 24
100.0%

시군구명
Categorical

CONSTANT 

Distinct1
Distinct (%)4.2%
Missing0
Missing (%)0.0%
Memory size324.0 B
서울특별시 동대문구
24 

Length

Max length10
Median length10
Mean length10
Min length10

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row서울특별시 동대문구
2nd row서울특별시 동대문구
3rd row서울특별시 동대문구
4th row서울특별시 동대문구
5th row서울특별시 동대문구

Common Values

ValueCountFrequency (%)
서울특별시 동대문구 24
100.0%

Length

2023-12-12T14:51:02.322356image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T14:51:02.426709image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
서울특별시 24
50.0%
동대문구 24
50.0%

읍면동명
Categorical

HIGH CORRELATION 

Distinct9
Distinct (%)37.5%
Missing0
Missing (%)0.0%
Memory size324.0 B
제기동
8 
답십리동
4 
회기동
3 
이문동
2 
용두동
2 
Other values (4)
5 

Length

Max length4
Median length3
Mean length3.2083333
Min length3

Unique

Unique3 ?
Unique (%)12.5%

Sample

1st row회기동
2nd row제기동
3rd row답십리동
4th row이문동
5th row용두동

Common Values

ValueCountFrequency (%)
제기동 8
33.3%
답십리동 4
16.7%
회기동 3
 
12.5%
이문동 2
 
8.3%
용두동 2
 
8.3%
전농동 2
 
8.3%
휘경동 1
 
4.2%
청량리동 1
 
4.2%
장안동 1
 
4.2%

Length

2023-12-12T14:51:02.587837image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T14:51:02.708537image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
제기동 8
33.3%
답십리동 4
16.7%
회기동 3
 
12.5%
이문동 2
 
8.3%
용두동 2
 
8.3%
전농동 2
 
8.3%
휘경동 1
 
4.2%
청량리동 1
 
4.2%
장안동 1
 
4.2%

면적
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct24
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean436569.96
Minimum43424
Maximum1979899
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size348.0 B
2023-12-12T14:51:02.878313image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum43424
5-th percentile66050.15
Q1218682.75
median276299.5
Q3486128
95-th percentile1173419.6
Maximum1979899
Range1936475
Interquartile range (IQR)267445.25

Descriptive statistics

Standard deviation435824.15
Coefficient of variation (CV)0.99829165
Kurtosis6.3028362
Mean436569.96
Median Absolute Deviation (MAD)66079.5
Skewness2.3703209
Sum10477679
Variance1.8994269 × 1011
MonotonicityNot monotonic
2023-12-12T14:51:03.064146image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=24)
ValueCountFrequency (%)
341050 1
 
4.2%
211443 1
 
4.2%
1006687 1
 
4.2%
1202843 1
 
4.2%
618138 1
 
4.2%
826843 1
 
4.2%
265807 1
 
4.2%
225555 1
 
4.2%
221096 1
 
4.2%
306232 1
 
4.2%
Other values (14) 14
58.3%
ValueCountFrequency (%)
43424 1
4.2%
54425 1
4.2%
131926 1
4.2%
194243 1
4.2%
208997 1
4.2%
211443 1
4.2%
221096 1
4.2%
225555 1
4.2%
227521 1
4.2%
234215 1
4.2%
ValueCountFrequency (%)
1979899 1
4.2%
1202843 1
4.2%
1006687 1
4.2%
826843 1
4.2%
618138 1
4.2%
553658 1
4.2%
463618 1
4.2%
341050 1
4.2%
322259 1
4.2%
307328 1
4.2%

업체수
Real number (ℝ)

HIGH CORRELATION 

Distinct23
Distinct (%)95.8%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean138.95833
Minimum14
Maximum553
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size348.0 B
2023-12-12T14:51:03.250718image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum14
5-th percentile26.65
Q153.75
median102
Q3149.75
95-th percentile320.55
Maximum553
Range539
Interquartile range (IQR)96

Descriptive statistics

Standard deviation127.40708
Coefficient of variation (CV)0.91687252
Kurtosis3.7196617
Mean138.95833
Median Absolute Deviation (MAD)49.5
Skewness1.8472214
Sum3335
Variance16232.563
MonotonicityNot monotonic
2023-12-12T14:51:03.387033image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=23)
ValueCountFrequency (%)
50 2
 
