Overview

Dataset statistics

Number of variables6
Number of observations500
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory26.5 KiB
Average record size in memory54.3 B

Variable types

Categorical3
Numeric3

Dataset

DescriptionSample
Author해봄데이터㈜
URLhttps://www.bigdata-coast.kr/gdsInfo/gdsInfoDetail.do?gdsCd=CT02HBM009

Alerts

CTOF_LO is highly overall correlated with CTOF_LA and 1 other fieldsHigh correlation
CTOF_LA is highly overall correlated with CTOF_LO and 1 other fieldsHigh correlation
SST is highly overall correlated with CTOF_YMDHigh correlation
FSASSN_SZN_CTSH is highly overall correlated with MTBT_NETBT_SZN_CTSHHigh correlation
MTBT_NETBT_SZN_CTSH is highly overall correlated with CTOF_LO and 2 other fieldsHigh correlation
CTOF_YMD is highly overall correlated with SSTHigh correlation

Reproduction

Analysis started2024-03-13 12:32:43.972978
Analysis finished2024-03-13 12:32:46.196295
Duration2.22 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

FSASSN_SZN_CTSH
Categorical

HIGH CORRELATION 

Distinct3
Distinct (%)0.6%
Missing0
Missing (%)0.0%
Memory size4.0 KiB
100
251 
0
213 
200
36 

Length

Max length3
Median length3
Mean length2.148
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row100
2nd row100
3rd row100
4th row100
5th row100

Common Values

ValueCountFrequency (%)
100 251
50.2%
0 213
42.6%
200 36
 
7.2%

Length

2024-03-13T21:32:46.309404image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-13T21:32:46.498377image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
100 251
50.2%
0 213
42.6%
200 36
 
7.2%

MTBT_NETBT_SZN_CTSH
Categorical

HIGH CORRELATION 

Distinct3
Distinct (%)0.6%
Missing0
Missing (%)0.0%
Memory size4.0 KiB
100
276 
0
179 
200
45 

Length

Max length3
Median length3
Mean length2.284
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
100 276
55.2%
0 179
35.8%
200 45
 
9.0%

Length

2024-03-13T21:32:46.696882image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-13T21:32:46.888373image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
100 276
55.2%
0 179
35.8%
200 45
 
9.0%

CTOF_LO
Real number (ℝ)

HIGH CORRELATION 

Distinct21
Distinct (%)4.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean126.265
Minimum124.583
Maximum127.917
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size4.5 KiB
2024-03-13T21:32:47.088409image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum124.583
5-th percentile124.583
Q1125.417
median126.25
Q3127.25
95-th percentile127.917
Maximum127.917
Range3.334
Interquartile range (IQR)1.833

Descriptive statistics

Standard deviation1.048753
Coefficient of variation (CV)0.0083059679
Kurtosis-1.2529047
Mean126.265
Median Absolute Deviation (MAD)0.833
Skewness-0.02681825
Sum63132.499
Variance1.0998829
MonotonicityNot monotonic
2024-03-13T21:32:47.320567image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=21)
ValueCountFrequency (%)
125.583 33
 
6.6%
125.917 33
 
6.6%
125.75 33
 
6.6%
124.917 30
 
6.0%
124.75 30
 
6.0%
124.583 30
 
6.0%
127.25 27
 
5.4%
127.917 27
 
5.4%
127.75 27
 
5.4%
127.583 27
 
5.4%
Other values (11) 203
40.6%
ValueCountFrequency (%)
124.583 30
6.0%
124.75 30
6.0%
124.917 30
6.0%
125.083 12
 
2.4%
125.25 12
 
2.4%
125.417 12
 
2.4%
125.583 33
6.6%
125.75 33
6.6%
125.917 33
6.6%
126.083 22
4.4%
ValueCountFrequency (%)
127.917 27
5.4%
127.75 27
5.4%
127.583 27
5.4%
127.417 27
5.4%
127.25 27
5.4%
127.083 27
5.4%
126.917 18
3.6%
126.75 17
3.4%
126.583 17
3.4%
126.417 18
3.6%

CTOF_LA
Real number (ℝ)

HIGH CORRELATION 

Distinct30
Distinct (%)6.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean34.394662
Minimum32.083
Maximum36.917
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size4.5 KiB
2024-03-13T21:32:47.608885image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum32.083
5-th percentile32.417
Q133.20825
median34.25
Q335.583
95-th percentile36.583
Maximum36.917
Range4.834
Interquartile range (IQR)2.37475

Descriptive statistics

Standard deviation1.3629123
Coefficient of variation (CV)0.039625694
Kurtosis-1.1995494
Mean34.394662
Median Absolute Deviation (MAD)1.167
Skewness0.13303779
Sum17197.331
Variance1.85753
MonotonicityNot monotonic
2024-03-13T21:32:47.812930image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=30)
ValueCountFrequency (%)
32.583 26
 
5.2%
33.25 24
 
4.8%
33.083 24
 
4.8%
32.917 24
 
4.8%
32.75 24
 
4.8%
33.417 21
 
4.2%
35.75 18
 
3.6%
34.25 18
 
3.6%
35.917 18
 
3.6%
34.083 18
 
3.6%
Other values (20) 285
57.0%
ValueCountFrequency (%)
32.083 9
 
1.8%
32.25 9
 
1.8%
32.417 9
 
1.8%
32.583 26
5.2%
32.75 24
4.8%
32.917 24
4.8%
33.083 24
4.8%
33.25 24
4.8%
33.417 21
4.2%
33.583 15
3.0%
ValueCountFrequency (%)
36.917 10
2.0%
36.75 11
2.2%
36.583 12
2.4%
36.417 15
3.0%
36.25 15
3.0%
36.083 15
3.0%
35.917 18
3.6%
35.75 18
3.6%
35.583 18
3.6%
35.417 18
3.6%

