Overview

Dataset statistics

Number of variables13
Number of observations48
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory5.6 KiB
Average record size in memory118.7 B

Variable types

Text1
Numeric12

Dataset

Description장해등급(1등급 ~ 11등급 이하)별 장해연금지급액 현황(연령구분)에 대한 데이터입니다. 38세 미만부터 시작됩니다.
Author공공데이터포털
URLhttps://www.data.go.kr/data/15054034/fileData.do

Alerts

is highly overall correlated with 1등급 and 10 other fieldsHigh correlation
1등급 is highly overall correlated with and 7 other fieldsHigh correlation
2등급 is highly overall correlated with and 10 other fieldsHigh correlation
3등급 is highly overall correlated with and 10 other fieldsHigh correlation
4등급 is highly overall correlated with and 9 other fieldsHigh correlation
5등급 is highly overall correlated with and 9 other fieldsHigh correlation
6등급 is highly overall correlated with and 9 other fieldsHigh correlation
7등급 is highly overall correlated with and 10 other fieldsHigh correlation
8등급 is highly overall correlated with and 10 other fieldsHigh correlation
9등급 is highly overall correlated with and 10 other fieldsHigh correlation
10등급 is highly overall correlated with and 10 other fieldsHigh correlation
11등급이하 is highly overall correlated with and 10 other fieldsHigh correlation
구분 has unique valuesUnique
has 3 (6.2%) zerosZeros
1등급 has 8 (16.7%) zerosZeros
2등급 has 18 (37.5%) zerosZeros
3등급 has 11 (22.9%) zerosZeros
4등급 has 19 (39.6%) zerosZeros
5등급 has 9 (18.8%) zerosZeros
6등급 has 16 (33.3%) zerosZeros
7등급 has 14 (29.2%) zerosZeros
8등급 has 11 (22.9%) zerosZeros
9등급 has 14 (29.2%) zerosZeros
10등급 has 14 (29.2%) zerosZeros
11등급이하 has 7 (14.6%) zerosZeros

Reproduction

Analysis started2024-04-21 12:08:10.302630
Analysis finished2024-04-21 12:08:37.976260
Duration27.67 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

구분
Text

UNIQUE 

Distinct48
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size512.0 B
2024-04-21T21:08:38.639839image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length5
Median length3
Mean length3.0833333
Min length3

Characters and Unicode

Total characters148
Distinct characters15
Distinct categories2 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique48 ?
Unique (%)100.0%

Sample

1st row38세미만
2nd row38세
3rd row39세
4th row40세
5th row41세
ValueCountFrequency (%)
38세미만 1
 
2.1%
38세 1
 
2.1%
72세 1
 
2.1%
63세 1
 
2.1%
64세 1
 
2.1%
65세 1
 
2.1%
66세 1
 
2.1%
67세 1
 
2.1%
68세 1
 
2.1%
69세 1
 
2.1%
Other values (38) 38
79.2%
2024-04-21T21:08:39.638274image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
48
32.4%
4 15
 
10.1%
5 14
 
9.5%
6 14
 
9.5%
7 14
 
9.5%
8 11
 
7.4%
3 8
 
5.4%
9 5
 
3.4%
0 5
 
3.4%
1 5
 
3.4%
Other values (5) 9
 
6.1%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 96
64.9%
Other Letter 52
35.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
4 15
15.6%
5 14
14.6%
6 14
14.6%
7 14
14.6%
8 11
11.5%
3 8
8.3%
9 5
 
5.2%
0 5
 
5.2%
1 5
 
5.2%
2 5
 
5.2%
Other Letter
ValueCountFrequency (%)
48
92.3%
1
 
1.9%
1
 
1.9%
1
 
1.9%
1
 
1.9%

Most occurring scripts

ValueCountFrequency (%)
Common 96
64.9%
Hangul 52
35.1%

Most frequent character per script

Common
ValueCountFrequency (%)
4 15
15.6%
5 14
14.6%
6 14
14.6%
7 14
14.6%
8 11
11.5%
3 8
8.3%
9 5
 
