Overview

Dataset statistics

Number of variables9
Number of observations113
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory9.0 KiB
Average record size in memory81.2 B

Variable types

Numeric5
Categorical4

Dataset

Description전국 시도별 부동산개발업체의 부동산개발업법 위반행위에 대한 행정처분 결과에 대한 년도별 통계 정보(처분대상구분, 법원이송구분, 시정조치, 영업정지, 등록취소 등)
URLhttps://www.data.go.kr/data/15063556/fileData.do

Alerts

처분대상구분 has constant value ""Constant
법원이송구분 has constant value ""Constant
시정조치 has constant value ""Constant
시도코드 is highly overall correlated with 시군구코드 and 1 other fieldsHigh correlation
시군구코드 is highly overall correlated with 시도코드 and 1 other fieldsHigh correlation
영업정지 is highly overall correlated with 등록취소High correlation
등록취소 is highly overall correlated with 영업정지High correlation
비고 is highly overall correlated with 시도코드 and 1 other fieldsHigh correlation
영업정지 has 45 (39.8%) zerosZeros
등록취소 has 60 (53.1%) zerosZeros

Reproduction

Analysis started2023-12-12 20:47:18.117346
Analysis finished2023-12-12 20:47:22.158621
Duration4.04 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

처분종료년도
Real number (ℝ)

Distinct7
Distinct (%)6.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2018.5752
Minimum2016
Maximum2022
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.1 KiB
2023-12-13T05:47:22.225009image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum2016
5-th percentile2016
Q12017
median2018
Q32020
95-th percentile2022
Maximum2022
Range6
Interquartile range (IQR)3

Descriptive statistics

Standard deviation2.0169164
Coefficient of variation (CV)0.00099917825
Kurtosis-1.2673317
Mean2018.5752
Median Absolute Deviation (MAD)2
Skewness0.30051273
Sum228099
Variance4.067952
MonotonicityIncreasing
2023-12-13T05:47:22.365337image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=7)
ValueCountFrequency (%)
2017 25
22.1%
2020 21
18.6%
2016 20
17.7%
2018 19
16.8%
2021 12
10.6%
2022 12
10.6%
2019 4
 
3.5%
ValueCountFrequency (%)
2016 20
17.7%
2017 25
22.1%
2018 19
16.8%
2019 4
 
3.5%
2020 21
18.6%
2021 12
10.6%
2022 12
10.6%
ValueCountFrequency (%)
2022 12
10.6%
2021 12
10.6%
2020 21
18.6%
2019 4
 
3.5%
2018 19
16.8%
2017 25
22.1%
2016 20
17.7%

시도코드
Real number (ℝ)

HIGH CORRELATION 

Distinct13
Distinct (%)11.5%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean30.168142
Minimum11
Maximum51
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.1 KiB
2023-12-13T05:47:22.515880image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum11
5-th percentile11
Q111
median36
Q341
95-th percentile49.2
Maximum51
Range40
Interquartile range (IQR)30

Descriptive statistics

Standard deviation14.237089
Coefficient of variation (CV)0.47192461
Kurtosis-1.479806
Mean30.168142
Median Absolute Deviation (MAD)10
Skewness-0.29036419
Sum3409
Variance202.69469
MonotonicityNot monotonic
2023-12-13T05:47:22.674904image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=13)
ValueCountFrequency (%)
41 38
33.6%
11 34
30.1%
26 14
 
12.4%
51 6
 
5.3%
28 5
 
4.4%
47 3
 
2.7%
48 2
 
1.8%
29 2
 
1.8%
36 2
 
1.8%
45 2
 
1.8%
Other values (3) 5
 
4.4%
ValueCountFrequency (%)
11 34
30.1%
26 14
 
12.4%
28 5
 
4.4%
29 2
 
1.8%
30 1
 
0.9%
36 2
 
1.8%
41 38
33.6%
44 2
 
1.8%
45 2
 
1.8%
46 2
 
1.8%
ValueCountFrequency (%)
51 6
 
5.3%
48 2
 
1.8%
47 3
 
2.7%
46 2
 
1.8%
45 2
 
1.8%
44 2
 
1.8%
41 38
33.6%
36 2
 
1.8%
30 1
 
0.9%
29 2
 
1.8%

시군구코드
Real number (ℝ)

HIGH CORRELATION 

Distinct72
Distinct (%)63.7%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean30540.938
Minimum11110
Maximum51770
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.1 KiB
2023-12-13T05:47:22.883060image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum11110
5-th percentile11209
Q111680
median36110
Q341463
95-th percentile49442
Maximum51770
Range40660
Interquartile range (IQR)29783

