Overview

Dataset statistics

Number of variables16
Number of observations81
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory11.4 KiB
Average record size in memory144.6 B

Variable types

Text1
Numeric15

Dataset

Description농작물재해보험에 가입된 품목별(사과, 배, 단감 등)로 대상면적, 가입농가수, 가입건수, 가입농지수, 가입금액, 가입면적 등에 대한 데이터를 제공합니다.
Author농업정책보험금융원
URLhttps://www.data.go.kr/data/15126188/fileData.do

Alerts

대상면적 is highly overall correlated with 가입농가수 and 10 other fieldsHigh correlation
가입농가수 is highly overall correlated with 대상면적 and 11 other fieldsHigh correlation
가입건수 is highly overall correlated with 대상면적 and 11 other fieldsHigh correlation
가입농지수 is highly overall correlated with 대상면적 and 11 other fieldsHigh correlation
가입금액 is highly overall correlated with 대상면적 and 10 other fieldsHigh correlation
가입면적 is highly overall correlated with 대상면적 and 11 other fieldsHigh correlation
가입률 is highly overall correlated with 가입농가수 and 3 other fieldsHigh correlation
순보험료 is highly overall correlated with 대상면적 and 10 other fieldsHigh correlation
순환급금 is highly overall correlated with 대상면적 and 10 other fieldsHigh correlation
환급금 차감 후 순보험료 is highly overall correlated with 대상면적 and 10 other fieldsHigh correlation
위험보험료 is highly overall correlated with 대상면적 and 10 other fieldsHigh correlation
지급건수 is highly overall correlated with 대상면적 and 10 other fieldsHigh correlation
보험금 is highly overall correlated with 대상면적 and 10 other fieldsHigh correlation
품목 has unique valuesUnique
가입농지수 has unique valuesUnique
가입금액 has unique valuesUnique
가입면적 has unique valuesUnique
가입률 has unique valuesUnique
순보험료 has unique valuesUnique
환급금 차감 후 순보험료 has unique valuesUnique
위험보험료 has unique valuesUnique
가입농가수 has 1 (1.2%) zerosZeros
가입건수 has 1 (1.2%) zerosZeros
가입농지수 has 1 (1.2%) zerosZeros
가입면적 has 1 (1.2%) zerosZeros
가입률 has 1 (1.2%) zerosZeros
순환급금 has 30 (37.0%) zerosZeros
지급건수 has 3 (3.7%) zerosZeros
보험금 has 3 (3.7%) zerosZeros
손해율 has 3 (3.7%) zerosZeros

Reproduction

Analysis started2024-03-14 20:07:25.718684
Analysis finished2024-03-14 20:08:21.803084
Duration56.08 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

품목
Text

UNIQUE 

Distinct81
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size776.0 B
2024-03-15T05:08:22.643847image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length6
Median length5
Mean length3.3209877
Min length1

Characters and Unicode

Total characters269
Distinct characters108
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

Unique81 ?
Unique (%)100.0%

Sample

1st row사과
2nd row
3rd row단감
4th row떫은감
5th row감귤
ValueCountFrequency (%)
2
 
2.4%
사과 1
 
1.2%
호두 1
 
1.2%
시설딸기 1
 
1.2%
버섯재배사 1
 
1.2%
부대시설 1
 
1.2%
유리온실 1
 
1.2%
내재형하우스 1
 
1.2%
연동하우스 1
 
1.2%
단동하우스 1
 
1.2%
Other values (71) 71
86.6%
2024-03-15T05:08:23.842912image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
25
 
9.3%
23
 
8.6%
10
 
3.7%
7
 
2.6%
7
 
2.6%
7
 
2.6%
6
 
2.2%
6
 
2.2%
5
 
1.9%
5
 
1.9%
Other values (98) 168
62.5%

Most occurring categories

ValueCountFrequency (%)
Other Letter 268
99.6%
Space Separator 1
 
0.4%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
25
 
9.3%
23
 
8.6%
10
 
3.7%
7
 
2.6%
7
 
2.6%
7
 
2.6%
6
 
2.2%
6
 
2.2%
5
 
1.9%
5
 
1.9%
Other values (97) 167
62.3%
Space Separator
ValueCountFrequency (%)
1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 268
99.6%
Common 1
 
0.4%

Most frequent character per script

Hangul
ValueCountFrequency (%)
25
 
9.3%
23
 
8.6%
10
 
3.7%
7
 
2.6%
7
 
2.6%
7
 
2.6%
6
 
2.2%
6
 
2.2%
5
 
1.9%
5
 
1.9%
Other values (97) 167
62.3%
Common
ValueCountFrequency (%)
1
100.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 268
99.6%
ASCII 1
 
0.4%

Most frequent character per block

Hangul
ValueCountFrequency (%)
25
 
9.3%
23
 
8.6%
10
 
3.7%
7
 
2.6%
7
 
2.6%
7
 
2.6%
6
 
2.2%
6
 
2.2%
5
 
1.9%
5
 
1.9%
Other values (97) 167
62.3%
ASCII
ValueCountFrequency (%)
1
100.0%

대상면적
Real number (ℝ)

HIGH CORRELATION 

Distinct77
Distinct (%)95.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean18164.024
Minimum45
Maximum731245
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size857.0 B
2024-03-15T05:08:24.304749image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum45
5-th percentile107
Q1932.39
median2889
Q39708
95-th percentile62604
Maximum731245
Range731200
Interquartile range (IQR)8775.61

