Overview

Dataset statistics

Number of variables11
Number of observations500
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory48.5 KiB
Average record size in memory99.3 B

Variable types

Categorical8
Numeric3

Dataset

DescriptionSample
Author해봄데이터㈜
URLhttps://www.bigdata-coast.kr/gdsInfo/gdsInfoDetail.do?gdsCd=CT02HBM007

Alerts

CTOF_LO is highly overall correlated with CTOF_LA and 3 other fieldsHigh correlation
CTOF_LA is highly overall correlated with CTOF_LO and 3 other fieldsHigh correlation
FSASSN_SZN_CTSH is highly overall correlated with NCHVY_FSATN_CTSH and 2 other fieldsHigh correlation
MTBT_NETBT_SZN_CTSH is highly overall correlated with CTOF_LO and 2 other fieldsHigh correlation
SQDJG_CTSH is highly overall correlated with CTOF_LO and 2 other fieldsHigh correlation
NCHVY_FSATN_CTSH is highly overall correlated with FSASSN_SZN_CTSH and 2 other fieldsHigh correlation
LGZ_NETBT_CTSH is highly overall correlated with FSASSN_SZN_CTSH and 2 other fieldsHigh correlation
FSGN_CTSH is highly overall correlated with FSASSN_SZN_CTSH and 2 other fieldsHigh correlation
CTOF_YMD is highly overall correlated with CTOF_LO and 3 other fieldsHigh correlation
FSASSN_SZN_CTSH is highly imbalanced (60.0%)Imbalance
FSLSPS_CTSH is highly imbalanced (71.0%)Imbalance
NCHVY_FSATN_CTSH is highly imbalanced (82.9%)Imbalance
LGZ_NETBT_CTSH is highly imbalanced (84.2%)Imbalance
FSGN_CTSH is highly imbalanced (88.0%)Imbalance

Reproduction

Analysis started2024-03-13 12:28:35.198138
Analysis finished2024-03-13 12:28:39.753571
Duration4.56 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

FSASSN_SZN_CTSH
Categorical

HIGH CORRELATION  IMBALANCE 

Distinct5
Distinct (%)1.0%
Missing0
Missing (%)0.0%
Memory size4.0 KiB
0
410 
100
54 
200
 
27
39
 
6
257
 
3

Length

Max length3
Median length1
Mean length1.348
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row200
4th row200
5th row200

Common Values

ValueCountFrequency (%)
0 410
82.0%
100 54
 
10.8%
200 27
 
5.4%
39 6
 
1.2%
257 3
 
0.6%

Length

2024-03-13T21:28:39.912081image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-13T21:28:40.185740image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 410
82.0%
100 54
 
10.8%
200 27
 
5.4%
39 6
 
1.2%
257 3
 
0.6%

MTBT_NETBT_SZN_CTSH
Categorical

HIGH CORRELATION 

Distinct3
Distinct (%)0.6%
Missing0
Missing (%)0.0%
Memory size4.0 KiB
0
393 
100
89 
200
 
18

Length

Max length3
Median length1
Mean length1.428
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row100
2nd row100
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 393
78.6%
100 89
 
17.8%
200 18
 
3.6%

Length

2024-03-13T21:28:40.521659image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-13T21:28:40.759805image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 393
78.6%
100 89
 
17.8%
200 18
 
3.6%

SQDJG_CTSH
Categorical

HIGH CORRELATION 

Distinct3
Distinct (%)0.6%
Missing0
Missing (%)0.0%
Memory size4.0 KiB
10
248 
0
243 
30
 
9

Length

Max length2
Median length2
Mean length1.514
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
10 248
49.6%
0 243
48.6%
30 9
 
1.8%

Length

2024-03-13T21:28:41.010944image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-13T21:28:41.229940image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
10 248
49.6%
0 243
48.6%
30 9
 
1.8%

FSLSPS_CTSH
Categorical

IMBALANCE 

Distinct3
Distinct (%)0.6%
Missing0
Missing (%)0.0%
Memory size4.0 KiB
0
462 
100
 
24
200
 
14

Length

Max length3
Median length1
Mean length1.152
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
0 462
92.4%
100 24
 
4.8%
200 14
 
2.8%

Length

2024-03-13T21:28:41.508826image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-13T21:28:41.740812image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 462
92.4%
100 24
 
