Overview

Dataset statistics

Number of variables10
Number of observations100
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory8.7 KiB
Average record size in memory89.3 B

Variable types

Categorical3
Numeric7

Alerts

reprt_year_cn is highly overall correlated with star_nm and 1 other fieldsHigh correlation
examin_country_nm is highly overall correlated with reprt_year_cnHigh correlation
male_rate is highly overall correlated with female_rate and 4 other fieldsHigh correlation
female_rate is highly overall correlated with male_rate and 3 other fieldsHigh correlation
all_n10s_rate is highly overall correlated with female_rateHigh correlation
all_n20s_rate is highly overall correlated with male_rate and 2 other fieldsHigh correlation
all_n30s_rate is highly overall correlated with male_rate and 3 other fieldsHigh correlation
all_n40s_rate is highly overall correlated with male_rateHigh correlation
all_n50s_rate is highly overall correlated with male_rate and 1 other fieldsHigh correlation
star_nm is highly overall correlated with reprt_year_cnHigh correlation
reprt_year_cn is highly imbalanced (80.6%)Imbalance
male_rate has 4 (4.0%) zerosZeros
female_rate has 4 (4.0%) zerosZeros
all_n10s_rate has 16 (16.0%) zerosZeros
all_n20s_rate has 12 (12.0%) zerosZeros
all_n30s_rate has 16 (16.0%) zerosZeros
all_n40s_rate has 26 (26.0%) zerosZeros
all_n50s_rate has 51 (51.0%) zerosZeros

Reproduction

Analysis started2023-12-10 10:02:24.433128
Analysis finished2023-12-10 10:02:33.286316
Duration8.85 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

star_nm
Categorical

HIGH CORRELATION 

Distinct39
Distinct (%)39.0%
Missing0
Missing (%)0.0%
Memory size932.0 B
이민호
11 
박신혜
9 
송혜교
8 
공유
8 
이종석
7 
Other values (34)
57 

Length

Max length6
Median length3
Mean length2.78
Min length1

Unique

Unique23 ?
Unique (%)23.0%

Sample

1st row이민호
2nd row지드래곤
3rd row송혜교
4th row송중기
5th row김희선

Common Values

ValueCountFrequency (%)
이민호 11
 
11.0%
박신혜 9
 
9.0%
송혜교 8
 
8.0%
공유 8
 
8.0%
이종석 7
 
7.0%
송중기 6
 
6.0%
수지 5
 
5.0%
비 3
 
3.0%
윤아 3
 
3.0%
이병헌 3
 
3.0%
Other values (29) 37
37.0%

Length

2023-12-10T19:02:33.565806image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
이민호 11
 
11.0%
박신혜 9
 
9.0%
송혜교 8
 
8.0%
공유 8
 
8.0%
이종석 7
 
7.0%
송중기 6
 
6.0%
수지 5
 
5.0%
비 3
 
3.0%
윤아 3
 
3.0%
이병헌 3
 
3.0%
Other values (29) 37
37.0%

male_rate
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct27
Distinct (%)27.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2.928
Minimum0
Maximum26.4
Zeros4
Zeros (%)4.0%
Negative0
Negative (%)0.0%
Memory size1.0 KiB
2023-12-10T19:02:33.836202image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0.4
Q10.8
median2
Q34
95-th percentile6.94
Maximum26.4
Range26.4
Interquartile range (IQR)3.2

Descriptive statistics

Standard deviation3.4376137
Coefficient of variation (CV)1.1740484
Kurtosis22.295462
Mean2.928
Median Absolute Deviation (MAD)1.2
Skewness3.9219617
Sum292.8
Variance11.817188
MonotonicityNot monotonic
2023-12-10T19:02:34.125458image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=27)
ValueCountFrequency (%)
0.8 13
13.0%
1.2 8
 
