Overview

Dataset statistics

Number of variables14
Number of observations30
Missing cells6
Missing cells (%)1.4%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory3.8 KiB
Average record size in memory129.4 B

Variable types

Numeric13
Categorical1

Dataset

Description입원 재원자수 현황에 대한 데이터로 건강보험, 의료급여, 일반으로 구분하여 매월 현황을 데이터로 제공하고 있습니다.
Author질병관리청 국립마산병원
URLhttps://www.data.go.kr/data/3048702/fileData.do

Alerts

1 is highly overall correlated with 2 and 10 other fieldsHigh correlation
2 is highly overall correlated with 1 and 10 other fieldsHigh correlation
3 is highly overall correlated with 1 and 10 other fieldsHigh correlation
4 is highly overall correlated with 1 and 10 other fieldsHigh correlation
5 is highly overall correlated with 1 and 10 other fieldsHigh correlation
6 is highly overall correlated with 1 and 10 other fieldsHigh correlation
7 is highly overall correlated with 1 and 10 other fieldsHigh correlation
8 is highly overall correlated with 1 and 10 other fieldsHigh correlation
9 is highly overall correlated with 1 and 10 other fieldsHigh correlation
10 is highly overall correlated with 1 and 10 other fieldsHigh correlation
11 is highly overall correlated with 1 and 11 other fieldsHigh correlation
12 is highly overall correlated with 1 and 11 other fieldsHigh correlation
내용 is highly overall correlated with 11 and 1 other fieldsHigh correlation
11 has 3 (10.0%) missing valuesMissing
12 has 3 (10.0%) missing valuesMissing
2 has unique valuesUnique
4 has unique valuesUnique
5 has unique valuesUnique
6 has unique valuesUnique
7 has unique valuesUnique
8 has unique valuesUnique
9 has unique valuesUnique
10 has unique valuesUnique
1 has 1 (3.3%) zerosZeros
2 has 1 (3.3%) zerosZeros
3 has 2 (6.7%) zerosZeros
4 has 1 (3.3%) zerosZeros

Reproduction

Analysis started2023-12-12 12:08:33.524777
Analysis finished2023-12-12 12:08:52.471732
Duration18.95 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

구분
Real number (ℝ)

Distinct10
Distinct (%)33.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2018.5
Minimum2014
Maximum2023
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size402.0 B
2023-12-12T21:08:52.556740image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum2014
5-th percentile2014
Q12016
median2018.5
Q32021
95-th percentile2023
Maximum2023
Range9
Interquartile range (IQR)5

Descriptive statistics

Standard deviation2.9213837
Coefficient of variation (CV)0.0014473043
Kurtosis-1.2256534
Mean2018.5
Median Absolute Deviation (MAD)2.5
Skewness0
Sum60555
Variance8.5344828
MonotonicityIncreasing
2023-12-12T21:08:52.713664image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=10)
ValueCountFrequency (%)
2014 3
10.0%
2015 3
10.0%
2016 3
10.0%
2017 3
10.0%
2018 3
10.0%
2019 3
10.0%
2020 3
10.0%
2021 3
10.0%
2022 3
10.0%
2023 3
10.0%
ValueCountFrequency (%)
2014 3
10.0%
2015 3
10.0%
2016 3
10.0%
2017 3
10.0%
2018 3
10.0%
2019 3
10.0%
2020 3
10.0%
2021 3
10.0%
2022 3
10.0%
2023 3
10.0%
ValueCountFrequency (%)
2023 3
10.0%
2022 3
10.0%
2021 3
10.0%
2020 3
10.0%
2019 3
10.0%
2018 3
10.0%
2017 3
10.0%
2016 3
10.0%
2015 3
10.0%
2014 3
10.0%

내용
Categorical

HIGH CORRELATION 

Distinct6
Distinct (%)20.0%
Missing0
Missing (%)0.0%
Memory size372.0 B
건보
9 
급여
9 
일반
9 
건보
1 
급여
1 

