Overview

Dataset statistics

Number of variables4
Number of observations24
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory996.0 B
Average record size in memory41.5 B

Variable types

Categorical2
Numeric2

Dataset

DescriptionSample
Author㈜유에스티21
URLhttps://www.bigdata-coast.kr/gdsInfo/gdsInfoDetail.do?gdsCd=CT01UST005

Alerts

SHP_MVMN_YMDHM has constant value ""Constant
SHP_DN_VAL has unique valuesUnique

Reproduction

Analysis started2024-03-13 12:45:47.345700
Analysis finished2024-03-13 12:45:48.205998
Duration0.86 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

SHP_MVMN_YMDHM
Categorical

CONSTANT 

Distinct1
Distinct (%)4.2%
Missing0
Missing (%)0.0%
Memory size324.0 B
202002290000
24 

Length

Max length12
Median length12
Mean length12
Min length12

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row202002290000
2nd row202002290000
3rd row202002290000
4th row202002290000
5th row202002290000

Common Values

ValueCountFrequency (%)
202002290000 24
100.0%

Length

2024-03-13T21:45:48.295258image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-13T21:45:48.414338image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
202002290000 24
100.0%

SHP_LA
Real number (ℝ)

Distinct6
Distinct (%)25.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean34.375
Minimum33.75
Maximum35
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size348.0 B
2024-03-13T21:45:48.570745image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum33.75
5-th percentile33.75
Q134
median34.375
Q334.75
95-th percentile35
Maximum35
Range1.25
Interquartile range (IQR)0.75

Descriptive statistics

Standard deviation0.43613919
Coefficient of variation (CV)0.012687685
Kurtosis-1.2801484
Mean34.375
Median Absolute Deviation (MAD)0.375
Skewness0
Sum825
Variance0.19021739
MonotonicityDecreasing
2024-03-13T21:45:48.746062image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=6)
ValueCountFrequency (%)
35.0 4
16.7%
34.75 4
16.7%
34.5 4
16.7%
34.25 4
16.7%
34.0 4
16.7%
33.75 4
16.7%
ValueCountFrequency (%)
33.75 4
16.7%
34.0 4
16.7%
34.25 4
16.7%
34.5 4
16.7%
34.75 4
16.7%
35.0 4
16.7%
ValueCountFrequency (%)
35.0 4
16.7%
34.75 4
16.7%
34.5 4
16.7%
34.25 4
16.7%
34.0 4
16.7%
33.75 4
16.7%

SHP_LO
Categorical

Distinct4
Distinct (%)16.7%
Missing0
Missing (%)0.0%
Memory size324.0 B
125.0
6 
125.25
6 
125.5
6 
125.75
6 

Length

Max length6
Median length5.5
Mean length5.5
Min length5

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row125.0
2nd row125.25
3rd row125.5
4th row125.75
5th row125.0

Common Values

ValueCountFrequency (%)
125.0 6
25.0%
125.25 6
25.0%
125.5 6
25.0%
125.75 6
25.0%

Length

2024-03-13T21:45:48.912406image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-13T21:45:49.079206image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
125.0 6
25.0%
125.25 6
25.0%
125.5 6
25.0%
125.75 6
25.0%

SHP_DN_VAL
Real number (ℝ)

UNIQUE 

Distinct24
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean3212.1667
Minimum239
Maximum10965
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size348.0 B
2024-03-13T21:45:49.319395image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum239
5-th percentile264.75
Q11623.5
median2915
Q34287.75
95-th percentile7301.6
Maximum10965
Range10726
Interquartile range (IQR)2664.25

Descriptive statistics

Standard deviation2558.3555
Coefficient of variation (CV)0.7964579
Kurtosis2.3615591
Mean3212.1667
Median Absolute Deviation (MAD)1323
Skewness1.3102835
Sum77092
Variance6545183
MonotonicityNot monotonic
2024-03-13T21:45:49.597472image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=24)
ValueCountFrequency (%)
3093 1
 
4.2%
6132 1
 
4.2%
692 1
 
4.2%
337 1
 
4.2%
239 1
 
4.2%
1645 1
 
4.2%
3177 1
 
4.2%
1711 1
 
4.2%
2737 1
 
4.2%
1820 1
 
4.2%
Other values (14) 14
58.3%
ValueCountFrequency (%)
239 1
4.2%
252 1
4.2%
337 1
4.2%
661 1
4.2%
692 1
4.2%
1559 1
4.2%
1645 1
4.2%
1689 1
4.2%
1711 1
4.2%
1820 1
4.2%
ValueCountFrequency (%)
10965 1
4.2%
7508 1
4.2%
6132 1
4.2%
5432 1
4.2%
4902 1
4.2%
4536 1
4.2%
4205 1
4.2%
3996 1
4.2%
3956 1
4.2%
3605 1
4.2%

Interactions

2024-03-13T21:45:47.736701image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T21:45:47.490475image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T21:45:47.888865image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T21:45:47.621351image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-03-13T21:45:49.726909image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
SHP_LASHP_LOSHP_DN_VAL
SHP_LA1.0000.0000.367
SHP_LO0.0001.0000.665
SHP_DN_VAL0.3670.6651.000
2024-03-13T21:45:49.857219image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
SHP_LASHP_DN_VALSHP_LO
SHP_LA1.0000.2400.000
SHP_DN_VAL0.2401.0000.332
SHP_LO0.0000.3321.000

Missing values

2024-03-13T21:45:48.031887image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-03-13T21:45:48.156709image/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

SHP_MVMN_YMDHMSHP_LASHP_LOSHP_DN_VAL
020200229000035.0125.03093
120200229000035.0125.25661
220200229000035.0125.55432
320200229000035.0125.751559
420200229000034.75125.01689
520200229000034.75125.252243
620200229000034.75125.54536
720200229000034.75125.753996
820200229000034.5125.03956
920200229000034.5125.25252
SHP_MVMN_YMDHMSHP_LASHP_LOSHP_DN_VAL
1420200229000034.25125.57508
1520200229000034.25125.7510965
1620200229000034.0125.01820
1720200229000034.0125.252737
1820200229000034.0125.51711
1920200229000034.0125.753177
2020200229000033.75125.01645
2120200229000033.75125.25239
2220200229000033.75125.5337
2320200229000033.75125.75692