Overview

Dataset statistics

Number of variables5
Number of observations500
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory22.1 KiB
Average record size in memory45.3 B

Variable types

Categorical2
Numeric3

Dataset

DescriptionSample
Author해봄데이터㈜
URLhttps://www.bigdata-coast.kr/gdsInfo/gdsInfoDetail.do?gdsCd=CT02HBM008

Alerts

CTOF_LA is highly overall correlated with SSTHigh correlation
SST is highly overall correlated with CTOF_LAHigh correlation
SQDJG_CTSH is highly imbalanced (87.0%)Imbalance

Reproduction

Analysis started2024-03-13 12:43:26.432128
Analysis finished2024-03-13 12:43:28.554921
Duration2.12 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

SQDJG_CTSH
Categorical

IMBALANCE 

Distinct2
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Memory size4.0 KiB
10
491 
30
 
9

Length

Max length2
Median length2
Mean length2
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row10
2nd row10
3rd row10
4th row10
5th row10

Common Values

ValueCountFrequency (%)
10 491
98.2%
30 9
 
1.8%

Length

2024-03-13T21:43:28.679561image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-13T21:43:28.821537image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
10 491
98.2%
30 9
 
1.8%

CTOF_LO
Real number (ℝ)

Distinct33
Distinct (%)6.6%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean131.04201
Minimum128.583
Maximum133.917
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size4.5 KiB
2024-03-13T21:43:28.974887image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum128.583
5-th percentile129.25
Q1129.917
median130.917
Q3132.083
95-th percentile133.583
Maximum133.917
Range5.334
Interquartile range (IQR)2.166

Descriptive statistics

Standard deviation1.3565971
Coefficient of variation (CV)0.010352384
Kurtosis-0.73732004
Mean131.04201
Median Absolute Deviation (MAD)1
Skewness0.43831894
Sum65521.003
Variance1.8403557
MonotonicityNot monotonic
2024-03-13T21:43:29.193734image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=33)
ValueCountFrequency (%)
129.917 27
 
5.4%
129.583 27
 
5.4%
129.75 27
 
5.4%
131.25 22
 
4.4%
131.083 22
 
4.4%
131.417 22
 
4.4%
130.583 21
 
4.2%
130.75 21
 
4.2%
130.917 21
 
4.2%
130.25 21
 
4.2%
Other values (23) 269
53.8%
ValueCountFrequency (%)
128.583 2
 
0.4%
128.75 4
 
0.8%
128.917 5
 
1.0%
129.083 12
2.4%
129.25 18
3.6%
129.417 18
3.6%
129.583 27
5.4%
129.75 27
5.4%
129.917 27
5.4%
130.083 21
4.2%
ValueCountFrequency (%)
133.917 12
2.4%
133.75 12
2.4%
133.583 12
2.4%
133.417 6
 
1.2%
133.25 6
 
1.2%
133.083 6
 
1.2%
132.917 9
1.8%
132.75 9
1.8%
132.583 9
1.8%
132.417 16
3.2%

CTOF_LA
Real number (ℝ)

HIGH CORRELATION 

Distinct27
Distinct (%)5.4%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean37.55701
Minimum35.083
Maximum39.417
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size4.5 KiB
2024-03-13T21:43:29.389792image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum35.083
5-th percentile35.917
Q137.083
median37.583
Q338.25
95-th percentile38.75
Maximum39.417
Range4.334
Interquartile range (IQR)1.167

Descriptive statistics

Standard deviation0.86874593
Coefficient of variation (CV)0.023131392
Kurtosis0.33973888
Mean37.55701
Median Absolute Deviation (MAD)0.5
Skewness-0.69167856
Sum18778.505
Variance0.75471948
MonotonicityNot monotonic
2024-03-13T21:43:29.556956image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=27)
ValueCountFrequency (%)
37.417 45
 
9.0%
38.25 45
 
9.0%
38.417 45
 
9.0%
38.083 44
 
8.8%
37.917 35
 
7.0%
37.75 34
 
6.8%
37.25 34
 
6.8%
37.083 34
 
6.8%
37.583 33
 
6.6%
36.75 15
 
3.0%
Other values (17) 136
27.2%
ValueCountFrequency (%)
35.083 6
 
1.2%
35.25 6
 
1.2%
35.417 6
 
1.2%
35.583 3
 
0.6%
35.75 3
 
0.6%
35.917 3
 
0.6%
36.083 11
2.2%
36.25 11
2.2%
36.417 12
2.4%
36.583 15
3.0%
ValueCountFrequency (%)
39.417 3
 