Length

Max length4
Median length4
Mean length3.8
Min length2

Unique

Unique3 ?
Unique (%)10.0%

Sample

1st row 건보
2nd row 급여
3rd row 일반
4th row 건보
5th row 급여

Common Values

ValueCountFrequency (%)
건보 9
30.0%
급여 9
30.0%
일반 9
30.0%
건보 1
 
3.3%
급여 1
 
3.3%
일반 1
 
3.3%

Length

2023-12-12T21:08:52.905313image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T21:08:53.074768image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
건보 10
33.3%
급여 10
33.3%
일반 10
33.3%

1
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct29
Distinct (%)96.7%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1100.1333
Minimum0
Maximum4231
Zeros1
Zeros (%)3.3%
Negative0
Negative (%)0.0%
Memory size402.0 B
2023-12-12T21:08:53.236835image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile46.25
Q1283.5
median864
Q31723.75
95-th percentile2806.3
Maximum4231
Range4231
Interquartile range (IQR)1440.25

Descriptive statistics

Standard deviation1034.9219
Coefficient of variation (CV)0.94072404
Kurtosis1.3904363
Mean1100.1333
Median Absolute Deviation (MAD)631.5
Skewness1.1833504
Sum33004
Variance1071063.3
MonotonicityNot monotonic
2023-12-12T21:08:53.416060image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=29)
ValueCountFrequency (%)
376 2
 
6.7%
4231 1
 
3.3%
2028 1
 
3.3%
44 1
 
3.3%
494 1
 
3.3%
940 1
 
3.3%
109 1
 
3.3%
49 1
 
3.3%
1812 1
 
3.3%
0 1
 
3.3%
Other values (19) 19
63.3%
ValueCountFrequency (%)
0 1
3.3%
44 1
3.3%
49 1
3.3%
109 1
3.3%
124 1
3.3%
130 1
3.3%
196 1
3.3%
279 1
3.3%
297 1
3.3%
357 1
3.3%
ValueCountFrequency (%)
4231 1
3.3%
3007 1
3.3%
2561 1
3.3%
2392 1
3.3%
2028 1
3.3%
1924 1
3.3%
1922 1
3.3%
1812 1
3.3%
1459 1
3.3%
1438 1
3.3%

2
Real number (ℝ)

HIGH CORRELATION  UNIQUE  ZEROS 

Distinct30
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean927.03333
Minimum0
Maximum3844
Zeros1
Zeros (%)3.3%
Negative0
Negative (%)0.0%
Memory size402.0 B
2023-12-12T21:08:53.586690image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile3.9
Q1123.75
median550.5
Q31378.5
95-th percentile2507.75
Maximum3844
Range3844
Interquartile range (IQR)1254.75

Descriptive statistics

Standard deviation968.71926
Coefficient of variation (CV)1.044967
Kurtosis1.3366137
Mean927.03333
Median Absolute Deviation (MAD)512
Skewness1.2433842
Sum27811
Variance938417
MonotonicityNot monotonic
2023-12-12T21:08:53.770042image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=30)
ValueCountFrequency (%)
3844 1
 
3.3%
464 1
 
3.3%
112 1
 
3.3%
441 1
 
3.3%
808 1
 
3.3%
109 1
 
3.3%
94 1
 
3.3%
1395 1
 
3.3%
0 1
 
3.3%
5 1
 
3.3%
Other values (20) 20
66.7%
ValueCountFrequency (%)
0 1
3.3%
3 1
3.3%
5 1
3.3%
72 1
3.3%
94 1
3.3%
102 1
3.3%
109 1
3.3%
112 1
3.3%
159 1
3.3%
164 1
3.3%
ValueCountFrequency (%)
3844 1
3.3%
2744 1
3.3%
2219 1
3.3%
2167 1
3.3%
2037 1
3.3%
1899 1
3.3%
1619 1
3.3%
1395 1
3.3%
1329 1
3.3%
1223 1
3.3%

3
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct29
Distinct (%)96.7%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1014.2
Minimum0
Maximum4407
Zeros2
Zeros (%)6.7%
Negative0
Negative (%)0.0%
Memory size402.0 B
2023-12-12T21:08:53.961107image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile3.6
Q1129
median668
Q31557.75
95-th percentile2638.3
Maximum4407
Range4407
Interquartile range (IQR)1428.75