8.0%
1.6 8
 
8.0%
2.8 8
 
8.0%
0.4 7
 
7.0%
2.0 7
 
7.0%
4.4 5
 
5.0%
3.2 4
 
4.0%
5.2 4
 
4.0%
0.0 4
 
4.0%
Other values (17) 32
32.0%
ValueCountFrequency (%)
0.0 4
 
4.0%
0.4 7
7.0%
0.5 2
 
2.0%
0.8 13
13.0%
1.0 3
 
3.0%
1.2 8
8.0%
1.5 1
 
1.0%
1.6 8
8.0%
2.0 7
7.0%
2.3 3
 
3.0%
ValueCountFrequency (%)
26.4 1
 
1.0%
13.6 1
 
1.0%
12.0 1
 
1.0%
10.4 1
 
1.0%
9.6 1
 
1.0%
6.8 1
 
1.0%
6.4 2
2.0%
6.0 1
 
1.0%
5.6 3
3.0%
5.2 4
4.0%

female_rate
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct30
Distinct (%)30.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean3.252
Minimum0
Maximum25.2
Zeros4
Zeros (%)4.0%
Negative0
Negative (%)0.0%
Memory size1.0 KiB
2023-12-10T19:02:34.381864image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0.4
Q11.425
median2.6
Q33.6
95-th percentile8.46
Maximum25.2
Range25.2
Interquartile range (IQR)2.175

Descriptive statistics

Standard deviation3.5417704
Coefficient of variation (CV)1.0891053
Kurtosis15.999564
Mean3.252
Median Absolute Deviation (MAD)1.1
Skewness3.4197188
Sum325.2
Variance12.544137
MonotonicityNot monotonic
2023-12-10T19:02:34.619002image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=30)
ValueCountFrequency (%)
2.8 14
14.0%
1.6 13
13.0%
3.2 9
 
9.0%
1.2 8
 
8.0%
0.8 5
 
5.0%
2.4 5
 
5.0%
0.4 5
 
5.0%
0.0 4
 
4.0%
3.6 4
 
4.0%
2.0 3
 
3.0%
Other values (20) 30
30.0%
ValueCountFrequency (%)
0.0 4
 
4.0%
0.4 5
 
5.0%
0.5 1
 
1.0%
0.8 5
 
5.0%
1.0 2
 
2.0%
1.2 8
8.0%
1.5 3
 
3.0%
1.6 13
13.0%
2.0 3
 
3.0%
2.1 1
 
1.0%
ValueCountFrequency (%)
25.2 1
1.0%
14.8 1
1.0%
14.0 1
1.0%
13.6 1
1.0%
9.6 1
1.0%
8.4 1
1.0%
8.0 1
1.0%
7.6 1
1.0%
7.2 2
2.0%
6.8 1
1.0%

all_n10s_rate
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct20
Distinct (%)20.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2.991
Minimum0
Maximum21.6
Zeros16
Zeros (%)16.0%
Negative0
Negative (%)0.0%
Memory size1.0 KiB
2023-12-10T19:02:34.828352image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10.8
median2.4
Q34
95-th percentile9.6
Maximum21.6
Range21.6
Interquartile range (IQR)3.2

Descriptive statistics

Standard deviation3.2950558
Coefficient of variation (CV)1.1016569
Kurtosis10.28195
Mean2.991
Median Absolute Deviation (MAD)1.6
Skewness2.5975917
Sum299.1
Variance10.857393
MonotonicityNot monotonic
2023-12-10T19:02:35.018285image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=20)
ValueCountFrequency (%)
0.8 18
18.0%
0.0 16
16.0%
2.4 13
13.0%
3.2 11
11.0%
1.6 10
10.0%
4.0 8
8.0%
4.8 4
 
4.0%
6.4 3
 
3.0%
5.6 3
 
3.0%
9.6 2
 
2.0%
Other values (10) 12
12.0%
ValueCountFrequency (%)
0.0 16
16.0%
0.8 18
18.0%
1.0 1
 
1.0%
1.6 10
10.0%
2.4 13
13.0%
3.0 2
 
2.0%
3.2 11
11.0%
3.8 1
 
1.0%
4.0 8
8.0%
4.8 4
 
4.0%
ValueCountFrequency (%)
21.6 1
 
1.0%
12.9 1
 
1.0%
12.0 1
 
1.0%
10.4 1
 
1.0%
9.6 2
2.0%
8.0 2
2.0%
7.2 1
 
1.0%
6.4 3
3.0%
5.6 3
3.0%
5.0 1
 
1.0%

all_n20s_rate
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct20
Distinct (%)20.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean3.376
Minimum0
Maximum33.6
Zeros12
Zeros (%)12.0%
Negative0
Negative (%)0.0%
Memory size1.0 KiB
2023-12-10T19:02:35.225463image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q11
median2.4
Q34.075
95-th percentile7.28
Maximum33.6
Range33.6
Interquartile range (IQR)3.075

Descriptive statistics

Standard deviation4.3995206
Coefficient of variation (CV)1.3031755
Kurtosis24.029344
Mean3.376
Median Absolute Deviation (MAD)1.6
Skewness4.2102582
Sum337.6
Variance19.355782
MonotonicityNot monotonic
2023-12-10T19:02:35.443364image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=20)
ValueCountFrequency (%)
1.6 18
18.0%
2.4 17
17.0%
0.0 12
12.0%
0.8 10
10.0%
4.0 7
 