5.2%
0 5
 
5.2%
1 5
 
5.2%
2 5
 
5.2%
Hangul
ValueCountFrequency (%)
48
92.3%
1
 
1.9%
1
 
1.9%
1
 
1.9%
1
 
1.9%

Most occurring blocks

ValueCountFrequency (%)
ASCII 96
64.9%
Hangul 52
35.1%

Most frequent character per block

Hangul
ValueCountFrequency (%)
48
92.3%
1
 
1.9%
1
 
1.9%
1
 
1.9%
1
 
1.9%
ASCII
ValueCountFrequency (%)
4 15
15.6%
5 14
14.6%
6 14
14.6%
7 14
14.6%
8 11
11.5%
3 8
8.3%
9 5
 
5.2%
0 5
 
5.2%
1 5
 
5.2%
2 5
 
5.2%


Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct46
Distinct (%)95.8%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1134.375
Minimum0
Maximum3258
Zeros3
Zeros (%)6.2%
Negative0
Negative (%)0.0%
Memory size560.0 B
2024-04-21T21:08:39.869223image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile1.05
Q1108
median679.5
Q31933.5
95-th percentile3122.6
Maximum3258
Range3258
Interquartile range (IQR)1825.5

Descriptive statistics

Standard deviation1090.0923
Coefficient of variation (CV)0.96096294
Kurtosis-0.9657573
Mean1134.375
Median Absolute Deviation (MAD)659
Skewness0.65713764
Sum54450
Variance1188301.3
MonotonicityNot monotonic
2024-04-21T21:08:40.108555image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=46)
ValueCountFrequency (%)
0 3
 
6.2%
3201 1
 
2.1%
2977 1
 
2.1%
3238 1
 
2.1%
3258 1
 
2.1%
2900 1
 
2.1%
2400 1
 
2.1%
1780 1
 
2.1%
2618 1
 
2.1%
1767 1
 
2.1%
Other values (36) 36
75.0%
ValueCountFrequency (%)
0 3
6.2%
3 1
 
2.1%
9 1
 
2.1%
16 1
 
2.1%
25 1
 
2.1%
39 1
 
2.1%
43 1
 
2.1%
46 1
 
2.1%
51 1
 
2.1%
105 1
 
2.1%
ValueCountFrequency (%)
3258 1
2.1%
3238 1
2.1%
3201 1
2.1%
2977 1
2.1%
2900 1
2.1%
2898 1
2.1%
2806 1
2.1%
2618 1
2.1%
2400 1
2.1%
2322 1
2.1%

1등급
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct37
Distinct (%)77.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean60.145833
Minimum0
Maximum188
Zeros8
Zeros (%)16.7%
Negative0
Negative (%)0.0%
Memory size560.0 B
2024-04-21T21:08:40.495827image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q113.75
median40
Q3111.25
95-th percentile167.05
Maximum188
Range188
Interquartile range (IQR)97.5

Descriptive statistics

Standard deviation56.847684
Coefficient of variation (CV)0.94516412
Kurtosis-0.75246547
Mean60.145833
Median Absolute Deviation (MAD)40
Skewness0.74555821
Sum2887
Variance3231.6591
MonotonicityNot monotonic
2024-04-21T21:08:40.907923image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=37)
ValueCountFrequency (%)
0 8
 
16.7%
27 3
 
6.2%
43 2
 
4.2%
116 2
 
4.2%
14 1
 
2.1%
44 1
 
2.1%
95 1
 
2.1%
20 1
 
2.1%
173 1
 
2.1%
32 1
 
2.1%
Other values (27) 27
56.2%
ValueCountFrequency (%)
0 8
16.7%
6 1
 
2.1%
8 1
 
2.1%
11 1
 
2.1%
13 1
 
2.1%
14 1
 
2.1%
17 1
 
2.1%
20 1
 
2.1%
23 1
 
2.1%
25 1
 
2.1%
ValueCountFrequency (%)
188 1
2.1%
176 1
2.1%
173 1
2.1%
156 1
2.1%
148 1
2.1%
138 1
2.1%
137 1
2.1%
134 1
2.1%
116 2
4.2%
114 1
2.1%