8.3%
90 1
 
4.2%
92 1
 
4.2%
321 1
 
4.2%
155 1
 
4.2%
318 1
 
4.2%
125 1
 
4.2%
84 1
 
4.2%
121 1
 
4.2%
301 1
 
4.2%
Other values (13) 13
54.2%
ValueCountFrequency (%)
14 1
4.2%
25 1
4.2%
36 1
4.2%
40 1
4.2%
50 2
8.3%
55 1
4.2%
62 1
4.2%
66 1
4.2%
84 1
4.2%
90 1
4.2%
ValueCountFrequency (%)
553 1
4.2%
321 1
4.2%
318 1
4.2%
301 1
4.2%
271 1
4.2%
155 1
4.2%
148 1
4.2%
133 1
4.2%
125 1
4.2%
121 1
4.2%

위도
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct24
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean37.582045
Minimum37.567073
Maximum37.60402
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size348.0 B
2023-12-12T14:51:03.530919image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum37.567073
5-th percentile37.567727
Q137.577936
median37.580357
Q337.586991
95-th percentile37.595152
Maximum37.60402
Range0.03694742
Interquartile range (IQR)0.0090549025

Descriptive statistics

Standard deviation0.0090662969
Coefficient of variation (CV)0.00024124012
Kurtosis0.33580194
Mean37.582045
Median Absolute Deviation (MAD)0.002729805
Skewness0.48762626
Sum901.96907
Variance8.219774 × 10-5
MonotonicityNot monotonic
2023-12-12T14:51:03.687075image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=24)
ValueCountFrequency (%)
37.59109689 1
 
4.2%
37.56707277 1
 
4.2%
37.59523033 1
 
4.2%
37.58572927 1
 
4.2%
37.59269783 1
 
4.2%
37.59077636 1
 
4.2%
37.57753694 1
 
4.2%
37.57771765 1
 
4.2%
37.57906626 1
 
4.2%
37.58189699 1
 
4.2%
Other values (14) 14
58.3%
ValueCountFrequency (%)
37.56707277 1
4.2%
37.56764563 1
4.2%
37.56818727 1
4.2%
37.57363843 1
4.2%
37.57753694 1
4.2%
37.57771765 1
4.2%
37.57800897 1
4.2%
37.57848466 1
4.2%
37.57906626 1
4.2%
37.57967067 1
4.2%
ValueCountFrequency (%)
37.60402019 1
4.2%
37.59523033 1
4.2%
37.59470933 1
4.2%
37.59269783 1
4.2%
37.59109689 1
4.2%
37.59077636 1
4.2%
37.58572927 1
4.2%
37.58216569 1
4.2%
37.58189699 1
4.2%
37.58182083 1
4.2%

경도
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct24
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean127.04946
Minimum127.02977
Maximum127.0687
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size348.0 B
2023-12-12T14:51:03.839933image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum127.02977
5-th percentile127.03747
Q1127.04065
median127.05157
Q3127.05707
95-th percentile127.0655
Maximum127.0687
Range0.038937
Interquartile range (IQR)0.016425625

Descriptive statistics

Standard deviation0.010352088
Coefficient of variation (CV)8.1480776 × 10-5
Kurtosis-0.94680076
Mean127.04946
Median Absolute Deviation (MAD)0.00990095
Skewness0.10449094
Sum3049.1869
Variance0.00010716573
MonotonicityNot monotonic
2023-12-12T14:51:04.026319image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=24)
ValueCountFrequency (%)
127.0555159 1
 
4.2%
127.0583122 1
 
4.2%
127.0612121 1
 
4.2%
127.0541022 1
 
4.2%
127.0520927 1
 
4.2%
127.0510474 1
 
4.2%
127.068704 1
 
4.2%
127.0566989 1
 
4.2%
127.0390814 1
 
4.2%
127.0434729 1
 
4.2%
Other values (14) 14
58.3%
ValueCountFrequency (%)
127.029767 1
4.2%
127.0371997 1
4.2%
127.0389881 1
4.2%
127.0390814 1
4.2%
127.040587 1
4.2%
127.0406457 1
4.2%
127.0406468 1
4.2%
127.0412383 1
4.2%
127.0414102 1
4.2%
127.0427948 1
4.2%
ValueCountFrequency (%)
127.068704 1
4.2%
127.0659803 1
4.2%
127.0627708 1
4.2%
127.0612121 1
4.2%
127.0583122 1
4.2%
127.0581919 1
4.2%
127.0566989 1
4.2%
127.0555159 1
4.2%
127.0541022 1
4.2%
127.0538444 1
4.2%