Descriptive statistics

Standard deviation81756.641
Coefficient of variation (CV)4.5010203
Kurtosis74.865519
Mean18164.024
Median Absolute Deviation (MAD)2547
Skewness8.5086984
Sum1471285.9
Variance6.6841484 × 109
MonotonicityNot monotonic
2024-03-15T05:08:24.991829image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
62604.0 5
 
6.2%
26153.0 1
 
1.2%
21503.0 1
 
1.2%
2993.0 1
 
1.2%
6045.0 1
 
1.2%
5287.0 1
 
1.2%
620.93 1
 
1.2%
1133.89 1
 
1.2%
709.74 1
 
1.2%
5178.0 1
 
1.2%
Other values (67) 67
82.7%
ValueCountFrequency (%)
45.0 1
1.2%
56.0 1
1.2%
87.0 1
1.2%
100.0 1
1.2%
107.0 1
1.2%
130.76 1
1.2%
143.0 1
1.2%
227.03 1
1.2%
237.0 1
1.2%
247.0 1
1.2%
ValueCountFrequency (%)
731245.0 1
 
1.2%
62604.0 5
6.2%
44267.0 1
 
1.2%
28869.0 1
 
1.2%
26153.0 1
 
1.2%
21503.0 1
 
1.2%
20206.0 1
 
1.2%
19681.0 1
 
1.2%
17955.0 1
 
1.2%
15509.0 1
 
1.2%

가입농가수
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct79
Distinct (%)97.5%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean6333.2716
Minimum0
Maximum266522
Zeros1
Zeros (%)1.2%
Negative0
Negative (%)0.0%
Memory size857.0 B
2024-03-15T05:08:25.431423image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile30
Q1187
median648
Q32979
95-th percentile17856
Maximum266522
Range266522
Interquartile range (IQR)2792

Descriptive statistics

Standard deviation30032.379
Coefficient of variation (CV)4.7420008
Kurtosis72.820045
Mean6333.2716
Median Absolute Deviation (MAD)568
Skewness8.357643
Sum512995
Variance9.0194381 × 108
MonotonicityNot monotonic
2024-03-15T05:08:25.874444image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
96 2
 
2.5%
680 2
 
2.5%
27800 1
 
1.2%
36963 1
 
1.2%
2187 1
 
1.2%
5144 1
 
1.2%
1102 1
 
1.2%
0 1
 
1.2%
201 1
 
1.2%
17856 1
 
1.2%
Other values (69) 69
85.2%
ValueCountFrequency (%)
0 1
1.2%
8 1
1.2%
25 1
1.2%
29 1
1.2%
30 1
1.2%
33 1
1.2%
44 1
1.2%
66 1
1.2%
70 1
1.2%
78 1
1.2%
ValueCountFrequency (%)
266522 1
1.2%
36963 1
1.2%
33568 1
1.2%
27800 1
1.2%
17856 1
1.2%
16747 1
1.2%
8618 1
1.2%
7723 1
1.2%
7710 1
1.2%
6911 1
1.2%

가입건수
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct80
Distinct (%)98.8%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean7332.6296
Minimum0
Maximum273927
Zeros1
Zeros (%)1.2%
Negative0
Negative (%)0.0%
Memory size857.0 B
2024-03-15T05:08:26.376663image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile37
Q1225
median866
Q33421
95-th percentile24096
Maximum273927
Range273927
Interquartile range (IQR)3196

Descriptive statistics

Standard deviation31351.932
Coefficient of variation (CV)4.2756737
Kurtosis67.46404
Mean7332.6296
Median Absolute Deviation (MAD)758
Skewness7.9579162
Sum593943
Variance9.8294363 × 108
MonotonicityNot monotonic
2024-03-15T05:08:26.708907image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
37 2
 
2.5%
35270 1
 
1.2%
108 1
 
1.2%
1396 1
 
1.2%
0 1
 
1.2%
225 1
 
1.2%
113 1
 
1.2%
24096 1
 
1.2%
61318 1
 
1.2%
32 1
 
1.2%
Other values (70) 70
86.4%
ValueCountFrequency (%)
0 1
1.2%
8 1
1.2%
32 1
1.2%
34 1
1.2%
37 2
2.5%
51 1
1.2%
67 1
1.2%
86 1
1.2%
93 1
1.2%
94 1
1.2%
ValueCountFrequency (%)
273927 1
1.2%
61318 1
1.2%
35270 1
1.2%
34463 1
1.2%
24096 1
1.2%
18787 1
1.2%
9839 1
1.2%
9807 1
1.2%
9385 1
1.2%
8929 1
1.2%

가입농지수
Real number (ℝ)

HIGH CORRELATION  UNIQUE  ZEROS 

Distinct81
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean32452.148
Minimum0
Maximum1715587
Zeros1
Zeros (%)1.2%
Negative0
Negative (%)0.0%
Memory size857.0 B
2024-03-15T05:08:27.051837image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile108
Q1608
median2590
Q310512
95-th percentile49667
Maximum1715587
Range1715587
Interquartile range (IQR)9904

Descriptive statistics

Standard deviation192579.09
Coefficient of variation (CV)5.9342479
Kurtosis75.555518
Mean32452.148
Median Absolute Deviation (MAD)2393
Skewness8.5887268
Sum2628624
Variance3.7086706 × 1010
MonotonicityNot monotonic
2024-03-15T05:08:27.463784image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
53619 1
 