2등급
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct29
Distinct (%)60.4%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean36.916667
Minimum0
Maximum144
Zeros18
Zeros (%)37.5%
Negative0
Negative (%)0.0%
Memory size560.0 B
2024-04-21T21:08:41.285089image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median27
Q368.5
95-th percentile100.2
Maximum144
Range144
Interquartile range (IQR)68.5

Descriptive statistics

Standard deviation40.863985
Coefficient of variation (CV)1.1069251
Kurtosis-0.046242363
Mean36.916667
Median Absolute Deviation (MAD)27
Skewness0.89209749
Sum1772
Variance1669.8652
MonotonicityNot monotonic
2024-04-21T21:08:41.692096image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=29)
ValueCountFrequency (%)
0 18
37.5%
7 2
 
4.2%
36 2
 
4.2%
88 1
 
2.1%
32 1
 
2.1%
29 1
 
2.1%
60 1
 
2.1%
81 1
 
2.1%
57 1
 
2.1%
62 1
 
2.1%
Other values (19) 19
39.6%
ValueCountFrequency (%)
0 18
37.5%
5 1
 
2.1%
7 2
 
4.2%
14 1
 
2.1%
19 1
 
2.1%
26 1
 
2.1%
28 1
 
2.1%
29 1
 
2.1%
32 1
 
2.1%
36 2
 
4.2%
ValueCountFrequency (%)
144 1
2.1%
143 1
2.1%
103 1
2.1%
95 1
2.1%
91 1
2.1%
88 1
2.1%
87 1
2.1%
86 1
2.1%
81 1
2.1%
79 1
2.1%

3등급
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct35
Distinct (%)72.9%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean58.020833
Minimum0
Maximum212
Zeros11
Zeros (%)22.9%
Negative0
Negative (%)0.0%
Memory size560.0 B
2024-04-21T21:08:42.094778image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q14
median44.5
Q397.75
95-th percentile152.2
Maximum212
Range212
Interquartile range (IQR)93.75

Descriptive statistics

Standard deviation56.914078
Coefficient of variation (CV)0.98092487
Kurtosis-0.48021978
Mean58.020833
Median Absolute Deviation (MAD)44.5
Skewness0.68545908
Sum2785
Variance3239.2123
MonotonicityNot monotonic
2024-04-21T21:08:42.490600image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=35)
ValueCountFrequency (%)
0 11
22.9%
86 2
 
4.2%
147 2
 
4.2%
5 2
 
4.2%
10 1
 
2.1%
141 1
 
2.1%
107 1
 
2.1%
26 1
 
2.1%
7 1
 
2.1%
67 1
 
2.1%
Other values (25) 25
52.1%
ValueCountFrequency (%)
0 11
22.9%
1 1
 
2.1%
5 2
 
4.2%
7 1
 
2.1%
10 1
 
2.1%
13 1
 
2.1%
15 1
 
2.1%
18 1
 
2.1%
23 1
 
2.1%
25 1
 
2.1%
ValueCountFrequency (%)
212 1
2.1%
156 1
2.1%
155 1
2.1%
147 2
4.2%
141 1
2.1%
137 1
2.1%
122 1
2.1%
119 1
2.1%
107 1
2.1%
103 1
2.1%

4등급
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct26
Distinct (%)54.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean47.645833
Minimum0
Maximum178
Zeros19
Zeros (%)39.6%
Negative0
Negative (%)0.0%
Memory size560.0 B
2024-04-21T21:08:42.856401image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median42
Q380.5
95-th percentile126.45
Maximum178
Range178
Interquartile range (IQR)80.5

Descriptive statistics

Standard deviation48.73615
Coefficient of variation (CV)1.0228838
Kurtosis-0.44322236
Mean47.645833
Median Absolute Deviation (MAD)42
Skewness0.68146743
Sum2287
Variance2375.2123
MonotonicityNot monotonic
2024-04-21T21:08:43.252414image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=26)
ValueCountFrequency (%)
0 19
39.6%
50 3
 