Descriptive statistics

Standard deviation14150.89
Coefficient of variation (CV)0.46334169
Kurtosis-1.479711
Mean30540.938
Median Absolute Deviation (MAD)9610
Skewness-0.28610625
Sum3451126
Variance2.0024769 × 108
MonotonicityNot monotonic
2023-12-13T05:47:23.109983image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
11680 6
 
5.3%
11710 5
 
4.4%
41590 4
 
3.5%
41465 4
 
3.5%
11650 4
 
3.5%
41135 4
 
3.5%
11545 3
 
2.7%
41273 3
 
2.7%
41390 2
 
1.8%
26530 2
 
1.8%
Other values (62) 76
67.3%
ValueCountFrequency (%)
11110 1
0.9%
11140 2
1.8%
11170 1
0.9%
11200 2
1.8%
11215 1
0.9%
11290 1
0.9%
11410 1
0.9%
11440 2
1.8%
11470 1
0.9%
11530 2
1.8%
ValueCountFrequency (%)
51770 1
0.9%
51720 1
0.9%
51210 1
0.9%
51130 2
1.8%
51110 1
0.9%
48330 1
0.9%
48310 1
0.9%
47290 1
0.9%
47150 1
0.9%
47130 1
0.9%

처분대상구분
Categorical

CONSTANT 

Distinct1
Distinct (%)0.9%
Missing0
Missing (%)0.0%
Memory size1.0 KiB
0
113 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 113
100.0%

Length

2023-12-13T05:47:23.308150image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T05:47:23.454484image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 113
100.0%

법원이송구분
Categorical

CONSTANT 

Distinct1
Distinct (%)0.9%
Missing0
Missing (%)0.0%
Memory size1.0 KiB
0
113 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 113
100.0%

Length

2023-12-13T05:47:23.575698image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T05:47:23.684277image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 113
100.0%

시정조치
Categorical

CONSTANT 

Distinct1
Distinct (%)0.9%
Missing0
Missing (%)0.0%
Memory size1.0 KiB
0
113 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 113
100.0%

Length

2023-12-13T05:47:23.814587image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T05:47:23.950140image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 113
100.0%

영업정지
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct7
Distinct (%)6.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.91150442
Minimum0
Maximum6
Zeros45
Zeros (%)39.8%
Negative0
Negative (%)0.0%
Memory size1.1 KiB
2023-12-13T05:47:24.079689image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median1
Q31
95-th percentile2.4
Maximum6
Range6
Interquartile range (IQR)1

Descriptive statistics

Standard deviation1.1064545
Coefficient of variation (CV)1.2138772
Kurtosis6.2262051
Mean0.91150442
Median Absolute Deviation (MAD)1
Skewness2.1504952
Sum103
Variance1.2242415
MonotonicityNot monotonic
2023-12-13T05:47:24.238832image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=7)
ValueCountFrequency (%)
1 48
42.5%
0 45
39.8%
2 14
 
12.4%
5 2
 
1.8%
4 2
 
1.8%
3 1
 
0.9%
6 1
 
0.9%
ValueCountFrequency (%)
0 45
39.8%
1 48
42.5%
2 14
 
12.4%
3 1
 
0.9%
4 2
 
1.8%
5 2
 
1.8%
6 1
 
0.9%
ValueCountFrequency (%)
6 1
 
0.9%
5 2
 
1.8%
4 2
 
1.8%
3 1
 
0.9%
2 14
 
12.4%
1 48
42.5%
0 45
39.8%

등록취소
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct9
Distinct (%)8.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.94690265
Minimum0
Maximum12
Zeros60
Zeros (%)53.1%
Negative0
Negative (%)0.0%
Memory size1.1 KiB
2023-12-13T05:47:24.389930image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q31
95-th percentile3
Maximum12
Range12
Interquartile range (IQR)1

Descriptive statistics

Standard deviation1.8411987
Coefficient of variation (CV)1.9444435
Kurtosis17.562841
Mean0.94690265
Median Absolute Deviation (MAD)0
Skewness3.8452198
Sum107
Variance3.3900126
MonotonicityNot monotonic
2023-12-13T05:47:24.577877image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=9)
ValueCountFrequency (%)
0 60
53.1%
1 35
31.0%
2 8
 