7.0%
7.2 6
 
6.0%
4.8 6
 
6.0%
5.6 4
 
4.0%
1.0 4
 
4.0%
3.2 4
 
4.0%
Other values (10) 12
12.0%
ValueCountFrequency (%)
0.0 12
12.0%
0.8 10
10.0%
1.0 4
 
4.0%
1.6 18
18.0%
2.0 1
 
1.0%
2.1 2
 
2.0%
2.4 17
17.0%
3.2 4
 
4.0%
4.0 7
 
7.0%
4.3 1
 
1.0%
ValueCountFrequency (%)
33.6 1
 
1.0%
19.2 1
 
1.0%
17.6 1
 
1.0%
11.2 1
 
1.0%
8.8 1
 
1.0%
7.2 6
6.0%
7.1 1
 
1.0%
6.4 2
 
2.0%
5.6 4
4.0%
4.8 6
6.0%

all_n30s_rate
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct20
Distinct (%)20.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean3.147
Minimum0
Maximum24
Zeros16
Zeros (%)16.0%
Negative0
Negative (%)0.0%
Memory size1.0 KiB
2023-12-10T19:02:35.659364image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10.8
median2.2
Q34
95-th percentile9.64
Maximum24
Range24
Interquartile range (IQR)3.2

Descriptive statistics

Standard deviation3.5899539
Coefficient of variation (CV)1.1407543
Kurtosis11.670389
Mean3.147
Median Absolute Deviation (MAD)1.6
Skewness2.7823545
Sum314.7
Variance12.887769
MonotonicityNot monotonic
2023-12-10T19:02:35.875903image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=20)
ValueCountFrequency (%)
0.0 16
16.0%
1.6 16
16.0%
0.8 15
15.0%
4.0 12
12.0%
3.2 8
8.0%
2.4 7
7.0%
5.6 5
 
5.0%
4.8 5
 
5.0%
10.4 2
 
2.0%
8.8 2
 
2.0%
Other values (10) 12
12.0%
ValueCountFrequency (%)
0.0 16
16.0%
0.8 15
15.0%
1.0 1
 
1.0%
1.6 16
16.0%
2.0 2
 
2.0%
2.4 7
7.0%
3.0 1
 
1.0%
3.2 8
8.0%
4.0 12
12.0%
4.3 1
 
1.0%
ValueCountFrequency (%)
24.0 1
 
1.0%
15.2 1
 
1.0%
11.2 1
 
1.0%
10.4 2
 
2.0%
9.6 2
 
2.0%
8.8 2
 
2.0%
8.0 1
 
1.0%
6.4 1
 
1.0%
5.6 5
5.0%
4.8 5
5.0%

all_n40s_rate
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct35
Distinct (%)35.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean3.059
Minimum0
Maximum23.5
Zeros26
Zeros (%)26.0%
Negative0
Negative (%)0.0%
Memory size1.0 KiB
2023-12-10T19:02:36.102244image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median2.05
Q34.3
95-th percentile10.005
Maximum23.5
Range23.5
Interquartile range (IQR)4.3

Descriptive statistics

Standard deviation3.7513929
Coefficient of variation (CV)1.2263461
Kurtosis8.620236
Mean3.059
Median Absolute Deviation (MAD)2.05
Skewness2.4188088
Sum305.9
Variance14.072948
MonotonicityNot monotonic
2023-12-10T19:02:36.320150image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=35)
ValueCountFrequency (%)
0.0 26
26.0%
1.2 7
 
7.0%
1.0 6
 
6.0%
1.1 5
 
5.0%
2.4 5
 
5.0%
4.5 5
 
5.0%
2.0 4
 
4.0%
2.2 4
 
4.0%
4.3 3
 
3.0%
3.7 3
 
3.0%
Other values (25) 32
32.0%
ValueCountFrequency (%)
0.0 26
26.0%
1.0 6
 
6.0%
1.1 5
 
5.0%
1.2 7
 
7.0%
1.5 2
 
2.0%
2.0 4
 
4.0%
2.1 2
 
2.0%
2.2 4
 
4.0%
2.3 1
 
1.0%
2.4 5
 
5.0%
ValueCountFrequency (%)
23.5 1
1.0%
14.1 1
1.0%
12.1 1
1.0%
11.6 1
1.0%
10.1 1
1.0%
10.0 1
1.0%
9.6 1
1.0%
9.0 2
2.0%
8.7 1
1.0%
8.4 1
1.0%

all_n50s_rate
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct28
Distinct (%)28.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2.364
Minimum0
Maximum26.1
Zeros51
Zeros (%)51.0%
Negative0
Negative (%)0.0%
Memory size1.0 KiB
2023-12-10T19:02:36.536001image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q33.3
95-th percentile8.72
Maximum26.1
Range26.1
Interquartile range (IQR)3.3

