Overview

Dataset statistics

Number of variables7
Number of observations6480
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory373.5 KiB
Average record size in memory59.0 B

Variable types

Categorical5
Numeric2

Dataset

Description성남시 전통시장/발달상권/골목상권 업종별 시장규모와 관련된 현황에 대한 데이터로, 기준년월, 상권구분, 소속구역, 대분류 업종, 중분류 업종, 시장규모 등의 데이터를 제공합니다.
Author경기도 성남시
URLhttps://www.data.go.kr/data/15098568/fileData.do

Alerts

소속구역명 is highly overall correlated with 상권구분코드(전통시장 1 발달상권 2 골목상권 3)High correlation
대분류업종명 is highly overall correlated with 중분류업종명High correlation
중분류업종명 is highly overall correlated with 대분류업종명High correlation
상권구분코드(전통시장 1 발달상권 2 골목상권 3) is highly overall correlated with 소속구역명High correlation
시장규모 is highly overall correlated with 표본수High correlation
표본수 is highly overall correlated with 시장규모High correlation

Reproduction

Analysis started2023-12-12 11:51:57.013750
Analysis finished2023-12-12 11:51:58.679660
Duration1.67 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

기준년월
Categorical

Distinct10
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size50.8 KiB
2021-03-01
657 
2021-10-01
656 
2021-09-01
652 
2021-07-01
651 
2021-06-01
650 
Other values (5)
3214 

Length

Max length10
Median length10
Mean length10
Min length10

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row2021-01-01
2nd row2021-01-01
3rd row2021-01-01
4th row2021-01-01
5th row2021-01-01

Common Values

ValueCountFrequency (%)
2021-03-01 657
10.1%
2021-10-01 656
10.1%
2021-09-01 652
10.1%
2021-07-01 651
10.0%
2021-06-01 650
10.0%
2021-05-01 649
10.0%
2021-04-01 648
10.0%
2021-02-01 640
9.9%
2021-08-01 639
9.9%
2021-01-01 638
9.8%

Length

2023-12-12T20:51:59.156589image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T20:51:59.332782image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2021-03-01 657
10.1%
2021-10-01 656
10.1%
2021-09-01 652
10.1%
2021-07-01 651
10.0%
2021-06-01 650
10.0%
2021-05-01 649
10.0%
2021-04-01 648
10.0%
2021-02-01 640
9.9%
2021-08-01 639
9.9%
2021-01-01 638
9.8%

상권구분코드(전통시장 1 발달상권 2 골목상권 3)
Categorical

HIGH CORRELATION 

Distinct3
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size50.8 KiB
1
3458 
3
1674 
2
1348 

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 3458
53.4%
3 1674
25.8%
2 1348
 
20.8%

Length

2023-12-12T20:51:59.528898image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T20:51:59.658081image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
1 3458
53.4%
3 1674
25.8%
2 1348
 
20.8%

소속구역명
Categorical

HIGH CORRELATION 

Distinct33
Distinct (%)0.5%
Missing0
Missing (%)0.0%
Memory size50.8 KiB
서현역로데오 상권
 
300
수진역-신흥역 상권
 
293
수내역로데오 상권
 
290
야탑 먹자골목
 
246
단대시장 상권
 
239
Other values (28)
5112 

Length

Max length11
Median length10
Mean length7.2496914
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row모란상권 진흥구역
2nd row모란상권 진흥구역
3rd row모란상권 진흥구역
4th row모란상권 진흥구역
5th row모란상권 진흥구역

Common Values

ValueCountFrequency (%)
서현역로데오 상권 300
 
4.6%
수진역-신흥역 상권 293
 
4.5%
수내역로데오 상권 290
 
4.5%
야탑 먹자골목 246
 
3.8%
단대시장 상권 239
 
3.7%
미금현대벤처빌 상권 238
 
3.7%
태평동 전통 상권 238
 
3.7%
복정상권 235
 
3.6%
정자동 상권 235
 
3.6%
야탑역 상권 235
 
3.6%
Other values (23) 3931
60.7%

Length

2023-12-12T20:51:59.795178image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
상권 4481
36.2%
먹자골목 409
 
3.3%
정자동 398
 
3.2%
전통상권 385
 
3.1%
서현역로데오 300
 
2.4%
수진역-신흥역 293
 
2.4%
수내역로데오 290
 
2.3%
야탑 246
 
2.0%
단대시장 239
 
1.9%
미금현대벤처빌 238
 
1.9%
Other values (28) 5099
41.2%

대분류업종명
Categorical

HIGH CORRELATION 

Distinct4
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size50.8 KiB
음식
2911 
소매/유통
2072 
생활서비스
898 
여가/오락
599 