1.2%
49667 1
 
1.2%
28691 1
 
1.2%
6260 1
 
1.2%
0 1
 
1.2%
354 1
 
1.2%
298 1
 
1.2%
29556 1
 
1.2%
302471 1
 
1.2%
50 1
 
1.2%
Other values (71) 71
87.7%
ValueCountFrequency (%)
0 1
1.2%
9 1
1.2%
50 1
1.2%
69 1
1.2%
108 1
1.2%
114 1
1.2%
127 1
1.2%
130 1
1.2%
137 1
1.2%
141 1
1.2%
ValueCountFrequency (%)
1715587 1
1.2%
302471 1
1.2%
56500 1
1.2%
53619 1
1.2%
49667 1
1.2%
46423 1
1.2%
43493 1
1.2%
29556 1
1.2%
28691 1
1.2%
20303 1
1.2%

가입금액
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct81
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean323207.32
Minimum133.48
Maximum5995118.9
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size857.0 B
2024-03-15T05:08:27.997398image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum133.48
5-th percentile996.79
Q14677.92
median17572.88
Q3121318.42
95-th percentile1339631.8
Maximum5995118.9
Range5994985.4
Interquartile range (IQR)116640.5

Descriptive statistics

Standard deviation1078014.2
Coefficient of variation (CV)3.3353643
Kurtosis17.74552
Mean323207.32
Median Absolute Deviation (MAD)16257.88
Skewness4.2823025
Sum26179793
Variance1.1621145 × 1012
MonotonicityNot monotonic
2024-03-15T05:08:28.451986image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1339631.84 1
 
1.2%
181464.85 1
 
1.2%
358519.55 1
 
1.2%
305804.07 1
 
1.2%
3583743.83 1
 
1.2%
222165.55 1
 
1.2%
18566.64 1
 
1.2%
5001725.95 1
 
1.2%
5995118.91 1
 
1.2%
288.06 1
 
1.2%
Other values (71) 71
87.7%
ValueCountFrequency (%)
133.48 1
1.2%
197.74 1
1.2%
288.06 1
1.2%
963.93 1
1.2%
996.79 1
1.2%
1002.98 1
1.2%
1280.29 1
1.2%
1315.0 1
1.2%
1382.8 1
1.2%
1546.6 1
1.2%
ValueCountFrequency (%)
5995118.91 1
1.2%
5001725.95 1
1.2%
4960224.02 1
1.2%
3583743.83 1
1.2%
1339631.84 1
1.2%
516293.28 1
1.2%
358519.55 1
1.2%
339990.38 1
1.2%
329003.71 1
1.2%
305804.07 1
1.2%

가입면적
Real number (ℝ)

HIGH CORRELATION  UNIQUE  ZEROS 

Distinct81
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean7528.3117
Minimum0
Maximum435224.94
Zeros1
Zeros (%)1.2%
Negative0
Negative (%)0.0%
Memory size857.0 B
2024-03-15T05:08:28.878941image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile10.65
Q1128.74
median588.1
Q31644.13
95-th percentile13697.83
Maximum435224.94
Range435224.94
Interquartile range (IQR)1515.39

Descriptive statistics

Standard deviation48305.496
Coefficient of variation (CV)6.4165111
Kurtosis79.687414
Mean7528.3117
Median Absolute Deviation (MAD)553.59
Skewness8.8939886
Sum609793.25
Variance2.3334209 × 109
MonotonicityNot monotonic
2024-03-15T05:08:29.278717image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
23371.61 1
 
1.2%
2462.54 1
 
1.2%
2090.79 1
 
1.2%
156.25 1
 
1.2%
0.0 1
 
1.2%
194.12 1
 
1.2%
26.3 1
 
1.2%
7905.93 1
 
1.2%
17098.57 1
 
1.2%
76.87 1
 
1.2%
Other values (71) 71
87.7%
ValueCountFrequency (%)
0.0 1
1.2%
5.36 1
1.2%
7.42 1
1.2%
9.08 1
1.2%
10.65 1
1.2%
12.01 1
1.2%
16.7 1
1.2%
21.86 1
1.2%
22.2 1
1.2%
26.3 1
1.2%
ValueCountFrequency (%)
435224.94 1
1.2%
23371.61 1
1.2%
18939.58 1
1.2%
17098.57 1
1.2%
13697.83 1
1.2%
8369.29 1
1.2%
8122.71 1
1.2%
7920.52 1
1.2%
7905.93 1
1.2%
5537.93 1
1.2%

가입률
Real number (ℝ)

HIGH CORRELATION  UNIQUE  ZEROS 

Distinct81
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean27.249259
Minimum0
Maximum90.27
Zeros1
Zeros (%)1.2%
Negative0
Negative (%)0.0%
Memory size857.0 B
2024-03-15T05:08:29.518670image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile3.04
Q111.38
median22.85
Q338.7
95-th percentile69.28
Maximum90.27
Range90.27
Interquartile range (IQR)27.32

Descriptive statistics

Standard deviation21.893184
Coefficient of variation (CV)0.80344144
Kurtosis0.60725098
Mean27.249259
Median Absolute Deviation (MAD)12.41
Skewness1.0662803
Sum2207.19
Variance479.3115
MonotonicityNot monotonic
2024-03-15T05:08:29.768148image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
89.36 1
 