Descriptive statistics

Standard deviation1073.7021
Coefficient of variation (CV)1.058669
Kurtosis1.8900184
Mean1014.2
Median Absolute Deviation (MAD)591
Skewness1.342982
Sum30426
Variance1152836.1
MonotonicityNot monotonic
2023-12-12T21:08:54.113172image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=29)
ValueCountFrequency (%)
0 2
 
6.7%
4407 1
 
3.3%
1618 1
 
3.3%
88 1
 
3.3%
461 1
 
3.3%
884 1
 
3.3%
8 1
 
3.3%
124 1
 
3.3%
1173 1
 
3.3%
14 1
 
3.3%
Other values (19) 19
63.3%
ValueCountFrequency (%)
0 2
6.7%
8 1
3.3%
14 1
3.3%
66 1
3.3%
88 1
3.3%
118 1
3.3%
124 1
3.3%
144 1
3.3%
211 1
3.3%
348 1
3.3%
ValueCountFrequency (%)
4407 1
3.3%
2875 1
3.3%
2349 1
3.3%
2278 1
3.3%
2239 1
3.3%
2116 1
3.3%
2030 1
3.3%
1618 1
3.3%
1377 1
3.3%
1330 1
3.3%

4
Real number (ℝ)

HIGH CORRELATION  UNIQUE  ZEROS 

Distinct30
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean900.83333
Minimum0
Maximum4202
Zeros1
Zeros (%)3.3%
Negative0
Negative (%)0.0%
Memory size402.0 B
2023-12-12T21:08:54.246919image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile19.3
Q1151.75
median548.5
Q31180.75
95-th percentile2558.5
Maximum4202
Range4202
Interquartile range (IQR)1029

Descriptive statistics

Standard deviation1004.5405
Coefficient of variation (CV)1.1151236
Kurtosis2.7975373
Mean900.83333
Median Absolute Deviation (MAD)435.5
Skewness1.6323933
Sum27025
Variance1009101.7
MonotonicityNot monotonic
2023-12-12T21:08:54.387299image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=30)
ValueCountFrequency (%)
4202 1
 
3.3%
594 1
 
3.3%
122 1
 
3.3%
503 1
 
3.3%
806 1
 
3.3%
4 1
 
3.3%
47 1
 
3.3%
635 1
 
3.3%
38 1
 
3.3%
235 1
 
3.3%
Other values (20) 20
66.7%
ValueCountFrequency (%)
0 1
3.3%
4 1
3.3%
38 1
3.3%
47 1
3.3%
104 1
3.3%
122 1
3.3%
127 1
3.3%
145 1
3.3%
172 1
3.3%
193 1
3.3%
ValueCountFrequency (%)
4202 1
3.3%
2851 1
3.3%
2201 1
3.3%
2194 1
3.3%
2076 1
3.3%
2019 1
3.3%
1408 1
3.3%
1181 1
3.3%
1180 1
3.3%
1064 1
3.3%

5
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct30
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean877.2
Minimum17
Maximum4378
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size402.0 B
2023-12-12T21:08:54.544970image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum17
5-th percentile48.8
Q1140
median483.5
Q31288.25
95-th percentile2448.95
Maximum4378
Range4361
Interquartile range (IQR)1148.25

Descriptive statistics

Standard deviation1017.7538
Coefficient of variation (CV)1.16023
Kurtosis3.5442441
Mean877.2
Median Absolute Deviation (MAD)375.5
Skewness1.7629697
Sum26316
Variance1035822.8
MonotonicityNot monotonic
2023-12-12T21:08:54.688805image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=30)
ValueCountFrequency (%)
4378 1
 
3.3%
735 1
 
3.3%
139 1
 
3.3%
372 1
 
3.3%
808 1
 
3.3%
17 1
 
3.3%
131 1
 
3.3%
105 1
 
3.3%
62 1
 
3.3%
484 1
 
3.3%
Other values (20) 20
66.7%
ValueCountFrequency (%)
17 1
3.3%
38 1
3.3%
62 1
3.3%
68 1
3.3%
105 1
3.3%
111 1
3.3%
131 1
3.3%
139 1
3.3%
143 1
3.3%
151 1
3.3%
ValueCountFrequency (%)
4378 1
3.3%
2687 1
3.3%
2158 1
3.3%
2152 1
3.3%
2050 1
3.3%
1938 1
3.3%
1500 1
3.3%
1292 1
3.3%
1277 1
3.3%
888 1
3.3%