0.6%
39.25 3
 
0.6%
39.083 3
 
0.6%
38.917 12
 
2.4%
38.75 12
 
2.4%
38.583 12
 
2.4%
38.417 45
9.0%
38.25 45
9.0%
38.083 44
8.8%
37.917 35
7.0%

CTOF_YMD
Categorical

Distinct3
Distinct (%)0.6%
Missing0
Missing (%)0.0%
Memory size4.0 KiB
20210828
196 
20210821
187 
20210814
117 

Length

Max length8
Median length8
Mean length8
Min length8

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row20210814
2nd row20210814
3rd row20210814
4th row20210814
5th row20210814

Common Values

ValueCountFrequency (%)
20210828 196
39.2%
20210821 187
37.4%
20210814 117
23.4%

Length

2024-03-13T21:43:29.725941image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-13T21:43:29.854590image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
20210828 196
39.2%
20210821 187
37.4%
20210814 117
23.4%

SST
Real number (ℝ)

HIGH CORRELATION 

Distinct8
Distinct (%)1.6%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean24.184
Minimum21
Maximum31
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size4.5 KiB
2024-03-13T21:43:29.985928image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum21
5-th percentile23
Q124
median24
Q325
95-th percentile26
Maximum31
Range10
Interquartile range (IQR)1

Descriptive statistics

Standard deviation1.0432261
Coefficient of variation (CV)0.043137036
Kurtosis3.4533172
Mean24.184
Median Absolute Deviation (MAD)1
Skewness0.67893429
Sum12092
Variance1.0883206
MonotonicityNot monotonic
2024-03-13T21:43:30.119193image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=8)
ValueCountFrequency (%)
24 223
44.6%
25 120
24.0%
23 91
18.2%
26 38
 
7.6%
22 19
 
3.8%
27 7
 
1.4%
31 1
 
0.2%
21 1
 
0.2%
ValueCountFrequency (%)
21 1
 
0.2%
22 19
 
3.8%
23 91
18.2%
24 223
44.6%
25 120
24.0%
26 38
 
7.6%
27 7
 
1.4%
31 1
 
0.2%
ValueCountFrequency (%)
31 1
 
0.2%
27 7
 
1.4%
26 38
 
7.6%
25 120
24.0%
24 223
44.6%
23 91
18.2%
22 19
 
3.8%
21 1
 
0.2%

Interactions

2024-03-13T21:43:27.830007image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T21:43:26.672736image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T21:43:27.456944image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T21:43:27.966065image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T21:43:26.779563image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T21:43:27.593090image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T21:43:28.087588image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T21:43:26.885658image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T21:43:27.710224image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-03-13T21:43:30.238402image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
SQDJG_CTSHCTOF_LOCTOF_LACTOF_YMDSST
SQDJG_CTSH1.0000.3500.1490.1440.000
CTOF_LO0.3501.0000.7190.4470.482
CTOF_LA0.1490.7191.0000.5420.540
CTOF_YMD0.1440.4470.5421.0000.425
SST0.0000.4820.5400.4251.000
2024-03-13T21:43:30.366010image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
SQDJG_CTSHCTOF_YMD
SQDJG_CTSH1.0000.237
CTOF_YMD0.2371.000
2024-03-13T21:43:30.490807image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
CTOF_LOCTOF_LASSTSQDJG_CTSHCTOF_YMD
CTOF_LO1.0000.479-0.4110.2670.302
CTOF_LA0.4791.000-0.5440.1130.383
SST-0.411-0.5441.0000.0000.299
SQDJG_CTSH0.2670.1130.0001.0000.237
CTOF_YMD0.3020.3830.2990.2371.000

Missing values

2024-03-13T21:43:28.273656image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-03-13T21:43:28.476807image/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

SQDJG_CTSHCTOF_LOCTOF_LACTOF_YMDSST
010131.08337.4172021081423
110131.2537.4172021081425
210131.41737.4172021081425
310131.58337.4172021081423
410131.7537.4172021081425
510131.91737.4172021081423
610132.08337.4172021081426
710132.2537.4172021081423
810132.41737.4172021081424
910130.58337.5832021081431
SQDJG_CTSHCTOF_LOCTOF_LACTOF_YMDSST
49010130.91738.4172021082823
49110131.08338.4172021082823
49210131.2538.4172021082824
49310131.41738.4172021082824
49410132.08338.4172021082824
49510132.2538.4172021082824
49610132.41738.4172021082825
49710133.08338.4172021082824
49810133.2538.4172021082824
49910133.41738.4172021082824