Length

Max length5
Median length5
Mean length3.6523148
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row생활서비스
2nd row생활서비스
3rd row소매/유통
4th row소매/유통
5th row소매/유통

Common Values

ValueCountFrequency (%)
음식 2911
44.9%
소매/유통 2072
32.0%
생활서비스 898
 
13.9%
여가/오락 599
 
9.2%

Length

2023-12-12T20:51:59.956909image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T20:52:00.104564image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
음식 2911
44.9%
소매/유통 2072
32.0%
생활서비스 898
 
13.9%
여가/오락 599
 
9.2%

중분류업종명
Categorical

HIGH CORRELATION 

Distinct36
Distinct (%)0.6%
Missing0
Missing (%)0.0%
Memory size50.8 KiB
한식
 
320
종합소매점
 
320
미용서비스
 
320
커피/음료
 
315
고기요리
 
310
Other values (31)
4895 

Length

Max length10
Median length9
Mean length5.0790123
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row광고/인쇄/인화
2nd row미용서비스
3rd row건강/기호식품
4th row음/식료품소매
5th row의복/의류

Common Values

ValueCountFrequency (%)
한식 320
 
4.9%
종합소매점 320
 
4.9%
미용서비스 320
 
4.9%
커피/음료 315
 
4.9%
고기요리 310
 
4.8%
분식 309
 
4.8%
닭/오리요리 299
 
4.6%
일반스포츠 289
 
4.5%
일식/수산물 286
 
4.4%
간이주점 283
 
4.4%
Other values (26) 3429
52.9%

Length

2023-12-12T20:52:00.265037image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
한식 320
 
4.9%
종합소매점 320
 
4.9%
미용서비스 320
 
4.9%
커피/음료 315
 
4.9%
고기요리 310
 
4.8%
분식 309
 
4.8%
닭/오리요리 299
 
4.6%
일반스포츠 289
 
4.5%
일식/수산물 286
 
4.4%
간이주점 283
 
4.4%
Other values (26) 3429
52.9%

시장규모
Real number (ℝ)

HIGH CORRELATION 

Distinct6063
Distinct (%)93.6%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean3.2644734 × 108
Minimum500000
Maximum2.37461 × 1010
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size57.1 KiB
2023-12-12T20:52:00.418151image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum500000
5-th percentile12820000
Q165355000
median1.41605 × 108
Q33.320725 × 108
95-th percentile1.1697415 × 109
Maximum2.37461 × 1010
Range2.37456 × 1010
Interquartile range (IQR)2.667175 × 108

Descriptive statistics

Standard deviation8.0874332 × 108
Coefficient of variation (CV)2.4774082
Kurtosis357.2793
Mean3.2644734 × 108
Median Absolute Deviation (MAD)1.01095 × 108
Skewness15.950556
Sum2.1153788 × 1012
Variance6.5406576 × 1017
MonotonicityNot monotonic
2023-12-12T20:52:00.582089image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
64950000 6
 
0.1%
84090000 3
 
< 0.1%
282500000 3
 
< 0.1%
12120000 3
 
< 0.1%
122040000 3
 
< 0.1%
55120000 3
 
< 0.1%
113590000 3
 
< 0.1%
98000000 3
 
< 0.1%
2570000 3
 
< 0.1%
9900000 3
 
< 0.1%
Other values (6053) 6447
99.5%
ValueCountFrequency (%)
500000 1
< 0.1%
890000 1
< 0.1%
1380000 1
< 0.1%
1440000 1
< 0.1%
1500000 1
< 0.1%
1550000 1
< 0.1%
1670000 1
< 0.1%
1770000 1
< 0.1%
1790000 1
< 0.1%
1810000 1
< 0.1%
ValueCountFrequency (%)
23746100000 1
< 0.1%
21582350000 1
< 0.1%
19342200000 1
< 0.1%
18261490000 1
< 0.1%
17364170000 1
< 0.1%
15561550000 1
< 0.1%
14349550000 1
< 0.1%
13587570000 1
< 0.1%
12584300000 1
< 0.1%
12230860000 1
< 0.1%

표본수
Real number (ℝ)

HIGH CORRELATION 

Distinct81
Distinct (%)1.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean11.377623
Minimum3
Maximum87
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size57.1 KiB
2023-12-12T20:52:00.765836image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum3
5-th percentile3
Q14
median7
Q314
95-th percentile33
Maximum87
Range84
Interquartile range (IQR)10

Descriptive statistics

Standard deviation11.517751
Coefficient of variation (CV)1.012316
Kurtosis9.9530179
Mean11.377623
Median Absolute Deviation (MAD)4
Skewness2.7828453
Sum73727
Variance132.65858
MonotonicityNot monotonic
2023-12-12T20:52:00.950664image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
3 1032
15.9%
4 770
11.9%
5 674
 