6
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct30
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean906.63333
Minimum52
Maximum4333
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size402.0 B
2023-12-12T21:08:54.813454image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum52
5-th percentile95.9
Q1270.5
median595
Q31158.75
95-th percentile2443.7
Maximum4333
Range4281
Interquartile range (IQR)888.25

Descriptive statistics

Standard deviation953.2106
Coefficient of variation (CV)1.0513739
Kurtosis4.7261557
Mean906.63333
Median Absolute Deviation (MAD)393.5
Skewness1.979965
Sum27199
Variance908610.45
MonotonicityNot monotonic
2023-12-12T21:08:54.959818image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=30)
ValueCountFrequency (%)
4333 1
 
3.3%
757 1
 
3.3%
150 1
 
3.3%
323 1
 
3.3%
707 1
 
3.3%
52 1
 
3.3%
325 1
 
3.3%
483 1
 
3.3%
95 1
 
3.3%
472 1
 
3.3%
Other values (20) 20
66.7%
ValueCountFrequency (%)
52 1
3.3%
95 1
3.3%
97 1
3.3%
110 1
3.3%
150 1
3.3%
192 1
3.3%
211 1
3.3%
253 1
3.3%
323 1
3.3%
325 1
3.3%
ValueCountFrequency (%)
4333 1
3.3%
2702 1
3.3%
2128 1
3.3%
2010 1
3.3%
1974 1
3.3%
1672 1
3.3%
1388 1
3.3%
1160 1
3.3%
1155 1
3.3%
851 1
3.3%

7
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct30
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean998.73333
Minimum37
Maximum4572
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size402.0 B
2023-12-12T21:08:55.096059image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum37
5-th percentile143.6
Q1300
median704.5
Q31312.5
95-th percentile2635.6
Maximum4572
Range4535
Interquartile range (IQR)1012.5

Descriptive statistics

Standard deviation1007.9674
Coefficient of variation (CV)1.0092458
Kurtosis4.3479084
Mean998.73333
Median Absolute Deviation (MAD)449
Skewness1.9061761
Sum29962
Variance1015998.3
MonotonicityNot monotonic
2023-12-12T21:08:55.236389image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=30)
ValueCountFrequency (%)
4572 1
 
3.3%
697 1
 
3.3%
131 1
 
3.3%
421 1
 
3.3%
879 1
 
3.3%
37 1
 
3.3%
402 1
 
3.3%
712 1
 
3.3%
250 1
 
3.3%
295 1
 
3.3%
Other values (20) 20
66.7%
ValueCountFrequency (%)
37 1
3.3%
131 1
3.3%
159 1
3.3%
167 1
3.3%
242 1
3.3%
250 1
3.3%
261 1
3.3%
295 1
3.3%
315 1
3.3%
327 1
3.3%
ValueCountFrequency (%)
4572 1
3.3%
2785 1
3.3%
2453 1
3.3%
2362 1
3.3%
2037 1
3.3%
1719 1
3.3%
1364 1
3.3%
1356 1
3.3%
1182 1
3.3%
1108 1
3.3%

8
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct30
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1100.9667
Minimum53
Maximum4670
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size402.0 B
2023-12-12T21:08:55.373447image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum53
5-th percentile83.8
Q1319
median832
Q31254
95-th percentile3074.45
Maximum4670
Range4617
Interquartile range (IQR)935

Descriptive statistics

Standard deviation1105.9836
Coefficient of variation (CV)1.0045568
Kurtosis2.5758579
Mean1100.9667
Median Absolute Deviation (MAD)509
Skewness1.6125492
Sum33029
Variance1223199.6
MonotonicityNot monotonic
2023-12-12T21:08:55.504842image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=30)
ValueCountFrequency (%)
4670 1
 