7.1%
3 5
 
4.4%
6 1
 
0.9%
5 1
 
0.9%
12 1
 
0.9%
8 1
 
0.9%
10 1
 
0.9%
ValueCountFrequency (%)
0 60
53.1%
1 35
31.0%
2 8
 
7.1%
3 5
 
4.4%
5 1
 
0.9%
6 1
 
0.9%
8 1
 
0.9%
10 1
 
0.9%
12 1
 
0.9%
ValueCountFrequency (%)
12 1
 
0.9%
10 1
 
0.9%
8 1
 
0.9%
6 1
 
0.9%
5 1
 
0.9%
3 5
 
4.4%
2 8
 
7.1%
1 35
31.0%
0 60
53.1%

비고
Categorical

HIGH CORRELATION 

Distinct13
Distinct (%)11.5%
Missing0
Missing (%)0.0%
Memory size1.0 KiB
경기도
38 
서울특별시
34 
부산광역시
14 
강원특별자치도
6 
인천광역시
5 
Other values (8)
16 

Length

Max length7
Median length5
Mean length4.3716814
Min length3

Unique

Unique1 ?
Unique (%)0.9%

Sample

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

Common Values

ValueCountFrequency (%)
경기도 38
33.6%
서울특별시 34
30.1%
부산광역시 14
 
12.4%
강원특별자치도 6
 
5.3%
인천광역시 5
 
4.4%
경상북도 3
 
2.7%
경상남도 2
 
1.8%
광주광역시 2
 
1.8%
세종특별자치시 2
 
1.8%
전라북도 2
 
1.8%
Other values (3) 5
 
4.4%

Length

2023-12-13T05:47:24.797586image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
경기도 38
33.6%
서울특별시 34
30.1%
부산광역시 14
 
12.4%
강원특별자치도 6
 
5.3%
인천광역시 5
 
4.4%
경상북도 3
 
2.7%
경상남도 2
 
1.8%
광주광역시 2
 
1.8%
세종특별자치시 2
 
1.8%
전라북도 2
 
1.8%
Other values (3) 5
 
4.4%

Interactions

2023-12-13T05:47:21.188234image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T05:47:18.363661image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T05:47:19.029806image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T05:47:19.648664image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T05:47:20.575492image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T05:47:21.309203image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T05:47:18.547357image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T05:47:19.156486image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T05:47:19.767612image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T05:47:20.681117image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T05:47:21.442633image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T05:47:18.662155image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T05:47:19.281122image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T05:47:19.890008image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T05:47:20.813421image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T05:47:21.583039image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T05:47:18.815958image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T05:47:19.402206image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T05:47:20.342430image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T05:47:20.940536image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T05:47:21.700671image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T05:47:18.928846image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T05:47:19.542374image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T05:47:20.454947image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T05:47:21.074700image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-13T05:47:24.908115image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
처분종료년도시도코드시군구코드영업정지등록취소비고
처분종료년도1.0000.4340.4350.4990.2160.632
시도코드0.4341.0001.0000.2000.0541.000
시군구코드0.4351.0001.0000.1870.0601.000
영업정지0.4990.2000.1871.0000.0000.000
등록취소0.2160.0540.0600.0001.0000.000
비고0.6321.0001.0000.0000.0001.000
2023-12-13T05:47:25.043645image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
처분종료년도시도코드시군구코드영업정지등록취소비고
처분종료년도1.0000.3690.3740.296-0.4590.315
시도코드0.3691.0000.9660.046-0.2200.971
시군구코드0.3740.9661.0000.078-0.2330.971
영업정지0.2960.0460.0781.000-0.7000.000
등록취소-0.459-0.220-0.233-0.7001.0000.000
비고0.3150.9710.9710.0000.0001.000

Missing values

2023-12-13T05:47:21.890556image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-13T05:47:22.079327image/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

처분종료년도시도코드시군구코드처분대상구분법원이송구분시정조치영업정지등록취소비고
02016111114000050서울특별시
12016111120000002서울특별시
22016111129000001서울특별시
32016111141000001서울특별시
42016111144000001서울특별시
52016111153000001서울특별시
62016111154500001서울특별시
72016111162000001서울특별시
82016111165000012서울특별시
92016111168000026서울특별시
처분종료년도시도코드시군구코드처분대상구분법원이송구분시정조치영업정지등록취소비고
1032022414113500010경기도
1042022414127100010경기도
1052022414146300010경기도
1062022414146500010경기도
1072022414159000050경기도
1082022414183000010경기도
1092022464611000020전라남도
1102022474715000010경상북도
1112022474729000010경상북도
1122022484831000001경상남도