1.2%
55.56 1
 
1.2%
34.59 1
 
1.2%
2.96 1
 
1.2%
0.0 1
 
1.2%
0.31 1
 
1.2%
0.04 1
 
1.2%
12.63 1
 
1.2%
27.31 1
 
1.2%
12.38 1
 
1.2%
Other values (71) 71
87.7%
ValueCountFrequency (%)
0.0 1
1.2%
0.04 1
1.2%
0.31 1
1.2%
2.96 1
1.2%
3.04 1
1.2%
3.48 1
1.2%
3.75 1
1.2%
3.98 1
1.2%
4.27 1
1.2%
4.61 1
1.2%
ValueCountFrequency (%)
90.27 1
1.2%
89.36 1
1.2%
82.43 1
1.2%
76.82 1
1.2%
69.28 1
1.2%
63.7 1
1.2%
61.3 1
1.2%
59.52 1
1.2%
59.0 1
1.2%
57.12 1
1.2%

순보험료
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct81
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean11735.749
Minimum4.64
Maximum223054.4
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size857.0 B
2024-03-15T05:08:30.017243image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum4.64
5-th percentile28.96
Q1319.09
median858.46
Q37502.06
95-th percentile55136.82
Maximum223054.4
Range223049.76
Interquartile range (IQR)7182.97

Descriptive statistics

Standard deviation33091.603
Coefficient of variation (CV)2.8197265
Kurtosis26.743951
Mean11735.749
Median Absolute Deviation (MAD)831.84
Skewness4.9148869
Sum950595.7
Variance1.0950542 × 109
MonotonicityNot monotonic
2024-03-15T05:08:30.527044image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
223054.4 1
 
1.2%
2394.75 1
 
1.2%
9615.05 1
 
1.2%
2898.12 1
 
1.2%
10102.84 1
 
1.2%
2152.7 1
 
1.2%
264.15 1
 
1.2%
67447.2 1
 
1.2%
72967.23 1
 
1.2%
33.49 1
 
1.2%
Other values (71) 71
87.7%
ValueCountFrequency (%)
4.64 1
1.2%
4.77 1
1.2%
22.87 1
1.2%
26.62 1
1.2%
28.96 1
1.2%
29.88 1
1.2%
33.49 1
1.2%
39.53 1
1.2%
50.01 1
1.2%
65.53 1
1.2%
ValueCountFrequency (%)
223054.4 1
1.2%
170411.88 1
1.2%
72967.23 1
1.2%
67447.2 1
1.2%
55136.82 1
1.2%
42186.46 1
1.2%
35639.0 1
1.2%
31334.4 1
1.2%
24586.63 1
1.2%
23161.29 1
1.2%

순환급금
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct46
Distinct (%)56.8%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean11.596543
Minimum0
Maximum348.07
Zeros30
Zeros (%)37.0%
Negative0
Negative (%)0.0%
Memory size857.0 B
2024-03-15T05:08:30.905638image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0.16
Q32.4
95-th percentile46.79
Maximum348.07
Range348.07
Interquartile range (IQR)2.4

Descriptive statistics

Standard deviation44.468313
Coefficient of variation (CV)3.8346179
Kurtosis42.935021
Mean11.596543
Median Absolute Deviation (MAD)0.16
Skewness6.1588919
Sum939.32
Variance1977.4308
MonotonicityNot monotonic
2024-03-15T05:08:31.350920image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=46)
ValueCountFrequency (%)
0.0 30
37.0%
0.01 4
 
4.9%
0.07 2
 
2.5%
0.99 2
 
2.5%
0.16 2
 
2.5%
348.07 1
 
1.2%
6.22 1
 
1.2%
23.94 1
 
1.2%
0.57 1
 
1.2%
6.79 1
 
1.2%
Other values (36) 36
44.4%
ValueCountFrequency (%)
0.0 30
37.0%
0.01 4
 
4.9%
0.02 1
 
1.2%
0.05 1
 
1.2%
0.06 1
 
1.2%
0.07 2
 
2.5%
0.16 2
 
2.5%
0.19 1
 
1.2%
0.27 1
 
1.2%
0.28 1
 
1.2%
ValueCountFrequency (%)
348.07 1
1.2%
157.1 1
1.2%
106.01 1
1.2%
74.46 1
1.2%
46.79 1
1.2%
43.75 1
1.2%
27.95 1
1.2%
23.94 1
1.2%
17.46 1
1.2%
13.79 1
1.2%

환급금 차감 후 순보험료
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct81
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean11724.153
Minimum4.64
Maximum222706.33
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size857.0 B
2024-03-15T05:08:31.813660image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum4.64
5-th percentile28.96
Q1319.09
median858.46
Q37501.86
95-th percentile54979.72
Maximum222706.33
Range222701.69
Interquartile range (IQR)7182.77

Descriptive statistics

Standard deviation33054.174
Coefficient of variation (CV)2.8193231
Kurtosis26.724037
Mean11724.153
Median Absolute Deviation (MAD)831.84
Skewness4.9135244
Sum949656.37
Variance1.0925784 × 109
MonotonicityNot monotonic
2024-03-15T05:08:32.470392image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
222706.33 1
 
1.2%
2393.21 1
 
1.2%
9611.76 1
 
1.2%
2897.79 1
 
1.2%
10096.05 1
 
1.2%
2152.13 1
 
1.2%
264.15 1
 
1.2%
67423.26 1
 
1.2%
72923.48 1
 
1.2%
33.49 1
 
1.2%
Other values (71) 71
87.7%
ValueCountFrequency (%)
4.64 1
1.2%
4.77 1
1.2%
22.87 1
1.2%
26.62 1
1.2%
28.96 1
1.2%
29.88 1
1.2%
33.49 1
1.2%
39.53 1
1.2%
50.0 1
1.2%
65.52 1
1.2%
ValueCountFrequency (%)
222706.33 1
1.2%
170337.42 1
1.2%
72923.48 1
1.2%
67423.26 1
1.2%
54979.72 1
1.2%
42139.67 1
1.2%
35628.7 1
1.2%
31332.54 1
1.2%
24583.01 1
1.2%
23055.28 1
1.2%