3.3%
842 1
 
3.3%
86 1
 
3.3%
352 1
 
3.3%
976 1
 
3.3%
82 1
 
3.3%
488 1
 
3.3%
857 1
 
3.3%
315 1
 
3.3%
53 1
 
3.3%
Other values (20) 20
66.7%
ValueCountFrequency (%)
53 1
3.3%
82 1
3.3%
86 1
3.3%
134 1
3.3%
190 1
3.3%
274 1
3.3%
279 1
3.3%
315 1
3.3%
331 1
3.3%
352 1
3.3%
ValueCountFrequency (%)
4670 1
3.3%
3218 1
3.3%
2899 1
3.3%
2427 1
3.3%
2408 1
3.3%
2320 1
3.3%
1694 1
3.3%
1275 1
3.3%
1191 1
3.3%
1143 1
3.3%

9
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct30
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1063.3667
Minimum35
Maximum3907
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size402.0 B
2023-12-12T21:08:55.635196image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum35
5-th percentile68.45
Q1318
median805.5
Q31504.75
95-th percentile2689
Maximum3907
Range3872
Interquartile range (IQR)1186.75

Descriptive statistics

Standard deviation967.7477
Coefficient of variation (CV)0.91007903
Kurtosis1.1122297
Mean1063.3667
Median Absolute Deviation (MAD)542
Skewness1.2028652
Sum31901
Variance936535.62
MonotonicityNot monotonic
2023-12-12T21:08:56.139946image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=30)
ValueCountFrequency (%)
3907 1
 
3.3%
902 1
 
3.3%
80 1
 
3.3%
507 1
 
3.3%
1035 1
 
3.3%
35 1
 
3.3%
538 1
 
3.3%
1038 1
 
3.3%
531 1
 
3.3%
59 1
 
3.3%
Other values (20) 20
66.7%
ValueCountFrequency (%)
35 1
3.3%
59 1
3.3%
80 1
3.3%
105 1
3.3%
163 1
3.3%
199 1
3.3%
222 1
3.3%
305 1
3.3%
357 1
3.3%
481 1
3.3%
ValueCountFrequency (%)
3907 1
3.3%
2707 1
3.3%
2667 1
3.3%
2331 1
3.3%
2232 1
3.3%
2102 1
3.3%
1861 1
3.3%
1579 1
3.3%
1282 1
3.3%
1126 1
3.3%

10
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct30
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1053.9333
Minimum39
Maximum3274
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size402.0 B
2023-12-12T21:08:56.357392image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum39
5-th percentile79.7
Q1285.25
median885.5
Q31614.5
95-th percentile2671.65
Maximum3274
Range3235
Interquartile range (IQR)1329.25

Descriptive statistics

Standard deviation889.13767
Coefficient of variation (CV)0.84363748
Kurtosis-0.018190435
Mean1053.9333
Median Absolute Deviation (MAD)631.5
Skewness0.9071463
Sum31618
Variance790565.79
MonotonicityNot monotonic
2023-12-12T21:08:56.517330image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=30)
ValueCountFrequency (%)
3274 1
 
3.3%
903 1
 
3.3%
94 1
 
3.3%
553 1
 
3.3%
1020 1
 
3.3%
39 1
 
3.3%
590 1
 
3.3%
1135 1
 
3.3%
868 1
 
3.3%
68 1
 
3.3%
Other values (20) 20
66.7%
ValueCountFrequency (%)
39 1
3.3%
68 1
3.3%
94 1
3.3%
102 1
3.3%
193 1
3.3%
230 1
3.3%
253 1
3.3%
255 1
3.3%
376 1
3.3%
447 1
3.3%
ValueCountFrequency (%)
3274 1
3.3%
2673 1
3.3%
2670 1
3.3%
2308 1
3.3%
2081 1
3.3%
1981 1
3.3%
1860 1
3.3%
1696 1
3.3%
1370 1
3.3%
1135 1
3.3%

11
Real number (ℝ)

HIGH CORRELATION  MISSING 

Distinct26
Distinct (%)96.3%
Missing3
Missing (%)10.0%
Infinite0
Infinite (%)0.0%
Mean1046.9259
Minimum16
Maximum2829
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size402.0 B
2023-12-12T21:08:56.691343image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum16
5-th percentile154.7
Q1265.5
median849
Q31693
95-th percentile2560.8
Maximum2829
Range2813
Interquartile range (IQR)1427.5