Descriptive statistics

Standard deviation3.8591494
Coefficient of variation (CV)1.6324659
Kurtosis15.201547
Mean2.364
Median Absolute Deviation (MAD)0
Skewness3.2544551
Sum236.4
Variance14.893034
MonotonicityNot monotonic
2023-12-10T19:02:36.752775image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=28)
ValueCountFrequency (%)
0.0 51
51.0%
2.4 5
 
5.0%
2.5 4
 
4.0%
3.0 4
 
4.0%
2.8 3
 
3.0%
3.4 3
 
3.0%
1.7 3
 
3.0%
1.9 2
 
2.0%
3.3 2
 
2.0%
1.2 2
 
2.0%
Other values (18) 21
21.0%
ValueCountFrequency (%)
0.0 51
51.0%
1.2 2
 
2.0%
1.7 3
 
3.0%
1.9 2
 
2.0%
2.4 5
 
5.0%
2.5 4
 
4.0%
2.8 3
 
3.0%
3.0 4
 
4.0%
3.3 2
 
2.0%
3.4 3
 
3.0%
ValueCountFrequency (%)
26.1 1
1.0%
16.7 1
1.0%
11.1 1
1.0%
10.0 1
1.0%
9.1 1
1.0%
8.7 1
1.0%
8.0 2
2.0%
7.5 1
1.0%
7.1 1
1.0%
6.2 1
1.0%

reprt_year_cn
Categorical

HIGH CORRELATION  IMBALANCE 

Distinct2
Distinct (%)2.0%
Missing0
Missing (%)0.0%
Memory size932.0 B
2019
97 
2021
 
3

Length

Max length4
Median length4
Mean length4
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row2019
2nd row2021
3rd row2019
4th row2019
5th row2019

Common Values

ValueCountFrequency (%)
2019 97
97.0%
2021 3
 
3.0%

Length

2023-12-10T19:02:36.967499image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T19:02:37.136578image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2019 97
97.0%
2021 3
 
3.0%

examin_country_nm
Categorical

HIGH CORRELATION 

Distinct12
Distinct (%)12.0%
Missing0
Missing (%)0.0%
Memory size932.0 B
일본
10 
대만
10 
말레이시아
10 
인도네시아
10 
브라질
10 
Other values (7)
50 

Length

Max length5
Median length2
Mean length2.79
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row중국
2nd row남아공
3rd row중국
4th row중국
5th row중국

Common Values

ValueCountFrequency (%)
일본 10
10.0%
대만 10
10.0%
말레이시아 10
10.0%
인도네시아 10
10.0%
브라질 10
10.0%
인도 9
9.0%
미국 9
9.0%
중국 8
8.0%
태국 8
8.0%
호주 7
7.0%
Other values (2) 9
9.0%

Length

2023-12-10T19:02:37.317477image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
일본 10
10.0%
대만 10
10.0%
말레이시아 10
10.0%
인도네시아 10
10.0%
브라질 10
10.0%
인도 9
9.0%
미국 9
9.0%
중국 8
8.0%
태국 8
8.0%
호주 7
7.0%
Other values (2) 9
9.0%