6.2%
71 2
 
4.2%
105 2
 
4.2%
178 1
 
2.1%
28 1
 
2.1%
26 1
 
2.1%
113 1
 
2.1%
40 1
 
2.1%
72 1
 
2.1%
Other values (16) 16
33.3%
ValueCountFrequency (%)
0 19
39.6%
26 1
 
2.1%
28 1
 
2.1%
30 1
 
2.1%
33 1
 
2.1%
40 1
 
2.1%
44 1
 
2.1%
50 3
 
6.2%
58 1
 
2.1%
60 1
 
2.1%
ValueCountFrequency (%)
178 1
2.1%
147 1
2.1%
131 1
2.1%
118 1
2.1%
114 1
2.1%
113 1
2.1%
107 1
2.1%
105 2
4.2%
100 1
2.1%
89 1
2.1%

5등급
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct38
Distinct (%)79.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean104.04167
Minimum0
Maximum321
Zeros9
Zeros (%)18.8%
Negative0
Negative (%)0.0%
Memory size560.0 B
2024-04-21T21:08:43.639915image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q125
median91
Q3144.5
95-th percentile253.6
Maximum321
Range321
Interquartile range (IQR)119.5

Descriptive statistics

Standard deviation90.918237
Coefficient of variation (CV)0.87386372
Kurtosis-0.41040946
Mean104.04167
Median Absolute Deviation (MAD)65
Skewness0.69991771
Sum4994
Variance8266.1259
MonotonicityNot monotonic
2024-04-21T21:08:44.043408image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=38)
ValueCountFrequency (%)
0 9
 
18.8%
26 2
 
4.2%
56 2
 
4.2%
13 1
 
2.1%
230 1
 
2.1%
155 1
 
2.1%
132 1
 
2.1%
125 1
 
2.1%
210 1
 
2.1%
187 1
 
2.1%
Other values (28) 28
58.3%
ValueCountFrequency (%)
0 9
18.8%
13 1
 
2.1%
16 1
 
2.1%
22 1
 
2.1%
26 2
 
4.2%
32 1
 
2.1%
51 1
 
2.1%
56 2
 
4.2%
59 1
 
2.1%
67 1
 
2.1%
ValueCountFrequency (%)
321 1
2.1%
309 1
2.1%
255 1
2.1%
251 1
2.1%
248 1
2.1%
247 1
2.1%
232 1
2.1%
230 1
2.1%
210 1
2.1%
187 1
2.1%

6등급
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct31
Distinct (%)64.6%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean40.354167
Minimum0
Maximum166
Zeros16
Zeros (%)33.3%
Negative0
Negative (%)0.0%
Memory size560.0 B
2024-04-21T21:08:44.419837image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median23.5
Q364.5
95-th percentile134.05
Maximum166
Range166
Interquartile range (IQR)64.5

Descriptive statistics

Standard deviation47.061069
Coefficient of variation (CV)1.166201
Kurtosis0.14404379
Mean40.354167
Median Absolute Deviation (MAD)23.5
Skewness1.1243653
Sum1937
Variance2214.7442
MonotonicityNot monotonic
2024-04-21T21:08:44.815498image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=31)
ValueCountFrequency (%)
0 16
33.3%
109 2
 
4.2%
24 2
 
4.2%
123 1
 
2.1%
87 1
 
2.1%
19 1
 
2.1%
41 1
 
2.1%
17 1
 
2.1%
34 1
 
2.1%
33 1
 
2.1%
Other values (21) 21
43.8%
ValueCountFrequency (%)
0 16
33.3%
7 1
 
2.1%
10 1
 
2.1%
15 1
 
2.1%
16 1
 
2.1%
17 1
 
2.1%
19 1
 
2.1%
22 1
 
2.1%
23 1
 
2.1%
24 2
 
4.2%
ValueCountFrequency (%)
166 1
2.1%
143 1
2.1%
140 1
2.1%
123 1
2.1%
119 1
2.1%
116 1
2.1%
109 2
4.2%
87 1
2.1%
83 1
2.1%
77 1
2.1%