Descriptive statistics

Standard deviation861.91571
Coefficient of variation (CV)0.82328242
Kurtosis-0.80133279
Mean1046.9259
Median Absolute Deviation (MAD)590
Skewness0.68444376
Sum28267
Variance742898.69
MonotonicityNot monotonic
2023-12-12T21:08:56.869858image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=26)
ValueCountFrequency (%)
2224 2
 
6.7%
1807 1
 
3.3%
16 1
 
3.3%
605 1
 
3.3%
1043 1
 
3.3%
332 1
 
3.3%
143 1
 
3.3%
2299 1
 
3.3%
195 1
 
3.3%
849 1
 
3.3%
Other values (16) 16
53.3%
(Missing) 3
 
10.0%
ValueCountFrequency (%)
16 1
3.3%
143 1
3.3%
182 1
3.3%
195 1
3.3%
241 1
3.3%
259 1
3.3%
265 1
3.3%
266 1
3.3%
332 1
3.3%
376 1
3.3%
ValueCountFrequency (%)
2829 1
3.3%
2673 1
3.3%
2299 1
3.3%
2224 2
6.7%
1917 1
3.3%
1807 1
3.3%
1579 1
3.3%
1404 1
3.3%
1297 1
3.3%
1043 1
3.3%

12
Real number (ℝ)

HIGH CORRELATION  MISSING 

Distinct27
Distinct (%)100.0%
Missing3
Missing (%)10.0%
Infinite0
Infinite (%)0.0%
Mean1064.6667
Minimum31
Maximum2978
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size402.0 B
2023-12-12T21:08:57.039190image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum31
5-th percentile112.1
Q1297.5
median944
Q31624
95-th percentile2826.6
Maximum2978
Range2947
Interquartile range (IQR)1326.5

Descriptive statistics

Standard deviation896.57176
Coefficient of variation (CV)0.84211499
Kurtosis-0.38656769
Mean1064.6667
Median Absolute Deviation (MAD)664
Skewness0.79582319
Sum28746
Variance803840.92
MonotonicityNot monotonic
2023-12-12T21:08:57.198280image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=27)
ValueCountFrequency (%)
1689 1
 
3.3%
31 1
 
3.3%
549 1
 
3.3%
944 1
 
3.3%
101 1
 
3.3%
168 1
 
3.3%
2978 1
 
3.3%
138 1
 
3.3%
986 1
 
3.3%
999 1
 
3.3%
Other values (17) 17
56.7%
(Missing) 3
 
10.0%
ValueCountFrequency (%)
31 1
3.3%
101 1
3.3%
138 1
3.3%
168 1
3.3%
184 1
3.3%
253 1
3.3%
280 1
3.3%
315 1
3.3%
351 1
3.3%
363 1
3.3%
ValueCountFrequency (%)
2978 1
3.3%
2943 1
3.3%
2555 1
3.3%
2279 1
3.3%
1954 1
3.3%
1836 1
3.3%
1689 1
3.3%
1559 1
3.3%
1531 1
3.3%
1204 1
3.3%