CTOF_YMD
Categorical

HIGH CORRELATION 

Distinct4
Distinct (%)0.8%
Missing0
Missing (%)0.0%
Memory size4.0 KiB
20210814
165 
20210807
144 
20210821
108 
20210828
83 

Length

Max length8
Median length8
Mean length8
Min length8

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row20210807
2nd row20210807
3rd row20210807
4th row20210807
5th row20210807

Common Values

ValueCountFrequency (%)
20210814 165
33.0%
20210807 144
28.8%
20210821 108
21.6%
20210828 83
16.6%

Length

2024-03-13T21:32:48.072471image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-13T21:32:48.233932image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
20210814 165
33.0%
20210807 144
28.8%
20210821 108
21.6%
20210828 83
16.6%

SST
Real number (ℝ)

HIGH CORRELATION 

Distinct11
Distinct (%)2.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean22.08
Minimum3
Maximum35
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size4.5 KiB
2024-03-13T21:32:48.382508image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum3
5-th percentile3
Q124
median25
Q327
95-th percentile28
Maximum35
Range32
Interquartile range (IQR)3

Descriptive statistics

Standard deviation8.5655319
Coefficient of variation (CV)0.3879317
Kurtosis1.1080895
Mean22.08
Median Absolute Deviation (MAD)1
Skewness-1.7121683
Sum11040
Variance73.368337
MonotonicityNot monotonic
2024-03-13T21:32:48.536111image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=11)
ValueCountFrequency (%)
27 125
25.0%
25 122
24.4%
26 81
16.2%
3 74
14.8%
24 52
10.4%
28 26
 
5.2%
4 9
 
1.8%
23 8
 
1.6%
22 1
 
0.2%
34 1
 
0.2%
ValueCountFrequency (%)
3 74
14.8%
4 9
 
1.8%
22 1
 
0.2%
23 8
 
1.6%
24 52
10.4%
25 122
24.4%
26 81
16.2%
27 125
25.0%
28 26
 
5.2%
34 1
 
0.2%
ValueCountFrequency (%)
35 1
 
0.2%
34 1
 
0.2%
28 26
 
5.2%
27 125
25.0%
26 81
16.2%
25 122
24.4%
24 52
10.4%
23 8
 
1.6%
22 1
 
0.2%
4 9
 
1.8%

Interactions

2024-03-13T21:32:45.403526image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T21:32:44.338440image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T21:32:44.848948image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T21:32:45.561757image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T21:32:44.486094image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T21:32:45.031584image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T21:32:45.725223image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T21:32:44.650820image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T21:32:45.192047image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-03-13T21:32:48.688583image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
FSASSN_SZN_CTSHMTBT_NETBT_SZN_CTSHCTOF_LOCTOF_LACTOF_YMDSST
FSASSN_SZN_CTSH1.0000.8610.5970.6110.4770.373
MTBT_NETBT_SZN_CTSH0.8611.0000.8110.7540.4590.477
CTOF_LO0.5970.8111.0000.7910.4650.609
CTOF_LA0.6110.7540.7911.0000.4860.566
CTOF_YMD0.4770.4590.4650.4861.0000.732
SST0.3730.4770.6090.5660.7321.000
2024-03-13T21:32:48.860789image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
FSASSN_SZN_CTSHMTBT_NETBT_SZN_CTSHCTOF_YMD
FSASSN_SZN_CTSH1.0000.5490.473
MTBT_NETBT_SZN_CTSH0.5491.0000.454
CTOF_YMD0.4730.4541.000
2024-03-13T21:32:49.005415image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
CTOF_LOCTOF_LASSTFSASSN_SZN_CTSHMTBT_NETBT_SZN_CTSHCTOF_YMD
CTOF_LO1.000-0.693-0.0160.4380.7030.294
CTOF_LA-0.6931.000-0.0960.4520.6220.309
SST-0.016-0.0961.0000.3030.4090.673
FSASSN_SZN_CTSH0.4380.4520.3031.0000.5490.473
MTBT_NETBT_SZN_CTSH0.7030.6220.4090.5491.0000.454
CTOF_YMD0.2940.3090.6730.4730.4541.000

Missing values

2024-03-13T21:32:45.949374image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-03-13T21:32:46.124724image/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

FSASSN_SZN_CTSHMTBT_NETBT_SZN_CTSHCTOF_LOCTOF_LACTOF_YMDSST
01000125.58334.0832021080728
11000125.7534.0832021080727
21000125.91734.0832021080727
31000125.58334.252021080727
41000125.7534.252021080726
51000125.91734.252021080725
61000125.58334.4172021080727
71000125.7534.4172021080726
81000125.91734.4172021080724
91000125.58334.5832021080726
FSASSN_SZN_CTSHMTBT_NETBT_SZN_CTSHCTOF_LOCTOF_LACTOF_YMDSST
4901000126.2536.083202108284
4911000126.41736.083202108283
4921000126.08336.25202108283
4931000126.2536.25202108284
4941000126.41736.25202108283
4951000126.08336.417202108283
4961000126.2536.417202108283
4971000126.41736.417202108283
4980100126.08332.583202108283
4990100126.2532.583202108283