7등급
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct33
Distinct (%)68.8%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean114.66667
Minimum0
Maximum373
Zeros14
Zeros (%)29.2%
Negative0
Negative (%)0.0%
Memory size560.0 B
2024-04-21T21:08:45.195849image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median83
Q3219.25
95-th percentile321.45
Maximum373
Range373
Interquartile range (IQR)219.25

Descriptive statistics

Standard deviation114.73954
Coefficient of variation (CV)1.0006356
Kurtosis-0.84367831
Mean114.66667
Median Absolute Deviation (MAD)83
Skewness0.65022529
Sum5504
Variance13165.163
MonotonicityNot monotonic
2024-04-21T21:08:45.608665image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=33)
ValueCountFrequency (%)
0 14
29.2%
258 2
 
4.2%
101 2
 
4.2%
340 1
 
2.1%
240 1
 
2.1%
116 1
 
2.1%
218 1
 
2.1%
250 1
 
2.1%
223 1
 
2.1%
155 1
 
2.1%
Other values (23) 23
47.9%
ValueCountFrequency (%)
0 14
29.2%
3 1
 
2.1%
9 1
 
2.1%
39 1
 
2.1%
44 1
 
2.1%
48 1
 
2.1%
51 1
 
2.1%
52 1
 
2.1%
54 1
 
2.1%
71 1
 
2.1%
ValueCountFrequency (%)
373 1
2.1%
348 1
2.1%
340 1
2.1%
287 1
2.1%
279 1
2.1%
263 1
2.1%
258 2
4.2%
250 1
2.1%
240 1
2.1%
236 1
2.1%

8등급
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct38
Distinct (%)79.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean203.91667
Minimum0
Maximum804
Zeros11
Zeros (%)22.9%
Negative0
Negative (%)0.0%
Memory size560.0 B
2024-04-21T21:08:46.009441image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q111.75
median90.5
Q3398.75
95-th percentile685.6
Maximum804
Range804
Interquartile range (IQR)387

Descriptive statistics

Standard deviation237.05631
Coefficient of variation (CV)1.1625156
Kurtosis-0.073958082
Mean203.91667
Median Absolute Deviation (MAD)90.5
Skewness1.0553709
Sum9788
Variance56195.695
MonotonicityNot monotonic
2024-04-21T21:08:46.445839image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=38)
ValueCountFrequency (%)
0 11
 
22.9%
180 1
 
2.1%
433 1
 
2.1%
432 1
 
2.1%
439 1
 
2.1%
293 1
 
2.1%
397 1
 
2.1%
500 1
 
2.1%
404 1
 
2.1%
132 1
 
2.1%
Other values (28) 28
58.3%
ValueCountFrequency (%)
0 11
22.9%
5 1
 
2.1%
14 1
 
2.1%
15 1
 
2.1%
17 1
 
2.1%
18 1
 
2.1%
21 1
 
2.1%
27 1
 
2.1%
64 1
 
2.1%
66 1
 
2.1%
ValueCountFrequency (%)
804 1
2.1%
743 1
2.1%
694 1
2.1%
670 1
2.1%
582 1
2.1%
527 1
2.1%
513 1
2.1%
500 1
2.1%
439 1
2.1%
433 1
2.1%

9등급
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct35
Distinct (%)72.9%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean100.14583
Minimum0
Maximum428
Zeros14
Zeros (%)29.2%
Negative0
Negative (%)0.0%
Memory size560.0 B
2024-04-21T21:08:46.855210image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median59
Q3155.25
95-th percentile306.55
Maximum428
Range428
Interquartile range (IQR)155.25

