Overview

Dataset statistics

Number of variables3
Number of observations47
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory1.3 KiB
Average record size in memory28.8 B

Variable types

Categorical1
Numeric2

Dataset

Description대책여부,년도,기준
Author서울특별시
URLhttps://data.seoul.go.kr/dataList/OA-22147/S/1/datasetView.do

Alerts

기준 is highly overall correlated with 대책여부High correlation
대책여부 is highly overall correlated with 기준High correlation

Reproduction

Analysis started2024-05-18 05:29:43.323324
Analysis finished2024-05-18 05:29:45.069765
Duration1.75 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

대책여부
Categorical

HIGH CORRELATION 

Distinct3
Distinct (%)6.4%
Missing0
Missing (%)0.0%
Memory size508.0 B
기준초과지점수
20 
대책기준초과지점수
17 
총조사지점수
10 

Length

Max length9
Median length7
Mean length7.5106383
Min length6

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
기준초과지점수 20
42.6%
대책기준초과지점수 17
36.2%
총조사지점수 10
21.3%

Length

2024-05-18T14:29:45.272811image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-18T14:29:45.561095image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
기준초과지점수 20
42.6%
대책기준초과지점수 17
36.2%
총조사지점수 10
21.3%

년도
Real number (ℝ)

Distinct21
Distinct (%)44.7%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2012.9574
Minimum2003
Maximum2023
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size555.0 B
2024-05-18T14:29:45.973502image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum2003
5-th percentile2004.3
Q12009
median2013
Q32017
95-th percentile2021.7
Maximum2023
Range20
Interquartile range (IQR)8

Descriptive statistics

Standard deviation5.5126631
Coefficient of variation (CV)0.002738589
Kurtosis-1.005345
Mean2012.9574
Median Absolute Deviation (MAD)4
Skewness0.023916163
Sum94609
Variance30.389454
MonotonicityNot monotonic
2024-05-18T14:29:46.656007image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=21)
ValueCountFrequency (%)
2016 3
 
6.4%
2009 3
 
6.4%
2010 3
 
6.4%
2015 3
 
6.4%
2013 3
 
6.4%
2011 3
 
6.4%
2012 3
 
6.4%
2017 3
 
6.4%
2021 2
 
4.3%
2019 2
 
4.3%
Other values (11) 19
40.4%
ValueCountFrequency (%)
2003 1
 
2.1%
2004 2
4.3%
2005 2
4.3%
2006 2
4.3%
2007 2
4.3%
2008 2
4.3%
2009 3
6.4%
2010 3
6.4%
2011 3
6.4%
2012 3
6.4%
ValueCountFrequency (%)
2023 1
 
2.1%
2022 2
4.3%
2021 2
4.3%
2020 2
4.3%
2019 2
4.3%
2018 2
4.3%
2017 3
6.4%
2016 3
6.4%
2015 3
6.4%
2014 1
 
2.1%

기준
Real number (ℝ)

HIGH CORRELATION 

Distinct29
Distinct (%)61.7%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean103.38298
Minimum1
Maximum608
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size555.0 B
2024-05-18T14:29:47.115402image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile2
Q15
median11
Q318.5
95-th percentile500.9
Maximum608
Range607
Interquartile range (IQR)13.5

Descriptive statistics

Standard deviation187.90048
Coefficient of variation (CV)1.8175185
Kurtosis0.94508101
Mean103.38298
Median Absolute Deviation (MAD)7
Skewness1.6138396
Sum4859
Variance35306.589
MonotonicityNot monotonic
2024-05-18T14:29:47.478410image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=29)
ValueCountFrequency (%)
4 4
 
8.5%
6 3
 
6.4%
5 3
 
6.4%
2 3
 
6.4%
12 3
 
6.4%
3 3
 
6.4%
11 2
 
4.3%
7 2
 
4.3%
10 2
 
4.3%
16 2
 
4.3%
Other values (19) 20
42.6%
ValueCountFrequency (%)
1 1
 
2.1%
2 3
6.4%
3 3
6.4%
4 4
8.5%
5 3
6.4%
6 3
6.4%
7 2
4.3%
8 1
 
2.1%
9 1
 
2.1%
10 2
4.3%
ValueCountFrequency (%)
608 1
2.1%
574 1
2.1%
524 1
2.1%
447 1
2.1%
431 1
2.1%
415 1
2.1%
408 1
2.1%
406 1
2.1%
373 1
2.1%
347 1
2.1%

Interactions

2024-05-18T14:29:44.125467image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-18T14:29:43.528442image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-18T14:29:44.402983image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-18T14:29:43.865074image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-05-18T14:29:47.763162image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
대책여부년도기준
대책여부1.0000.0000.922
년도0.0001.0000.000
기준0.9220.0001.000
2024-05-18T14:29:48.099298image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
년도기준대책여부
년도1.0000.1460.000
기준0.1461.0000.640
대책여부0.0000.6401.000

Missing values

2024-05-18T14:29:44.711326image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-05-18T14:29:44.990262image/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

대책여부년도기준
0총조사지점수2016447
1총조사지점수2017415
2총조사지점수2009431
3총조사지점수2010608
4총조사지점수2014406
5총조사지점수2015408
6총조사지점수2013574
7총조사지점수2011373
8총조사지점수2012524
9총조사지점수2018347
대책여부년도기준
37대책기준초과지점수20227
38대책기준초과지점수20132
39대책기준초과지점수200812
40대책기준초과지점수20196
41대책기준초과지점수20114
42대책기준초과지점수20203
43대책기준초과지점수20072
44대책기준초과지점수20124
45대책기준초과지점수20041
46대책기준초과지점수20066