Interactions

2023-12-12T21:08:50.498468image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T21:08:34.058012image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T21:08:35.763509image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T21:08:37.131325image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T21:08:38.573359image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T21:08:39.525143image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T21:08:40.732786image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T21:08:42.334386image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T21:08:43.436152image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T21:08:44.526150image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T21:08:46.048893image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T21:08:47.598073image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T21:08:48.820736image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T21:08:50.603639image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T21:08:34.155688image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T21:08:35.848321image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T21:08:37.246750image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T21:08:38.655568image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T21:08:39.597017image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T21:08:40.858680image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T21:08:42.420914image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T21:08:43.505657image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T21:08:44.609264image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T21:08:46.150256image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T21:08:47.688408image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T21:08:49.238740image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T21:08:50.697592image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T21:08:34.261862image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T21:08:35.947854image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T21:08:37.352692image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T21:08:38.731719image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T21:08:39.670729image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T21:08:40.967228image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T21:08:42.516814image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T21:08:43.576864image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T21:08:44.700155image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T21:08:46.257124image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T21:08:47.793916image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T21:08:49.342599image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T21:08:50.832693image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T21:08:34.375972image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T21:08:36.061554image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T21:08:37.491256image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T21:08:38.820557image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T21:08:39.769615image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T21:08:41.069906image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T21:08:42.616883image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T21:08:43.652596image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T21:08:44.832257image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T21:08:46.375869image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T21:08:47.914732image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T21:08:49.456985image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T21:08:50.930681image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T21:08:34.857737image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T21:08:36.171526image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T21:08:37.602353image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T21:08:38.896615image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T21:08:39.841356image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T21:08:41.175925image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T21:08:42.703473image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T21:08:43.715933image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T21:08:44.953718image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T21:08:46.493645image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T21:08:48.002711image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T21:08:49.565238image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T21:08:51.036146image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T21:08:34.941548image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T21:08:36.263968image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T21:08:37.721699image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T21:08:38.961589image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T21:08:39.917882image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T21:08:41.272243image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T21:08:42.788407image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T21:08:43.779633image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T21:08:45.069515image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T21:08:46.606894image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T21:08:48.085063image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T21:08:49.669302image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T21:08:51.132022image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T21:08:35.041105image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T21:08:36.382884image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T21:08:37.844319image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T21:08:39.023079image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T21:08:39.993508image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T21:08:41.349657image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T21:08:42.878706image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T21:08:43.857294image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T21:08:45.199933image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T21:08:46.723487image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T21:08:48.176203image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T21:08:49.774883image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T21:08:51.230075image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T21:08:35.153128image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T21:08:36.478317image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T21:08:37.958199image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T21:08:39.085451image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T21:08:40.103362image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T21:08:41.448898image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T21:08:42.957962image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T21:08:43.953324image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T21:08:45.317993image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T21:08:46.854696image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T21:08:48.260471image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T21:08:49.894884image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T21:08:51.378218image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T21:08:35.240668image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T21:08:36.587235image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T21:08:38.063076image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T21:08:39.145598image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T21