Descriptive statistics

Standard deviation110.03694
Coefficient of variation (CV)1.098767
Kurtosis0.45150757
Mean100.14583
Median Absolute Deviation (MAD)59
Skewness1.0629345
Sum4807
Variance12108.127
MonotonicityNot monotonic
2024-04-21T21:08:47.463809image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=35)
ValueCountFrequency (%)
0 14
29.2%
5 1
 
2.1%
337 1
 
2.1%
190 1
 
2.1%
154 1
 
2.1%
159 1
 
2.1%
216 1
 
2.1%
153 1
 
2.1%
130 1
 
2.1%
111 1
 
2.1%
Other values (25) 25
52.1%
ValueCountFrequency (%)
0 14
29.2%
5 1
 
2.1%
6 1
 
2.1%
9 1
 
2.1%
30 1
 
2.1%
36 1
 
2.1%
37 1
 
2.1%
40 1
 
2.1%
44 1
 
2.1%
46 1
 
2.1%
ValueCountFrequency (%)
428 1
2.1%
337 1
2.1%
316 1
2.1%
289 1
2.1%
268 1
2.1%
258 1
2.1%
226 1
2.1%
217 1
2.1%
216 1
2.1%
209 1
2.1%

10등급
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct31
Distinct (%)64.6%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean101.66667
Minimum0
Maximum473
Zeros14
Zeros (%)29.2%
Negative0
Negative (%)0.0%
Memory size560.0 B
2024-04-21T21:08:47.834956image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median37.5
Q3192.25
95-th percentile319.25
Maximum473
Range473
Interquartile range (IQR)192.25

Descriptive statistics

Standard deviation120.99505
Coefficient of variation (CV)1.1901152
Kurtosis0.52462461
Mean101.66667
Median Absolute Deviation (MAD)37.5
Skewness1.1398242
Sum4880
Variance14639.801
MonotonicityNot monotonic
2024-04-21T21:08:48.222798image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=31)
ValueCountFrequency (%)
0 14
29.2%
30 3
 
6.2%
18 2
 
4.2%
73 2
 
4.2%
216 1
 
2.1%
154 1
 
2.1%
115 1
 
2.1%
217 1
 
2.1%
164 1
 
2.1%
139 1
 
2.1%
Other values (21) 21
43.8%
ValueCountFrequency (%)
0 14
29.2%
5 1
 
2.1%
6 1
 
2.1%
13 1
 
2.1%
18 2
 
4.2%
25 1
 
2.1%
27 1
 
2.1%
30 3
 
6.2%
45 1
 
2.1%
56 1
 
2.1%
ValueCountFrequency (%)
473 1
2.1%
356 1
2.1%
328 1
2.1%
303 1
2.1%
283 1
2.1%
265 1
2.1%
256 1
2.1%
239 1
2.1%
233 1
2.1%
217 1
2.1%

11등급이하
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct42
Distinct (%)87.5%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean266.85417
Minimum0
Maximum948
Zeros7
Zeros (%)14.6%
Negative0
Negative (%)0.0%
Memory size560.0 B
2024-04-21T21:08:48.607689image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q117.75
median145
Q3470.25
95-th percentile837.9
Maximum948
Range948
Interquartile range (IQR)452.5

Descriptive statistics

Standard deviation289.01086
Coefficient of variation (CV)1.0830292
Kurtosis-0.36271419
Mean266.85417
Median Absolute Deviation (MAD)145
Skewness0.93695387
Sum12809
Variance83527.276
MonotonicityNot monotonic
2024-04-21T21:08:49.017681image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=42)
ValueCountFrequency (%)
0 7
 
14.6%
854 1
 
2.1%
686 1
 
2.1%
808 1
 
2.1%
536 1
 
2.1%
468 1
 
2.1%
619 1
 
2.1%
340 1
 
2.1%
477 1
 
2.1%
382 1
 
2.1%
Other values (32) 32
66.7%
ValueCountFrequency (%)
0 7
14.6%
5 1
 
2.1%
9 1
 
2.1%
12 1
 
2.1%
15 1
 
2.1%
17 1
 
2.1%
18 1
 
2.1%
21 1
 
2.1%
38 1
 
2.1%
40 1
 
2.1%
ValueCountFrequency (%)
948 1
2.1%
882 1
2.1%
854 1
2.1%
808 1
2.1%
798 1
2.1%
699 1
2.1%
686 1
2.1%
619 1
2.1%
536 1
2.1%
534 1
2.1%