Interactions

2023-12-10T19:02:31.779355image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:02:25.141634image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:02:26.071238image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:02:26.941097image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:02:28.206504image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:02:29.361186image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:02:30.728842image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:02:31.930722image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:02:25.268340image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:02:26.190245image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:02:27.214924image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:02:28.366396image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:02:29.493986image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:02:30.867942image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:02:32.079552image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:02:25.407924image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:02:26.300260image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:02:27.469207image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:02:28.558248image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:02:29.654609image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:02:31.010467image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:02:32.211932image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:02:25.542300image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:02:26.400156image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:02:27.607462image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:02:28.717256image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:02:29.795218image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:02:31.169497image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:02:32.371486image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:02:25.687323image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:02:26.571093image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:02:27.782576image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:02:28.900277image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:02:29.973245image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:02:31.345835image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:02:32.514849image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:02:25.815409image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:02:26.704978image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:02:27.904609image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:02:29.064457image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:02:30.108981image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:02:31.489227image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:02:32.648988image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:02:25.935442image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:02:26.824540image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:02:28.048109image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:02:29.209711image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:02:30.579734image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:02:31.633793image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-10T19:02:37.478230image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
star_nmmale_ratefemale_rateall_n10s_rateall_n20s_rateall_n30s_rateall_n40s_rateall_n50s_ratereprt_year_cnexamin_country_nm
star_nm1.0000.0000.0000.0000.0000.0000.0000.0001.0000.000
male_rate0.0001.0000.7790.9480.8270.9630.8730.9460.0000.258
female_rate0.0000.7791.0000.8260.9590.7720.7760.7760.0000.584
all_n10s_rate0.0000.9480.8261.0000.7920.8920.7640.9080.0000.150
all_n20s_rate0.0000.8270.9590.7921.0000.7680.7880.7560.0000.489
all_n30s_rate0.0000.9630.7720.8920.7681.0000.7850.9620.0000.120
all_n40s_rate0.0000.8730.7760.7640.7880.7851.0000.7620.2090.000
all_n50s_rate0.0000.9460.7760.9080.7560.9620.7621.0000.0000.000
reprt_year_cn1.0000.0000.0000.0000.0000.0000.2090.0001.0001.000
examin_country_nm0.0000.2580.5840.1500.4890.1200.0000.0001.0001.000
2023-12-10T19:02:37.716792image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
reprt_year_cnexamin_country_nmstar_nm
reprt_year_cn1.0000.9480.789
examin_country_nm0.9481.0000.000
star_nm0.7890.0001.000
2023-12-10T19:02:37.903953image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
male_ratefemale_rateall_n10s_rateall_n20s_rateall_n30s_rateall_n40s_rateall_n50s_ratestar_nmreprt_year_cnexamin_country_nm
male_rate1.0000.5140.4770.6670.7260.6150.6030.0000.0000.120
female_rate0.5141.0000.6140.7080.6040.4930.4030.0000.0000.257
all_n10s_rate0.4770.6141.0000.4730.2710.2130.2320.0000.0000.063
all_n20s_rate0.6670.7080.4731.0000.5020.3730.2510.0000.0000.203
all_n30s_rate0.7260.6040.2710.5021.0000.4260.5630.0000.0000.000
all_n40s_rate0.6150.4930.2130.3730.4261.0000.4620.0000.1800.000
all_n50s_rate0.6030.4030.2320.2510.5630.4621.0000.0000.0000.000
star_nm0.0000.0000.0000.0000.0000.0000.0001.0000.7890.000
reprt_year_cn0.0000.0000.0000.0000.0000.1800.0000.7891.0000.948
examin_country_nm0.1200.2570.0630.2030.0000.0000.0000.0000.9481.000

Missing values

2023-12-10T19:02:32.860824image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-10T19:02:33.128372image/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

star_nmmale_ratefemale_rateall_n10s_rateall_n20s_rateall_n30s_rateall_n40s_rateall_n50s_ratereprt_year_cnexamin_country_nm
0이민호6.89.610.48.84.89.08.02019중국
1지드래곤2.33.20.04.34.33.70.02021남아공
2송혜교6.48.03.27.29.610.04.02019중국
3송중기4.88.49.611.22.44.00.02019중국
4김희선5.24.00.02.410.45.08.02019중국
5이종석1.67.28.07.21.61.00.02019중국
6윤아5.60.44.81.63.22.04.02019중국
7엑소2.32.13.82.10.03.70.02021남아공
8박신혜2.02.80.86.41.61.00.02019중국
9공유2.81.64.01.62.41.00.02019중국
star_nmmale_ratefemale_rateall_n10s_rateall_n20s_rateall_n30s_rateall_n40s_rateall_n50s_ratereprt_year_cnexamin_country_nm
90이병헌0.02.40.02.41.61.20.02019브라질
91배두나1.60.40.81.61.60.00.02019브라질
92공유0.41.21.60.01.60.00.02019브라질
93김태희0.80.80.00.00.03.52.52019브라질
94이민호5.24.46.44.84.03.64.92019프랑스
95이병헌4.00.82.41.63.22.42.42019프랑스
96배두나0.41.62.40.00.81.20.02019프랑스
97도경수1.60.01.60.00.02.40.02019프랑스
98최민식0.41.20.01.61.60.00.02019프랑스
99지창욱0.40.80.80.01.60.00.02019프랑스