10.4%
6 467
 
7.2%
7 367
 
5.7%
8 338
 
5.2%
9 307
 
4.7%
10 268
 
4.1%
11 209
 
3.2%
12 192
 
3.0%
Other values (71) 1856
28.6%
ValueCountFrequency (%)
3 1032
15.9%
4 770
11.9%
5 674
10.4%
6 467
7.2%
7 367
 
5.7%
8 338
 
5.2%
9 307
 
4.7%
10 268
 
4.1%
11 209
 
3.2%
12 192
 
3.0%
ValueCountFrequency (%)
87 1
 
< 0.1%
85 2
 
< 0.1%
82 3
< 0.1%
81 2
 
< 0.1%
80 1
 
< 0.1%
79 5
0.1%
78 3
< 0.1%
77 3
< 0.1%
76 6
0.1%
75 2
 
< 0.1%

Interactions

2023-12-12T20:51:58.058675image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T20:51:57.756622image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T20:51:58.198379image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T20:51:57.885311image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-12T20:52:01.055302image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
기준년월상권구분코드(전통시장 1 발달상권 2 골목상권 3)소속구역명대분류업종명중분류업종명시장규모표본수
기준년월1.0000.0000.0000.0000.0000.0000.000
상권구분코드(전통시장 1 발달상권 2 골목상권 3)0.0001.0001.0000.0530.3440.0790.179
소속구역명0.0001.0001.0000.2450.4890.1730.434
대분류업종명0.0000.0530.2451.0001.0000.0970.229
중분류업종명0.0000.3440.4891.0001.0000.4860.588
시장규모0.0000.0790.1730.0970.4861.0000.173
표본수0.0000.1790.4340.2290.5880.1731.000
2023-12-12T20:52:01.179612image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
소속구역명기준년월대분류업종명중분류업종명상권구분코드(전통시장 1 발달상권 2 골목상권 3)
소속구역명1.0000.0000.1280.1200.998
기준년월0.0001.0000.0000.0000.000
대분류업종명0.1280.0001.0000.9980.050
중분류업종명0.1200.0000.9981.0000.170
상권구분코드(전통시장 1 발달상권 2 골목상권 3)0.9980.0000.0500.1701.000
2023-12-12T20:52:01.291823image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
시장규모표본수기준년월상권구분코드(전통시장 1 발달상권 2 골목상권 3)소속구역명대분류업종명중분류업종명
시장규모1.0000.6270.0000.0340.0640.0620.183
표본수0.6271.0000.0000.1080.1680.1390.248
기준년월0.0000.0001.0000.0000.0000.0000.000
상권구분코드(전통시장 1 발달상권 2 골목상권 3)0.0340.1080.0001.0000.9980.0500.170
소속구역명0.0640.1680.0000.9981.0000.1280.120
대분류업종명0.0620.1390.0000.0500.1281.0000.998
중분류업종명0.1830.2480.0000.1700.1200.9981.000

Missing values

2023-12-12T20:51:58.393817image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-12T20:51:58.589092image/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

기준년월상권구분코드(전통시장 1 발달상권 2 골목상권 3)소속구역명대분류업종명중분류업종명시장규모표본수
02021-01-011모란상권 진흥구역생활서비스광고/인쇄/인화21000003
12021-01-011모란상권 진흥구역생활서비스미용서비스13899000014
22021-01-011모란상권 진흥구역소매/유통건강/기호식품1284400009
32021-01-011모란상권 진흥구역소매/유통음/식료품소매129957000043
42021-01-011모란상권 진흥구역소매/유통의복/의류53500003
52021-01-011모란상권 진흥구역소매/유통종합소매점144788000011
62021-01-011모란상권 진흥구역여가/오락일반스포츠142500004
72021-01-011모란상권 진흥구역여가/오락취미/오락241400004
82021-01-011모란상권 진흥구역음식간이주점284700009
92021-01-011모란상권 진흥구역음식고기요리447300004
기준년월상권구분코드(전통시장 1 발달상권 2 골목상권 3)소속구역명대분류업종명중분류업종명시장규모표본수
64702021-10-013중앙동상권여가/오락일반스포츠621200007
64712021-10-013중앙동상권여가/오락취미/오락1211100009
64722021-10-013중앙동상권음식간이주점22926000021
64732021-10-013중앙동상권음식고기요리4358600008
64742021-10-013중앙동상권음식닭/오리요리593500005
64752021-10-013중앙동상권음식분식69500005
64762021-10-013중앙동상권음식일식/수산물1048100003
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