Interactions

2024-04-21T21:08:35.390292image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T21:08:10.963981image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T21:08:13.910241image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T21:08:16.887981image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T21:08:18.921952image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T21:08:20.773137image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T21:08:22.564276image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T21:08:25.427286image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T21:08:28.286140image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T21:08:30.266153image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T21:08:32.091320image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T21:08:33.739301image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T21:08:35.529063image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T21:08:11.208144image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T21:08:14.158593image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T21:08:17.139365image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T21:08:19.059099image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T21:08:20.921872image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T21:08:22.760548image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T21:08:25.670309image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T21:08:28.432274image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T21:08:30.420391image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T21:08:32.230541image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T21:08:33.876380image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T21:08:35.674648image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T21:08:11.459349image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T21:08:14.413459image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T21:08:17.399643image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T21:08:19.203118image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T21:08:21.074080image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T21:08:23.009855image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T21:08:25.920099image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T21:08:28.586997image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T21:08:30.581361image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T21:08:32.374792image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T21:08:34.022296image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T21:08:35.819279image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T21:08:11.715159image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T21:08:14.667651image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T21:08:17.606556image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T21:08:19.345359image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T21:08:21.229368image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T21:08:23.260718image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T21:08:26.169819image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T21:08:28.740685image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T21:08:30.739601image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T21:08:32.520080image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T21:08:34.166453image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T21:08:35.946570image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T21:08:11.949733image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T21:08:14.904958image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T21:08:17.741220image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T21:08:19.470963image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T21:08:21.367138image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T21:08:23.489997image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T21:08:26.401265image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T21:08:29.088222image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T21:08:30.881790image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T21:08:32.644112image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T21:08:34.292847image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T21:08:36.089902image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T21:08:12.201878image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T21:08:15.158294image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T21:08:17.897221image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T21:08:19.823669image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T21:08:21.531426image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T21:08:23.741395image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T21:08:26.648871image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T21:08:29.240119image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T21:08:31.039420image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T21:08:32.789452image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T21:08:34.437050image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T21:08:36.443803image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T21:08:12.449700image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T21:08:15.410653image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T21:08:18.045184image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T21:08:19.962490image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T21:08:21.689559image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T21:08:23.982743image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T21:08:26.893826image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T21:08:29.390042image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T21:08:31.193409image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T21:08:32.927262image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T21:08:34.578427image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T21:08:36.581486image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T21:08:12.694836image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T21:08:15.660820image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T21:08:18.196210image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T21:08:20.098422image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T21:08:21.841759image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T21:08:24