데이터기준일자
Date

CONSTANT 

Distinct1
Distinct (%)4.2%
Missing0
Missing (%)0.0%
Memory size324.0 B
Minimum2022-12-12 00:00:00
Maximum2022-12-12 00:00:00
2023-12-12T14:51:04.176331image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T14:51:04.287300image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=1)

이미지명
Text

UNIQUE 

Distinct24
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size324.0 B
2023-12-12T14:51:04.541414image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length18
Median length16.5
Mean length14.916667
Min length12

Characters and Unicode

Total characters358
Distinct characters69
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

Unique24 ?
Unique (%)100.0%

Sample

1st rowM01_0001_회기시장
2nd rowM02_0001_청량종합도매시장
3rd rowM03_0001_답십리시장
4th rowM04_0001_이문제일시장
5th rowM05_0001_청량리수산시장
ValueCountFrequency (%)
m01_0001_회기시장 1
 
4.0%
m14_0001_답십리현대시장 1
 
4.0%
u04_0001_외대앞 1
 
4.0%
u03_0001_서울시립대 1
 
4.0%
u02_0001_경희대 1
 
4.0%
u01_0001_경희대삼거리 1
 
4.0%
m20_0001_전곡시장 1
 
4.0%
m19_0001_전농로터리시장 1
 
4.0%
m18_0001_경동시장 1
 
4.0%
m17_0001_청량리전통시장 1
 
4.0%
Other values (15) 15
60.0%
2023-12-12T14:51:04.976767image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 87
24.3%
_ 48
13.4%
1 38
 
10.6%
M 20
 
5.6%
시 20
 
5.6%
장 19
 
5.3%
리 10
 
2.8%
청 7
 
2.0%
량 6
 
1.7%
대 5
 
1.4%
Other values (59) 98
27.4%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 145
40.5%
Other Letter 140
39.1%
Connector Punctuation 48
 
13.4%
Uppercase Letter 24
 
6.7%
Space Separator 1
 
0.3%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
시 20
 
14.3%
장 19
 
13.6%
리 10
 
7.1%
청 7
 
5.0%
량 6
 
4.3%
대 5
 
3.6%
경 5
 
3.6%
동 4
 
2.9%
전 3
 
2.1%
답 3
 
2.1%
Other values (45) 58
41.4%
Decimal Number
ValueCountFrequency (%)
0 87
60.0%
1 38
26.2%
2 4
 
2.8%
4 3
 
2.1%
3 3
 
2.1%
9 2
 
1.4%
8 2
 
1.4%
7 2
 
1.4%
5 2
 
1.4%
6 2
 
1.4%
Uppercase Letter
ValueCountFrequency (%)
M 20
83.3%
U 4
 
16.7%
Connector Punctuation
ValueCountFrequency (%)
_ 48
100.0%
Space Separator
ValueCountFrequency (%)
1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 194
54.2%
Hangul 140
39.1%
Latin 24
 
6.7%

Most frequent character per script

Hangul
ValueCountFrequency (%)
시 20
 
14.3%
장 19
 
13.6%
리 10
 
7.1%
청 7
 
5.0%
량 6
 
4.3%
대 5
 
3.6%
경 5
 
3.6%
동 4
 
2.9%
전 3
 
2.1%
답 3
 
2.1%
Other values (45) 58
41.4%
Common
ValueCountFrequency (%)
0 87
44.8%
_ 48
24.7%
1 38
19.6%
2 4
 
2.1%
4 3
 
1.5%
3 3
 
1.5%
9 2
 
1.0%
8 2
 
1.0%
7 2
 
1.0%
5 2
 
1.0%
Other values (2) 3
 
1.5%
Latin
ValueCountFrequency (%)
M 20
83.3%
U 4
 
16.7%

Most occurring blocks

ValueCountFrequency (%)
ASCII 218
60.9%
Hangul 140
39.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 87
39.9%
_ 48
22.0%
1 38
17.4%
M 20
 