4.8%
200 14
 
2.8%

NCHVY_FSATN_CTSH
Categorical

HIGH CORRELATION  IMBALANCE 

Distinct4
Distinct (%)0.8%
Missing0
Missing (%)0.0%
Memory size4.0 KiB
0
477 
125
 
9
437
 
8
226
 
6

Length

Max length3
Median length1
Mean length1.092
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
0 477
95.4%
125 9
 
1.8%
437 8
 
1.6%
226 6
 
1.2%

Length

2024-03-13T21:28:42.047113image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-13T21:28:42.324190image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 477
95.4%
125 9
 
1.8%
437 8
 
1.6%
226 6
 
1.2%

LGZ_NETBT_CTSH
Categorical

HIGH CORRELATION  IMBALANCE 

Distinct4
Distinct (%)0.8%
Missing0
Missing (%)0.0%
Memory size4.0 KiB
0
479 
373
 
9
24
 
6
28
 
6

Length

Max length3
Median length1
Mean length1.06
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
0 479
95.8%
373 9
 
1.8%
24 6
 
1.2%
28 6
 
1.2%

Length

2024-03-13T21:28:42.648223image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-13T21:28:42.974548image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 479
95.8%
373 9
 
1.8%
24 6
 
1.2%
28 6
 
1.2%

FSGN_CTSH
Categorical

HIGH CORRELATION  IMBALANCE 

Distinct4
Distinct (%)0.8%
Missing0
Missing (%)0.0%
Memory size4.0 KiB
0
485 
59
 
6
150
 
6
7
 
3

Length

Max length3
Median length1
Mean length1.036
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
0 485
97.0%
59 6
 
1.2%
150 6
 
1.2%
7 3
 
0.6%

Length

2024-03-13T21:28:43.251889image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-13T21:28:43.483093image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 485
97.0%
59 6
 
1.2%
150 6
 
1.2%
7 3
 
0.6%

CTOF_LO
Real number (ℝ)

HIGH CORRELATION 

Distinct51
Distinct (%)10.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean128.918
Minimum124.583
Maximum133.917
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size4.5 KiB
2024-03-13T21:28:43.750961image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum124.583
5-th percentile124.917
Q1126.5415
median129.25
Q3130.75
95-th percentile133.583
Maximum133.917
Range9.334
Interquartile range (IQR)4.2085

Descriptive statistics

Standard deviation2.5726111
Coefficient of variation (CV)0.019955407
Kurtosis-1.0134095
Mean128.918
Median Absolute Deviation (MAD)2
Skewness0.080064072
Sum64458.999
Variance6.6183278
MonotonicityNot monotonic
2024-03-13T21:28:44.083200image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
129.75 18
 
3.6%
129.917 18
 
3.6%
125.583 18
 
3.6%
125.75 18
 
3.6%
125.917 18
 
3.6%
129.583 18
 
3.6%
127.917 15
 
3.0%
127.75 15
 
3.0%
126.083 14
 
2.8%
127.583 14
 
2.8%
Other values (41) 334
66.8%
ValueCountFrequency (%)
124.583 12
2.4%
124.75 12
2.4%
124.917 12
2.4%
125.583 18
3.6%
125.75 18
3.6%
125.917 18
3.6%
126.083 14
2.8%
126.25 12
2.4%
126.417 9
1.8%
126.583 5
 
1.0%
ValueCountFrequency (%)
133.917 9
1.8%
133.75 9
1.8%
133.583 9
1.8%
132.917 6
1.2%
132.75 6
1.2%
132.583 6
1.2%
132.417 9
1.8%
132.25 9
1.8%
132.083 9
1.8%
131.917 6
1.2%

CTOF_LA
Real number (ℝ)

HIGH CORRELATION 

Distinct42
Distinct (%)8.4%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean35.907998
Minimum32.583
Maximum39.417
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size4.5 KiB
2024-03-13T21:28:44.381952image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum32.583
5-th percentile32.917
Q134.417
median36.083
Q337.417
95-th percentile38.75
Maximum39.417
Range6.834
Interquartile range (IQR)3

Descriptive statistics

Standard deviation1.804396
Coefficient of variation (CV)0.050250531
Kurtosis-1.0716966
Mean35.907998
Median Absolute Deviation (MAD)1.5
Skewness-0.075861864
Sum17953.999
Variance3.2558448
MonotonicityNot monotonic
2024-03-13T21:28:44.690412image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=42)
ValueCountFrequency (%)
37.417 21
 