:08:40.212429image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T21:08:41.541744image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T21:08:43.037636image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T21:08:44.054346image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T21:08:45.441646image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T21:08:46.983003image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T21:08:48.343395image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T21:08:49.987709image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T21:08:51.480923image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T21:08:35.330498image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T21:08:36.695585image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T21:08:38.157608image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T21:08:39.211529image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T21:08:40.310005image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T21:08:41.644733image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T21:08:43.108497image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T21:08:44.146493image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T21:08:45.560269image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T21:08:47.110872image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T21:08:48.439677image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T21:08:50.082941image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T21:08:51.605301image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T21:08:35.434617image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T21:08:36.821186image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T21:08:38.269561image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T21:08:39.293736image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T21:08:40.416737image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T21:08:42.056373image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T21:08:43.192293image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T21:08:44.243703image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T21:08:45.697925image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T21:08:47.250436image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T21:08:48.548733image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T21:08:50.199233image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T21:08:51.717538image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T21:08:35.564499image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T21:08:36.923861image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T21:08:38.382167image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T21:08:39.376113image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T21:08:40.508998image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T21:08:42.145411image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T21:08:43.286634image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T21:08:44.341470image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T21:08:45.814905image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T21:08:47.394564image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T21:08:48.642621image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T21:08:50.315060image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T21:08:51.829473image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T21:08:35.665981image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T21:08:37.033855image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T21:08:38.486562image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T21:08:39.447561image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T21:08:40.618703image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T21:08:42.250654image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T21:08:43.360054image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T21:08:44.432844image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T21:08:45.934756image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T21:08:47.499005image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T21:08:48.731854image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T21:08:50.418065image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-12T21:08:57.315030image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
구분내용123456789101112
구분1.0000.0000.0000.0000.0000.1450.2730.0000.0000.0000.0000.0000.0000.000
내용0.0001.0000.6170.6230.6040.3830.3080.3380.3650.4590.5100.0000.9060.924
10.0000.6171.0000.9440.8390.8780.8350.8720.9340.8720.8770.8340.6570.885
20.0000.6230.9441.0000.9740.9750.8630.8740.9540.9350.9240.8820.8180.835
30.0000.6040.8390.9741.0000.9640.9080.9220.9680.9550.9330.8470.7870.794
40.1450.3830.8780.9750.9641.0000.9010.8980.9620.9440.9360.8400.9130.818
50.2730.3080.8350.8630.9080.9011.0000.9920.8660.8270.8140.8710.7950.779
60.0000.3380.8720.8740.9220.8980.9921.0000.9300.9020.8810.8670.8450.837
70.0000.3650.9340.9540.9680.9620.8660.9301.0000.9940.9760.8810.8050.879
80.0000.4590.8720.9350.9550.9440.8270.9020.9941.0000.9630.8700.8300.914
90.0000.5100.8770.9240.9330.9360.8140.8810.9760.9631.0000.9430.8800.751
100.0000.0000.8340.8820.8470.8400.8710.8670.8810.8700.9431.0000.9140.848
110.0000.9060.6570.8180.7870.9130.7950.8450.8050.8300.8800.9141.0000.762
120.0000.9240.8850.8350.7940.8180.7790.8370.8790.9140.7510.8480.7621.000
2023-12-12T21:08:57.513620image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
구분123456789101112내용
구분1.000-0.403-0.432-0.406-0.422-0.482-0.419-0.387-0.365-0.356-0.321-0.265-0.3460.000
1-0.4031.0000.9010.9050.8950.8050.9120.8660.7680.8000.8020.7740.7900.324
2-0.4320.9011.0000.9180.8800.7250.8370.8080.7370.7670.7740.7240.7260.380
3-0.4060.9050.9181.0000.8860.8450.9370.9380.8980.8920.8820.8650.8860.363
4-0.4220.8950.8800.8861.0000.8650.8920.8760.7920.8260.8190.8090.8440.192
5-0.4820.8050.7250.8450.8651.0000.9160.8750.7940.7930.7700.7650.8280.162
6-0.4190.9120.8370.9370.8920.9161.0000.9620.9030.9060.8840.8770.9120.184
7-0.3870.8660.8080.9380.8760.8750.9621.0000.9710.9620.9420.9310.9430.179
8-0.3650.7680.7370.8980.7920.7940.9030.9711.0000.9790.9560.9620.9590.246
9-0.3560.8000.7670.8920.8260.7930.9060.9620.9791.0000.9900.9850.9580.285
10-0.3210.8020.7740.8820.8190.7700.8840.9420.9560.9901.0000.9800.9270.000
11-0.2650.7740.7240.8650.8090.7650.8770.9310.9620.9850.9801.0000.9640.723
12-0.3460.7900.7260.8860.8440.8280.9120.9430.9590.9580.9270.9641.0000.583
내용0.0000.3240.3800.3630.1920.1620.1840.1790.2460.2850.0000.7230.5831.000

Missing values

2023-12-12T21:08:52.008553image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-12T21:08:52.253715image/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.
2023-12-12T21:08:52.407292image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
The correlation heatmap measures nullity correlation: how strongly the presence or absence of one variable affects the presence of another.

Sample

구분내용123456789101112
02014건보423138444407420243784333457246703907327428292943
12014급여202816191618140812921155101410061579169615791689
22014일반12410266104151192242279105102182280
32015건보300727442875285126872702278528992707267326732555
42015급여14591329137796715001388136412751282137012971204
52015일반2972331441456897167190163193259184
62016건보256121672278219420502010203724272667267022241954
72016급여12281223133011801277116011821143108710117721006
82016일반196164211193233253315331222253241253
92017건보192418992030207621581974245324082331230819171836
구분내용123456789101112
202020일반2791590038110159134199230195138
212021건보3763749386843825135632182232186022992978
222021급여1313514235484472295535968143168
232021일반000386295250315531868332101
242022건보181213951173635105483712857103811351043944
252022급여499412447131325402488538590605549
262022일반109109841752378235391631
272023건보94080888480680870787997610351020<NA><NA>
282023급여494441461503372323421352507553<NA><NA>
292023일반4411288122139150131868094<NA><NA>