위험보험료
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct81
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean10559.46
Minimum4.16
Maximum202459.31
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size857.0 B
2024-03-15T05:08:33.010494image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum4.16
5-th percentile25.92
Q1285.67
median768.57
Q36716.08
95-th percentile49981.08
Maximum202459.31
Range202455.15
Interquartile range (IQR)6430.41

Descriptive statistics

Standard deviation29858.331
Coefficient of variation (CV)2.8276381
Kurtosis27.07502
Mean10559.46
Median Absolute Deviation (MAD)744.74
Skewness4.9402646
Sum855316.24
Variance8.9151993 × 108
MonotonicityNot monotonic
2024-03-15T05:08:33.533808image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
202459.31 1
 
1.2%
2142.48 1
 
1.2%
8604.94 1
 
1.2%
2594.5 1
 
1.2%
9038.51 1
 
1.2%
1926.71 1
 
1.2%
236.49 1
 
1.2%
60361.18 1
 
1.2%
65284.75 1
 
1.2%
29.98 1
 
1.2%
Other values (71) 71
87.7%
ValueCountFrequency (%)
4.16 1
1.2%
4.27 1
1.2%
20.47 1
1.2%
23.83 1
1.2%
25.92 1
1.2%
26.75 1
1.2%
29.98 1
1.2%
35.39 1
1.2%
44.76 1
1.2%
58.66 1
1.2%
ValueCountFrequency (%)
202459.31 1
1.2%
152493.73 1
1.2%
65284.75 1
1.2%
60361.18 1
1.2%
49981.08 1
1.2%
38301.86 1
1.2%
31896.75 1
1.2%
28050.59 1
1.2%
22008.07 1
1.2%
20638.67 1
1.2%

보험료율
Real number (ℝ)

Distinct78
Distinct (%)96.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean8.2793827
Minimum0.28
Maximum29.77
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size857.0 B
2024-03-15T05:08:33.999059image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0.28
5-th percentile0.99
Q13.41
median4.99
Q312.48
95-th percentile24.67
Maximum29.77
Range29.49
Interquartile range (IQR)9.07

Descriptive statistics

Standard deviation7.6874232
Coefficient of variation (CV)0.92850198
Kurtosis0.89397628
Mean8.2793827
Median Absolute Deviation (MAD)2.86
Skewness1.3355041
Sum670.63
Variance59.096476
MonotonicityNot monotonic
2024-03-15T05:08:34.489000image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
4.18 2
 
2.5%
14.64 2
 
2.5%
4.99 2
 
2.5%
16.65 1
 
1.2%
11.63 1
 
1.2%
0.95 1
 
1.2%
0.28 1
 
1.2%
0.97 1
 
1.2%
1.42 1
 
1.2%
1.35 1
 
1.2%
Other values (68) 68
84.0%
ValueCountFrequency (%)
0.28 1
1.2%
0.37 1
1.2%
0.95 1
1.2%
0.97 1
1.2%
0.99 1
1.2%
1.03 1
1.2%
1.22 1
1.2%
1.32 1
1.2%
1.35 1
1.2%
1.4 1
1.2%
ValueCountFrequency (%)
29.77 1
1.2%
29.19 1
1.2%
28.39 1
1.2%
27.95 1
1.2%
24.67 1
1.2%
24.59 1
1.2%
22.58 1
1.2%
20.98 1
1.2%
20.27 1
1.2%
18.92 1
1.2%

지급건수
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct73
Distinct (%)90.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2002.8642
Minimum0
Maximum55920
Zeros3
Zeros (%)3.7%
Negative0
Negative (%)0.0%
Memory size857.0 B
2024-03-15T05:08:34.741145image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile4
Q129
median141
Q3895
95-th percentile9207
Maximum55920
Range55920
Interquartile range (IQR)866

Descriptive statistics

Standard deviation7089.0242
Coefficient of variation (CV)3.5394432
Kurtosis43.915952
Mean2002.8642
Median Absolute Deviation (MAD)137
Skewness6.2451604
Sum162232
Variance50254263
MonotonicityNot monotonic
2024-03-15T05:08:35.161519image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 3
 
3.7%
12 2
 
2.5%
4 2
 
2.5%
16 2
 
2.5%
29 2
 
2.5%
5 2
 
2.5%
6 2
 
2.5%
74 1
 
1.2%
2566 1
 
1.2%
2426 1
 
1.2%
Other values (63) 63
77.8%
ValueCountFrequency (%)
0 3
3.7%
1 1
 
1.2%
4 2
2.5%
5 2
2.5%
6 2
2.5%
9 1
 
1.2%
12 2
2.5%
14 1
 
1.2%
16 2
2.5%
17 1
 
1.2%
ValueCountFrequency (%)
55920 1
1.2%
25554 1
1.2%
16975 1
1.2%
9519 1
1.2%
9207 1
1.2%
4567 1
1.2%
3791 1
1.2%
3744 1
1.2%
3236 1
1.2%
2566 1
1.2%

보험금
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct79
Distinct (%)97.5%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean6861.4451
Minimum0
Maximum128736.77
Zeros3
Zeros (%)3.7%
Negative0
Negative (%)0.0%
Memory size857.0 B
2024-03-15T05:08:35.585794image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile3.29
Q181.2
median567.09
Q34934.34
95-th percentile25698.06
Maximum128736.77
Range128736.77
Interquartile range (IQR)4853.14