.227824image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T21:08:27.134620image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T21:08:29.540471image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T21:08:31.345535image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T21:08:33.066681image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T21:08:34.716453image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T21:08:36.727836image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T21:08:12.949389image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T21:08:15.915885image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T21:08:18.353749image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T21:08:20.242672image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T21:08:21.996173image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T21:08:24.475670image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T21:08:27.385898image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T21:08:29.691909image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T21:08:31.506493image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T21:08:33.210131image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T21:08:34.864148image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T21:08:36.877135image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T21:08:13.207695image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T21:08:16.179557image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T21:08:18.513032image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T21:08:20.392330image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T21:08:22.158501image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T21:08:24.733085image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T21:08:27.641226image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T21:08:29.856071image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T21:08:31.671986image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T21:08:33.363039image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T21:08:35.012295image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T21:08:37.004800image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T21:08:13.442520image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T21:08:16.415133image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T21:08:18.650924image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T21:08:20.520123image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T21:08:22.292407image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T21:08:24.965000image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T21:08:27.872640image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T21:08:29.991478image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T21:08:31.810818image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T21:08:33.487157image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T21:08:35.138920image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T21:08:37.130827image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T21:08:13.675092image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T21:08:16.652770image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T21:08:18.785721image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T21:08:20.645100image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T21:08:22.429984image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T21:08:25.195244image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T21:08:28.102515image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T21:08:30.130430image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T21:08:31.952767image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T21:08:33.614101image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T21:08:35.262784image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-04-21T21:08:49.290264image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
구분1등급2등급3등급4등급5등급6등급7등급8등급9등급10등급11등급이하
구분1.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.000
1.0001.0000.6610.6640.6920.9200.8190.8540.7760.9460.8080.7260.939
1등급1.0000.6611.0000.5310.5070.7850.4880.5580.3210.6450.4700.1590.626
2등급1.0000.6640.5311.0000.7970.6630.7230.7210.7760.8000.8460.8350.808
3등급1.0000.6920.5070.7971.0000.6930.7840.6030.8510.7180.8610.9230.686
4등급1.0000.9200.7850.6630.6931.0000.8400.6850.7050.9020.6630.7270.809
5등급1.0000.8190.4880.7230.7840.8401.0000.6690.8900.7820.7600.8930.619
6등급1.0000.8540.5580.7210.6030.6850.6691.0000.7560.8790.7280.7800.885
7등급1.0000.7760.3210.7760.8510.7050.8900.7561.0000.7220.8840.8970.799
8등급1.0000.9460.6450.8000.7180.9020.7820.8790.7221.0000.8140.8020.914
9등급1.0000.8080.4700.8460.8610.6630.7600.7280.8840.8141.0000.8900.855
10등급1.0000.7260.1590.8350.9230.7270.8930.7800.8970.8020.8901.0000.781
11등급이하1.0000.9390.6260.8080.6860.8090.6190.8850.7990.9140.8550.7811.000
2024-04-21T21:08:49.632561image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
1등급2등급3등급4등급5등급6등급7등급8등급9등급10등급11등급이하
1.0000.6150.7770.8890.8530.8880.8090.9280.9700.9610.9620.982
1등급0.6151.0000.5310.6700.4100.4770.4440.5080.5860.5570.5290.584
2등급0.7770.5311.0000.6790.6060.6350.6760.7330.7860.7470.7380.715
3등급0.8890.6700.6791.0000.7270.7860.6940.8200.8820.8640.8370.877
4등급0.8530.4100.6060.7271.0000.7960.7080.8040.8290.8690.8370.855
5등급0.8880.4770.6350.7860.7961.0000.7370.8360.8330.8480.8550.872
6등급0.8090.4440.6760.6940.7080.7371.0000.7960.8090.8000.8240.796
7등급0.9280.5080.7330.8200.8040.8360.7961.0000.8990.9320.9170.908
8등급0.9700.5860.7860.8820.8290.8330.8090.8991.0000.9360.9450.953
9등급0.9610.5570.7470.8640.8690.8480.8000.9320.9361.0000.9390.956
10등급0.9620.5290.7380.8370.8370.8550.8240.9170.9450.9391.0000.958
11등급이하0.9820.5840.7150.8770.8550.8720.7960.9080.9530.9560.9581.000

Missing values

2024-04-21T21:08:37.323995image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-04-21T21:08:37.768498image/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

구분1등급2등급3등급4등급5등급6등급7등급8등급9등급10등급11등급이하
038세미만3914000130000012
138세000000000000
239세000000000000
340세300000030000
441세43430000000000
542세25250000000000
643세900000000009
744세000000000000
845세16000016000000
946세463100000000015
구분1등급2등급3등급4등급5등급6등급7등급8등급9등급10등급11등급이하
3875세192827571371002323425840415373453
3976세17443881160230123340180130216345
4077세1019660657910033101132111121211
4178세12564306772164281559497139397
4279세71417297409401081259013191
4380세831130511312923488410673237
4481세58949026261311052279927142
4582세5793932860672512690401856
4683세5536308628512444665225114
4784세이상13831073610750117140163245151107160