4.2%
37.25 20
 
4.0%
37.083 20
 
4.0%
34.75 17
 
3.4%
34.583 16
 
3.2%
34.083 15
 
3.0%
35.083 15
 
3.0%
35.25 15
 
3.0%
35.417 15
 
3.0%
36.583 15
 
3.0%
Other values (32) 331
66.2%
ValueCountFrequency (%)
32.583 9
1.8%
32.75 9
1.8%
32.917 9
1.8%
33.083 12
2.4%
33.25 12
2.4%
33.417 11
2.2%
33.583 6
 
1.2%
33.75 9
1.8%
33.917 11
2.2%
34.083 15
3.0%
ValueCountFrequency (%)
39.417 3
 
0.6%
39.25 3
 
0.6%
39.083 3
 
0.6%
38.917 9
1.8%
38.75 9
1.8%
38.583 9
1.8%
38.417 12
2.4%
38.25 12
2.4%
38.083 12
2.4%
37.917 12
2.4%

CTOF_YMD
Categorical

HIGH CORRELATION 

Distinct2
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Memory size4.0 KiB
20210814
390 
20210821
110 

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 (%)
20210814 390
78.0%
20210821 110
 
22.0%

Length

2024-03-13T21:28:45.065864image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-13T21:28:45.312307image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
20210814 390
78.0%
20210821 110
 
22.0%

SST
Real number (ℝ)

Distinct12
Distinct (%)2.4%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean24.848
Minimum21
Maximum35
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size4.5 KiB
2024-03-13T21:28:45.496894image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum21
5-th percentile23
Q124
median25
Q325
95-th percentile27
Maximum35
Range14
Interquartile range (IQR)1

Descriptive statistics

Standard deviation2.1452506
Coefficient of variation (CV)0.086334941
Kurtosis10.35874
Mean24.848
Median Absolute Deviation (MAD)1
Skewness2.6769113
Sum12424
Variance4.6021002
MonotonicityNot monotonic
2024-03-13T21:28:45.721373image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=12)
ValueCountFrequency (%)
25 153
30.6%
24 133
26.6%
23 79
15.8%
26 50
 