9.2%
2 4
 
1.8%
U 4
 
1.8%
4 3
 
1.4%
3 3
 
1.4%
9 2
 
0.9%
8 2
 
0.9%
Other values (4) 7
 
3.2%
Hangul
ValueCountFrequency (%)
시 20
 
14.3%
장 19
 
13.6%
리 10
 
7.1%
청 7
 
5.0%
량 6
 
4.3%
대 5
 
3.6%
경 5
 
3.6%
동 4
 
2.9%
전 3
 
2.1%
답 3
 
2.1%
Other values (45) 58
41.4%

Interactions

2023-12-12T14:50:59.449342image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T14:50:57.995662image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T14:50:58.510725image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T14:50:58.950655image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T14:50:59.551265image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T14:50:58.121106image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T14:50:58.638676image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T14:50:59.087138image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T14:50:59.662127image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T14:50:58.243732image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T14:50:58.740212image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T14:50:59.206777image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T14:50:59.796042image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T14:50:58.382625image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T14:50:58.849988image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T14:50:59.334244image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-12T14:51:05.106543image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
아이디상권명읍면동명면적업체수위도경도이미지명
아이디1.0001.0001.0001.0001.0001.0001.0001.000
상권명1.0001.0001.0001.0001.0001.0001.0001.000
읍면동명1.0001.0001.0000.0000.0000.9500.9381.000
면적1.0001.0000.0001.0000.8410.5460.5841.000
업체수1.0001.0000.0000.8411.0000.0000.3341.000
위도1.0001.0000.9500.5460.0001.0000.6461.000
경도1.0001.0000.9380.5840.3340.6461.0001.000
이미지명1.0001.0001.0001.0001.0001.0001.0001.000
2023-12-12T14:51:05.256564image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
면적업체수위도경도읍면동명
면적1.0000.6040.302-0.0270.000
업체수0.6041.0000.348-0.3010.000
위도0.3020.3481.0000.0930.623
경도-0.027-0.3010.0931.0000.586
읍면동명0.0000.0000.6230.5861.000

Missing values

2023-12-12T14:50:59.985916image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-12T14:51:00.192847image/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

아이디상권명시도명시군구명읍면동명면적업체수위도경도데이터기준일자이미지명
0M01회기시장서울특별시서울특별시 동대문구회기동3410509037.591097127.0555162022-12-12M01_0001_회기시장
1M02청량종합도매시장서울특별시서울특별시 동대문구제기동4636189237.582166127.0406472022-12-12M02_0001_청량종합도매시장
2M03답십리시장서울특별시서울특별시 동대문구답십리동2275213637.573638127.0581922022-12-12M03_0001_답십리시장
3M04이문제일시장서울특별시서울특별시 동대문구이문동1942434037.60402127.0627712022-12-12M04_0001_이문제일시장
4M05청량리수산시장서울특별시서울특별시 동대문구용두동30732811237.578009127.0412382022-12-12M05_0001_청량리수산시장
5M06용두시장서울특별시서울특별시 동대문구용두동544251437.578485127.0297672022-12-12M06_0001_용두시장
6M07동부시장서울특별시서울특별시 동대문구답십리동2342152537.567646127.0526382022-12-12M07_0001_동부시장
7M08경동광성상가서울특별시서울특별시 동대문구제기동20899714837.581323127.0389882022-12-12M08_0001_경동광성상가
8M09청량리청과물시장서울특별시서울특별시 동대문구제기동28679211337.579941127.0427952022-12-12M09_0001_청량리청과물시장
9M10청량리농수산물시장서울특별시서울특별시 동대문구제기동32225927137.580774127.0406462022-12-12M10_0001_청량리농수산물시장
아이디상권명시도명시군구명읍면동명면적업체수위도경도데이터기준일자이미지명
14M15이경시장서울특별시서울특별시 동대문구휘경동1319265037.594709127.065982022-12-12M15_0001_이경시장
15M16동서시장서울특별시서울특별시 동대문구제기동434245037.579859127.041412022-12-12M16_0001_동서시장
16M17청량리전통시장서울특별시서울특별시 동대문구청량리동3062326237.581897127.0434732022-12-12M17_0001_청량리전통시장
17M18경동시장서울특별시서울특별시 동대문구제기동22109630137.579066127.0390812022-12-12M18_0001_경동시장
18M19전농로터리시장서울특별시서울특별시 동대문구전농동22555512137.577718127.0566992022-12-12M19_0001_전농로터리시장
19M20전곡시장서울특별시서울특별시 동대문구장안동2658078437.577537127.0687042022-12-12M20_0001_전곡시장
20U01경희대삼거리서울특별시서울특별시 동대문구회기동82684312537.590776127.0510472022-12-12U01_0001_경희대삼거리
21U02경희대서울특별시서울특별시 동대문구회기동61813831837.592698127.0520932022-12-12U02_0001_경희대
22U03서울시립대서울특별시서울특별시 동대문구전농동120284315537.585729127.0541022022-12-12U03_0001_서울시립대
23U04외대앞 1번출구서울특별시서울특별시 동대문구이문동100668732137.59523127.0612122022-12-12U04_0001_외대앞 1번출구