Descriptive statistics

Standard deviation20465.799
Coefficient of variation (CV)2.9827243
Kurtosis27.13721
Mean6861.4451
Median Absolute Deviation (MAD)554.87
Skewness5.0510773
Sum555777.05
Variance4.1884892 × 108
MonotonicityNot monotonic
2024-03-15T05:08:36.040594image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.0 3
 
3.7%
121025.25 1
 
1.2%
34.83 1
 
1.2%
733.51 1
 
1.2%
548.49 1
 
1.2%
9876.53 1
 
1.2%
237.09 1
 
1.2%
29.29 1
 
1.2%
13201.57 1
 
1.2%
19630.78 1
 
1.2%
Other values (69) 69
85.2%
ValueCountFrequency (%)
0.0 3
3.7%
2.52 1
 
1.2%
3.29 1
 
1.2%
10.48 1
 
1.2%
12.22 1
 
1.2%
14.54 1
 
1.2%
17.32 1
 
1.2%
21.23 1
 
1.2%
29.03 1
 
1.2%
29.29 1
 
1.2%
ValueCountFrequency (%)
128736.77 1
1.2%
121025.25 1
1.2%
47790.85 1
1.2%
29711.7 1
1.2%
25698.06 1
1.2%
21187.67 1
1.2%
20216.79 1
1.2%
19630.78 1
1.2%
15315.23 1
1.2%
13201.57 1
1.2%

손해율
Real number (ℝ)

ZEROS 

Distinct79
Distinct (%)97.5%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean72.00358
Minimum0
Maximum405.47
Zeros3
Zeros (%)3.7%
Negative0
Negative (%)0.0%
Memory size857.0 B
2024-03-15T05:08:36.529000image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile5.93
Q125.29
median57.16
Q394.57
95-th percentile168.5
Maximum405.47
Range405.47
Interquartile range (IQR)69.28

Descriptive statistics

Standard deviation67.932137
Coefficient of variation (CV)0.94345498
Kurtosis7.2477505
Mean72.00358
Median Absolute Deviation (MAD)33.53
Skewness2.2277892
Sum5832.29
Variance4614.7752
MonotonicityNot monotonic
2024-03-15T05:08:36.790478image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.0 3
 
3.7%
59.78 1
 
1.2%
116.16 1
 
1.2%
8.52 1
 
1.2%
21.14 1
 
1.2%
109.27 1
 
1.2%
12.31 1
 
1.2%
12.39 1
 
1.2%
21.87 1
 
1.2%
30.07 1
 
1.2%
Other values (69) 69
85.2%
ValueCountFrequency (%)
0.0 3
3.7%
3.25 1
 
1.2%
5.93 1
 
1.2%
8.52 1
 
1.2%
8.7 1
 
1.2%
9.42 1
 
1.2%
12.31 1
 
1.2%
12.39 1
 
1.2%
15.31 1
 
1.2%
16.08 1
 
1.2%
ValueCountFrequency (%)
405.47 1
1.2%
270.04 1
1.2%
251.94 1
1.2%
239.08 1
1.2%
168.5 1
1.2%
161.65 1
1.2%
153.67 1
1.2%
151.0 1
1.2%
149.83 1
1.2%
136.94 1
1.2%