10.0%
27 42
 
8.4%
22 21
 
4.2%
35 11
 
2.2%
21 3
 
0.6%
31 3
 
0.6%
28 2
 
0.4%
Other values (2) 3
 
0.6%
ValueCountFrequency (%)
21 3
 
0.6%
22 21
 
4.2%
23 79
15.8%
24 133
26.6%
25 153
30.6%
26 50
 
10.0%
27 42
 
8.4%
28 2
 
0.4%
29 1
 
0.2%
31 3
 
0.6%
ValueCountFrequency (%)
35 11
 
2.2%
34 2
 
0.4%
31 3
 
0.6%
29 1
 
0.2%
28 2
 
0.4%
27 42
 
8.4%
26 50
 
10.0%
25 153
30.6%
24 133
26.6%
23 79
15.8%

Interactions

2024-03-13T21:28:38.531935image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T21:28:36.631446image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T21:28:37.793292image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T21:28:38.713251image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T21:28:37.372920image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T21:28:38.030478image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T21:28:38.941946image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T21:28:37.574574image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T21:28:38.301762image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-03-13T21:28:45.913890image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
FSASSN_SZN_CTSHMTBT_NETBT_SZN_CTSHSQDJG_CTSHFSLSPS_CTSHNCHVY_FSATN_CTSHLGZ_NETBT_CTSHFSGN_CTSHCTOF_LOCTOF_LACTOF_YMDSST
FSASSN_SZN_CTSH1.0000.1670.3990.2780.6450.6450.8410.7390.7150.2060.196
MTBT_NETBT_SZN_CTSH0.1671.0000.7190.2610.0250.0000.0000.8020.6750.4230.458
SQDJG_CTSH0.3990.7191.0000.4940.1480.1390.1080.8470.7570.3400.406
FSLSPS_CTSH0.2780.2610.4941.0000.0000.4600.4590.4680.5680.2390.230
NCHVY_FSATN_CTSH0.6450.0250.1480.0001.0000.8930.8930.5260.3270.1320.000
LGZ_NETBT_CTSH0.6450.0000.1390.4600.8931.0000.9820.5050.4290.3190.454
FSGN_CTSH0.8410.0000.1080.4590.8930.9821.0000.4470.3770.3080.233
CTOF_LO0.7390.8020.8470.4680.5260.5050.4471.0000.8700.8870.618
CTOF_LA0.7150.6750.7570.5680.3270.4290.3770.8701.0000.9870.484
CTOF_YMD0.2060.4230.3400.2390.1320.3190.3080.8870.9871.0000.303
SST0.1960.4580.4060.2300.0000.4540.2330.6180.4840.3031.000
2024-03-13T21:28:46.197529image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
NCHVY_FSATN_CTSHCTOF_YMDFSASSN_SZN_CTSHFSGN_CTSHMTBT_NETBT_SZN_CTSHSQDJG_CTSHLGZ_NETBT_CTSHFSLSPS_CTSH
NCHVY_FSATN_CTSH1.0000.0870.5740.5740.0240.1400.5740.000
CTOF_YMD0.0871.0000.2510.2050.6610.5430.2120.390
FSASSN_SZN_CTSH0.5740.2511.0000.8150.1270.3290.5740.218
FSGN_CTSH0.5740.2050.8151.0000.0000.1020.8150.454
MTBT_NETBT_SZN_CTSH0.0240.6610.1270.0001.0000.3750.0000.085
SQDJG_CTSH0.1400.5430.3290.1020.3751.0000.1310.199
LGZ_NETBT_CTSH0.5740.2120.5740.8150.0000.1311.0000.455
FSLSPS_CTSH0.0000.3900.2180.4540.0850.1990.4551.000
2024-03-13T21:28:46.457037image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
CTOF_LOCTOF_LASSTFSASSN_SZN_CTSHMTBT_NETBT_SZN_CTSHSQDJG_CTSHFSLSPS_CTSHNCHVY_FSATN_CTSHLGZ_NETBT_CTSHFSGN_CTSHCTOF_YMD
CTOF_LO1.0000.742-0.4690.3950.6890.7580.3160.3400.3240.2810.716
CTOF_LA0.7421.000-0.2670.3750.5240.6260.4090.2000.2680.2320.893
SST-0.469-0.2671.0000.1180.3180.2790.1420.0000.1860.1060.226
FSASSN_SZN_CTSH0.3950.3750.1181.0000.1270.3290.2180.5740.5740.8150.251
MTBT_NETBT_SZN_CTSH0.6890.5240.3180.1271.0000.3750.0850.0240.0000.0000.661
SQDJG_CTSH0.7580.6260.2790.3290.3751.0000.1990.1400.1310.1020.543
FSLSPS_CTSH0.3160.4090.1420.2180.0850.1991.0000.0000.4550.4540.390
NCHVY_FSATN_CTSH0.3400.2000.0000.5740.0240.1400.0001.0000.5740.5740.087
LGZ_NETBT_CTSH0.3240.2680.1860.5740.0000.1310.4550.5741.0000.8150.212
FSGN_CTSH0.2810.2320.1060.8150.0000.1020.4540.5740.8151.0000.205
CTOF_YMD0.7160.8930.2260.2510.6610.5430.3900.0870.2120.2051.000

Missing values

2024-03-13T21:28:39.243473image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-03-13T21:28:39.606411image/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_CTSHSQDJG_CTSHFSLSPS_CTSHNCHVY_FSATN_CTSHLGZ_NETBT_CTSHFSGN_CTSHCTOF_LOCTOF_LACTOF_YMDSST
0010000000127.7533.9172021081425
1010000000127.91733.9172021081425
2200000000125.58334.0832021081425
3200000000125.7534.0832021081426
4200000000125.91734.0832021081425
5100000000127.58334.0832021081425
6100000000127.7534.0832021081424
7100000000127.91734.0832021081425
8200000000125.58334.252021081426
9200000000125.7534.252021081426
FSASSN_SZN_CTSHMTBT_NETBT_SZN_CTSHSQDJG_CTSHFSLSPS_CTSHNCHVY_FSATN_CTSHLGZ_NETBT_CTSHFSGN_CTSHCTOF_LOCTOF_LACTOF_YMDSST
49020010000000127.91734.252021082125
491000100000128.58334.252021082125
492000100000128.7534.252021082125
49320000100000125.58334.4172021082124
49420000100000125.7534.4172021082122
49520000100000125.91734.4172021082124
49620010000000127.58334.4172021082124
49720010000000127.7534.4172021082124
49820010000000127.91734.4172021082125
499000100000128.58334.4172021082124