Overview

Dataset statistics

Number of variables3
Number of observations952
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory24.3 KiB
Average record size in memory26.1 B

Variable types

Numeric2
Categorical1

Dataset

Description시도별 어음부도율
Author제주데이터허브
URLhttps://www.jejudatahub.net/data/view/data/553

Alerts

단위(%) has 73 (7.7%) zerosZeros

Reproduction

Analysis started2023-12-11 19:52:51.313284
Analysis finished2023-12-11 19:52:52.659822
Duration1.35 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

연월
Real number (ℝ)

Distinct56
Distinct (%)5.9%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean201991.93
Minimum201801
Maximum202208
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size8.5 KiB
2023-12-12T04:52:52.762860image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum201801
5-th percentile201803
Q1201902.75
median202004.5
Q3202106.25
95-th percentile202206
Maximum202208
Range407
Interquartile range (IQR)203.5

Descriptive statistics

Standard deviation135.18709
Coefficient of variation (CV)0.00066926976
Kurtosis-1.2166155
Mean201991.93
Median Absolute Deviation (MAD)102
Skewness0.079054352
Sum1.9229632 × 108
Variance18275.549
MonotonicityIncreasing
2023-12-12T04:52:53.014880image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
201801 17
 
1.8%
202006 17
 
1.8%
202008 17
 
1.8%
202009 17
 
1.8%
202010 17
 
1.8%
202011 17
 
1.8%
202012 17
 
1.8%
202101 17
 
1.8%
202102 17
 
1.8%
202103 17
 
1.8%
Other values (46) 782
82.1%
ValueCountFrequency (%)
201801 17
1.8%
201802 17
1.8%
201803 17
1.8%
201804 17
1.8%
201805 17
1.8%
201806 17
1.8%
201807 17
1.8%
201808 17
1.8%
201809 17
1.8%
201810 17
1.8%
ValueCountFrequency (%)
202208 17
1.8%
202207 17
1.8%
202206 17
1.8%
202205 17
1.8%
202204 17
1.8%
202203 17
1.8%
202202 17
1.8%
202201 17
1.8%
202112 17
1.8%
202111 17
1.8%

시도
Categorical

Distinct17
Distinct (%)1.8%
Missing0
Missing (%)0.0%
Memory size7.6 KiB
전국
 
56
서울
 
56
부산
 
56
대구
 
56
인천
 
56
Other values (12)
672 

Length

Max length2
Median length2
Mean length2
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row전국
2nd row서울
3rd row부산
4th row대구
5th row인천

Common Values

ValueCountFrequency (%)
전국 56
 
5.9%
서울 56
 
5.9%
부산 56
 
5.9%
대구 56
 
5.9%
인천 56
 
5.9%
광주 56
 
5.9%
대전 56
 
5.9%
울산 56
 
5.9%
경기 56
 
5.9%
강원 56
 
5.9%
Other values (7) 392
41.2%

Length

2023-12-12T04:52:53.218645image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
전국 56
 
5.9%
강원 56
 
5.9%
경남 56
 
5.9%
경북 56
 
5.9%
전남 56
 
5.9%
전북 56
 
5.9%
충남 56
 
5.9%
충북 56
 
5.9%
경기 56
 
5.9%
서울 56
 
5.9%
Other values (7) 392
41.2%

단위(%)
Real number (ℝ)

ZEROS 

Distinct114
Distinct (%)12.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.23696429
Minimum0
Maximum7.57
Zeros73
Zeros (%)7.7%
Negative0
Negative (%)0.0%
Memory size8.5 KiB
2023-12-12T04:52:53.401132image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10.04
median0.09
Q30.23
95-th percentile0.8045
Maximum7.57
Range7.57
Interquartile range (IQR)0.19

Descriptive statistics

Standard deviation0.5596143
Coefficient of variation (CV)2.3615977
Kurtosis77.983388
Mean0.23696429
Median Absolute Deviation (MAD)0.07
Skewness7.7453948
Sum225.59
Variance0.31316817
MonotonicityNot monotonic
2023-12-12T04:52:53.589493image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.0 73
 
7.7%
0.01 58
 
6.1%
0.02 52
 
5.5%
0.03 48
 
5.0%
0.06 48
 
5.0%
0.04 46
 
4.8%
0.08 45
 
4.7%
0.05 43
 
4.5%
0.07 34
 
3.6%
0.09 32
 
3.4%
Other values (104) 473
49.7%
ValueCountFrequency (%)
0.0 73
7.7%
0.01 58
6.1%
0.02 52
5.5%
0.03 48
5.0%
0.04 46
4.8%
0.05 43
4.5%
0.06 48
5.0%
0.07 34
3.6%
0.08 45
4.7%
0.09 32
3.4%
ValueCountFrequency (%)
7.57 1
0.1%
7.25 1
0.1%
5.73 1
0.1%
4.63 1
0.1%
3.98 1
0.1%
3.94 1
0.1%
3.88 1
0.1%
3.52 1
0.1%
3.07 1
0.1%
2.91 1
0.1%

Interactions

2023-12-12T04:52:52.205706image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T04:52:51.869426image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T04:52:52.342275image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T04:52:52.040617image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-12T04:52:53.705028image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
연월시도단위(%)
연월1.0000.0000.052
시도0.0001.0000.253
단위(%)0.0520.2531.000
2023-12-12T04:52:53.809934image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
연월단위(%)시도
연월1.000-0.3030.000
단위(%)-0.3031.0000.103
시도0.0000.1031.000

Missing values

2023-12-12T04:52:52.499897image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-12T04:52:52.612208image/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

연월시도단위(%)
0201801전국0.15
1201801서울0.11
2201801부산0.21
3201801대구0.35
4201801인천0.12
5201801광주0.12
6201801대전0.12
7201801울산0.03
8201801경기0.67
9201801강원0.02
연월시도단위(%)
942202208울산0.0
943202208경기0.11
944202208강원0.0
945202208충북0.0
946202208충남0.0
947202208전북0.17
948202208전남0.01
949202208경북0.09
950202208경남0.01
951202208제주0.01