Interactions

2024-03-15T05:08:17.458835image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T05:07:26.565137image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T05:07:29.927050image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T05:07:33.317857image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T05:07:36.922462image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T05:07:40.967438image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T05:07:44.595325image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T05:07:48.562061image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T05:07:52.031768image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T05:07:55.010006image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T05:07:59.579706image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T05:08:03.122831image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T05:08:06.864783image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T05:08:10.535212image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T05:08:14.575705image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T05:08:17.784063image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T05:07:26.877310image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T05:07:30.159578image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T05:07:33.578760image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T05:07:37.331618image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T05:07:41.226403image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T05:07:44.843889image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T05:07:48.811854image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T05:07:52.279827image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T05:07:55.169471image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T05:07:59.847667image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T05:08:03.393435image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T05:08:07.059799image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T05:08:10.797898image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T05:08:14.837127image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T05:08:18.005512image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T05:07:27.031277image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T05:07:30.334244image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T05:07:33.822767image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T05:07:37.597471image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T05:07:41.471282image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T05:07:45.078863image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T05:07:49.049818image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T05:07:52.526015image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T05:07:55.415956image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T05:08:00.135159image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T05:08:03.649123image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T05:08:07.202431image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T05:08:11.050278image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T05:08:15.093133image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T05:08:18.203024image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T05:07:27.262083image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T05:07:30.578141image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T05:07:34.016017image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T05:07:37.863439image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T05:07:41.716189image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T05:07:45.316775image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T05:07:49.285343image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T05:07:52.668810image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T05:07:55.721511image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T05:08:00.386837image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T05:08:03.909487image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T05:08:07.465160image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T05:08:11.312233image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T05:08:15.263078image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T05:08:18.371871image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T05:07:27.429798image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T05:07:30.777741image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T05:07:34.174919image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T05:07:38.156619image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T05:07:41.980658image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T05:07:45.628442image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T05:07:49.537924image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T05:07:52.870713image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T05:07:55.993065image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T05:08:00.650855image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T05:08:04.082693image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T05:08:07.795131image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T05:08:11.554632image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T05:08:15.425749image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T05:08:18.624072image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T05:07:27.626337image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T05:07:30.938999image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T05:07:34.325699image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T05:07:38.467316image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T05:07:42.231791image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T05:07:46.070579image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T05:07:49.783721image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T05:07:53.114119image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T05:07:56.247231image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T05:08:00.855820image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T05:08:04.333905image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T05:08:08.062999image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T05:08:12.017928image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T05:08:15.577924image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T05:08:18.870119image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T05:07:27.847844image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T05:07:31.076462image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T05:07:34.461765image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T05:07:38.728095image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T05:07:42.470421image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T05:07:46.300215image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T05:07:50.014055image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T05:07:53.342007image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T05:07:56.528896image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T05:08:00.986685image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T05:08:04.579902image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T05:08:08.298344image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T05:08:12.259145image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T05:08:15.717821image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T05:08:19.067330image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T05:07:27.989341image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T05:07:31.298318image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T05:07:34.654082image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T05:07:38.985052image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T05:07:42.613546image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T05:07:46.534316image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T05:07:50.241200image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T05:07:53.589739image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T05:07:56.905284image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T05:08:01.130947image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T05:08:04.770055image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T05:08:08.534837image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T05:08:12.520043image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T05:08:15.862665image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T05:08:19.297724image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T05:07:28.214761image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T05:07:31.513240image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T05:07:34.889273image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T05:07:39.243614image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T05:07:42.813781image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T05:07:46.767541image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T05:07:50.400526image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T05:07:53.760695image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T05:07:57.250189image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T05:08:01.363707image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T05:08:04.955695image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T05:08:08.775811image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T05:08:12.800697image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T05:08:16.113820image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T05:08:19.562726image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T05:07:28.476105image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T05:07:31.769843image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T05:07:35.145997image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T05:07:39.521166image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T05:07:43.075301image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T05:07:47.022594image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T05:07:50.554838image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T05:07:54.017459image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T05:07:57.667750image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T05:08:01.616145image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T05:08:05.222423image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T05:08:08.986671image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T05:08:13.074368image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T05:08:16.337317image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T05:08:19.817280image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T05:07:28.721285image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T05:07:32.003865image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T05:07:35.441000image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T05:07:39.671453image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T05:07:43.315253image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T05:07:47.259628image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T05:07:50.790251image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T05:07:54.148555image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T05:07:57.926309image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T05:08:01.855611image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T05:08:05.469935image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T05:08:09.231775image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T05:08:13.308735image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T05:08:16.479409image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T05:08:20.094941image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T05:07:29.003337image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T05:07:32.265266image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T05:07:35.767357image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T05:07:39.926092image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T05:07:43.582016image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T05:07:47.574271image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T05:07:51.049849image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T05:07:54.306583image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T05:07:58.247107image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T05:08:02.119081image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T05:08:05.742816image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T05:08:09.557090image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T05:08:13.569542image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T05:08:16.643356image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T05:08:20.275529image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T05:07:29.262673image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T05:07:32.680766image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T05:07:36.119817image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T05:07:40.190381image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T05:07:43.831571image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T05:07:47.823357image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T05:07:51.297539image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T05:07:54.459418image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T05:07:58.513925image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T05:08:02.367052image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T05:08:06.069070image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T05:08:09.825505image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T05:08:13.830951image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T05:08:16.803900image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T05:08:20.430319image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T05:07:29.512331image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T05:07:32.847335image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T05:07:36.376983image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T05:07:40.438981image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T05:07:44.076095image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T05:07:48.062722image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T05:07:51.534729image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T05:07:54.600582image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T05:07:58.767534image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T05:08:02.606698image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T05:08:06.322427image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T05:08:10.084707image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T05:08:14.071139image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T05:08:16.950284image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T05:08:20.587976image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T05:07:29.727519image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T05:07:33.057245image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T05:07:36.642397image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T05:07:40.700559image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T05:07:44.328404image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T05:07:48.305437image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T05:07:51.776309image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T05:07:54.852276image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T05:07:59.049520image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T05:08:02.858420image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T05:08:06.593767image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T05:08:10.367928image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T05:08:14.315786image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T05:08:17.187478image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-03-15T05:08:36.989957image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
품목대상면적가입농가수가입건수가입농지수가입금액가입면적가입률순보험료순환급금환급금 차감 후 순보험료위험보험료보험료율지급건수보험금손해율
품목1.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.000
대상면적1.0001.0001.0001.0001.0000.5650.6890.2941.0001.0001.0001.0000.0001.0000.5650.000
가입농가수1.0001.0001.0001.0000.9760.7451.0000.3920.9890.9850.9890.9960.4030.9040.7170.000
가입건수1.0001.0001.0001.0001.0000.8321.0000.2730.9280.9130.9280.9870.4510.9030.7240.000
가입농지수1.0001.0000.9761.0001.0000.8261.0000.0000.9860.9860.9861.0000.0000.8260.5880.000
가입금액1.0000.5650.7450.8320.8261.0000.5650.3300.8300.7940.8300.8840.0000.9500.8260.000
가입면적1.0000.6891.0001.0001.0000.5651.0000.2941.0001.0001.0001.0000.0001.0000.5650.000
가입률1.0000.2940.3920.2730.0000.3300.2941.0000.7280.7780.7280.6070.3040.5140.1820.000
순보험료1.0001.0000.9890.9280.9860.8301.0000.7281.0000.9871.0000.9970.4360.8620.8000.000
순환급금1.0001.0000.9850.9130.9860.7941.0000.7780.9871.0000.9870.9820.1960.8280.7080.000
환급금 차감 후 순보험료1.0001.0000.9890.9280.9860.8301.0000.7281.0000.9871.0000.9970.4360.8620.8000.000
위험보험료1.0001.0000.9960.9871.0000.8841.0000.6070.9970.9820.9971.0000.3000.8880.7860.000
보험료율1.0000.0000.4030.4510.0000.0000.0000.3040.4360.1960.4360.3001.0000.4400.7120.000
지급건수1.0001.0000.9040.9030.8260.9501.0000.5140.8620.8280.8620.8880.4401.0000.9680.000
보험금1.0000.5650.7170.7240.5880.8260.5650.1820.8000.7080.8000.7860.7120.9681.0000.000
손해율1.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0001.000
2024-03-15T05:08:37.370239image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
대상면적가입농가수가입건수가입농지수가입금액가입면적가입률순보험료순환급금환급금 차감 후 순보험료위험보험료보험료율지급건수보험금손해율
대상면적1.0000.7060.6900.6340.7660.7650.1180.7460.5220.7460.7460.0450.7300.7160.128
가입농가수0.7061.0000.9920.9250.8190.9100.5520.8650.6710.8650.8650.1770.8090.7810.028
가입건수0.6900.9921.0000.9420.8340.9030.5660.8700.6800.8700.8700.1550.7990.7750.003
가입농지수0.6340.9250.9421.0000.7950.8610.5670.7640.5820.7640.7640.0030.6700.651-0.077
가입금액0.7660.8190.8340.7951.0000.7350.4160.9160.6880.9160.916-0.1000.7420.799-0.046
가입면적0.7650.9100.9030.8610.7351.0000.6260.8060.5080.8060.8060.2200.7880.7600.152
가입률0.1180.5520.5660.5670.4160.6261.0000.4770.2120.4770.4770.1490.3880.4070.046
순보험료0.7460.8650.8700.7640.9160.8060.4771.0000.7101.0001.0000.2670.9030.9390.129
순환급금0.5220.6710.6800.5820.6880.5080.2120.7101.0000.7100.7100.0970.6090.631-0.051
환급금 차감 후 순보험료0.7460.8650.8700.7640.9160.8060.4771.0000.7101.0001.0000.2670.9030.9390.129
위험보험료0.7460.8650.8700.7640.9160.8060.4771.0000.7101.0001.0000.2670.9030.9390.129
보험료율0.0450.1770.1550.003-0.1000.2200.1490.2670.0970.2670.2671.0000.4340.3800.360
지급건수0.7300.8090.7990.6700.7420.7880.3880.9030.6090.9030.9030.4341.0000.9630.396
보험금0.7160.7810.7750.6510.7990.7600.4070.9390.6310.9390.9390.3800.9631.0000.416
손해율0.1280.0280.003-0.077-0.0460.1520.0460.129-0.0510.1290.1290.3600.3960.4161.000

Missing values

2024-03-15T05:08:20.917388image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-03-15T05:08:21.552555image/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

품목대상면적가입농가수가입건수가입농지수가입금액가입면적가입률순보험료순환급금환급금 차감 후 순보험료위험보험료보험료율지급건수보험금손해율
0사과26153.02780035270536191339631.8423371.6189.36223054.4348.07222706.33202459.3116.6516975121025.2559.78
110574.07710980711984329003.718122.7176.8255136.82157.154979.7249981.0816.7619568860.2417.73
2단감10346.029793462412597597.873151.0230.469940.9313.799927.149024.2310.196802579.0328.58
3떫은감13687.069117643980181642.314397.3632.1320078.1127.9520050.1618226.5324.5932366098.633.46
4감귤15388.06565789911226148826.954715.730.656225.380.076225.315573.224.1823311451.3726.04
5복숭아15509.08618983910729288243.495537.9335.7142186.4646.7942139.6738301.8614.64379125698.0667.09
6포도9708.0255328042590117003.591106.8811.411167.7913.4611154.3310134.179.548045139.6550.72
7자두5799.031793421350839841.751362.6923.511630.368.3711621.9910563.7629.1916996734.2963.75
8매실8633.014181580173314707.19791.289.172082.390.92081.481863.1214.168952235.1119.97
9참다래1491.02632723095492.19129.388.68598.40.67597.73535.0910.993444.7283.11
품목대상면적가입농가수가입건수가입농지수가입금액가입면적가입률순보험료순환급금환급금 차감 후 순보험료위험보험료보험료율지급건수보험금손해율
71시설부추1115.06481295709721041.25347.9731.21764.860.07764.79684.73.64131378.655.29
72시설시금치2257.053686652309300.38256.8211.38464.030.16463.86415.284.995998.1223.63
73시설가지237.0436531124020125.14135.3857.12742.990.66742.34664.583.6920126.9419.1
74시설파2461.0596839449410148.61219.518.92368.280.27368.01329.463.632972.8922.13
75시설배추1938.0502812570114035.97264.813.66590.080.02590.06528.294.252233.5444.21
76시설무790.0558892621715037.19309.1739.13428.830.01428.82383.912.8567113.1529.47
77시설백합87.02537108996.799.0810.4422.870.022.8720.472.2913.2916.08
78시설카네이션45.033371372333.9810.6523.6699.250.099.2588.864.2500.00.0
79시설미나리508.019828410864677.4966.9413.18157.980.99156.99140.553.38612.228.7
80시설쑥갓289.012417112813253.2164.9222.46166.40.01166.39148.975.111237.6725.29