Overview

Dataset statistics

Number of variables4
Number of observations22
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory902.0 B
Average record size in memory41.0 B

Variable types

Text1
Numeric3

Dataset

Description연도별로 농작물재해보험에 계약된 건수들을지급건수(건), 지급보험금(백만원), 손해율(퍼센트) 등등 지급실적을 정리한 자료
Author농업정책보험금융원
URLhttps://www.data.go.kr/data/15068602/fileData.do

Alerts

지급건수(건) is highly overall correlated with 지급보험금(백만원) High correlation
지급보험금(백만원) is highly overall correlated with 지급건수(건) High correlation
연도 has unique valuesUnique
지급건수(건) has unique valuesUnique
지급보험금(백만원) has unique valuesUnique
손해율(퍼센트) has unique valuesUnique

Reproduction

Analysis started2023-12-12 20:12:21.265128
Analysis finished2023-12-12 20:12:22.367760
Duration1.1 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

연도
Text

UNIQUE 

Distinct22
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size308.0 B
2023-12-13T05:12:22.575984image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length5
Median length5
Mean length5
Min length5

Characters and Unicode

Total characters110
Distinct characters11
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

Unique22 ?
Unique (%)100.0%

Sample

1st row2001년
2nd row2002년
3rd row2003년
4th row2004년
5th row2005년
ValueCountFrequency (%)
2001년 1
 
4.5%
2002년 1
 
4.5%
2021년 1
 
4.5%
2020년 1
 
4.5%
2019년 1
 
4.5%
2018년 1
 
4.5%
2017년 1
 
4.5%
2016년 1
 
4.5%
2015년 1
 
4.5%
2014년 1
 
4.5%
Other values (12) 12
54.5%
2023-12-13T05:12:23.027453image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 33
30.0%
2 28
25.5%
년 22
20.0%
1 13
 
11.8%
3 2
 
1.8%
4 2
 
1.8%
5 2
 
1.8%
6 2
 
1.8%
7 2
 
1.8%
8 2
 
1.8%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 88
80.0%
Other Letter 22
 
20.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 33
37.5%
2 28
31.8%
1 13
 
14.8%
3 2
 
2.3%
4 2
 
2.3%
5 2
 
2.3%
6 2
 
2.3%
7 2
 
2.3%
8 2
 
2.3%
9 2
 
2.3%
Other Letter
ValueCountFrequency (%)
년 22
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 88
80.0%
Hangul 22
 
20.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 33
37.5%
2 28
31.8%
1 13
 
14.8%
3 2
 
2.3%
4 2
 
2.3%
5 2
 
2.3%
6 2
 
2.3%
7 2
 
2.3%
8 2
 
2.3%
9 2
 
2.3%
Hangul
ValueCountFrequency (%)
년 22
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 88
80.0%
Hangul 22
 
20.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 33
37.5%
2 28
31.8%
1 13
 
14.8%
3 2
 
2.3%
4 2
 
2.3%
5 2
 
2.3%
6 2
 
2.3%
7 2
 
2.3%
8 2
 
2.3%
9 2
 
2.3%
Hangul
ValueCountFrequency (%)
년 22
100.0%

지급건수(건)
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct22
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean55011.955
Minimum410
Maximum225240
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size330.0 B
2023-12-13T05:12:23.216650image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum410
5-th percentile3407.25
Q16996.25
median13184.5
Q378689.75
95-th percentile189608.5
Maximum225240
Range224830
Interquartile range (IQR)71693.5

Descriptive statistics

Standard deviation73027.691
Coefficient of variation (CV)1.3274877
Kurtosis0.17482777
Mean55011.955
Median Absolute Deviation (MAD)9298
Skewness1.3052
Sum1210263
Variance5.3330436 × 109
MonotonicityNot monotonic
2023-12-13T05:12:23.359070image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=22)
ValueCountFrequency (%)
410 1
 
4.5%
10630 1
 
4.5%
162232 1
 
4.5%
172822 1
 
4.5%
225240 1
 
4.5%
190492 1
 
4.5%
85099 1
 
4.5%
33577 1
 
4.5%
147109 1
 
4.5%
7150 1
 
4.5%
Other values (12) 12
54.5%
ValueCountFrequency (%)
410 1
4.5%
3354 1
4.5%
4419 1
4.5%
6077 1
4.5%
6344 1
4.5%
6945 1
4.5%
7150 1
4.5%
9300 1
4.5%
10156 1
4.5%
10630 1
4.5%
ValueCountFrequency (%)
225240 1
4.5%
190492 1
4.5%
172822 1
4.5%
162232 1
4.5%
147109 1
4.5%
85099 1
4.5%
59462 1
4.5%
33577 1
4.5%
25125 1
4.5%
17951 1
4.5%

지급보험금(백만원)
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct22
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean237198.82
Minimum1379
Maximum1015827
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size330.0 B
2023-12-13T05:12:23.516042image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1379
5-th percentile13974.65
Q137303.75
median78253
Q3438151.75
95-th percentile881845.05
Maximum1015827
Range1014448
Interquartile range (IQR)400848

Descriptive statistics

Standard deviation302413.69
Coefficient of variation (CV)1.2749376
Kurtosis1.1692888
Mean237198.82
Median Absolute Deviation (MAD)55761.5
Skewness1.4663537
Sum5218374
Variance9.1454041 × 1010
MonotonicityNot monotonic
2023-12-13T05:12:23.694074image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=22)
ValueCountFrequency (%)
1379 1
 
4.5%
45088 1
 
4.5%
555777 1
 
4.5%
573989 1
 
4.5%
1015827 1
 
4.5%
898048 1
 
4.5%
534450 1
 
4.5%
279673 1
 
4.5%
106904 1
 
4.5%
52444 1
 
4.5%
Other values (12) 12
54.5%
ValueCountFrequency (%)
1379 1
4.5%
13599 1
4.5%
21112 1
4.5%
23871 1
4.5%
24932 1
4.5%
34709 1
4.5%
45088 1
4.5%
50018 1
4.5%
52444 1
4.5%
61464 1
4.5%
ValueCountFrequency (%)
1015827 1
4.5%
898048 1
4.5%
573989 1
4.5%
555777 1
4.5%
534450 1
4.5%
490978 1
4.5%
279673 1
4.5%
144978 1
4.5%
132628 1
4.5%
106904 1
4.5%

손해율(퍼센트)
Real number (ℝ)

UNIQUE 

Distinct22
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean115.59545
Minimum18.2
Maximum433.5
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size330.0 B
2023-12-13T05:12:23.845939image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum18.2
5-th percentile22.46
Q143.875
median81.6
Q3117.225
95-th percentile353.785
Maximum433.5
Range415.3
Interquartile range (IQR)73.35

Descriptive statistics

Standard deviation110.3693
Coefficient of variation (CV)0.95478931
Kurtosis2.909742
Mean115.59545
Median Absolute Deviation (MAD)38
Skewness1.8461825
Sum2543.1
Variance12181.383
MonotonicityNot monotonic
2023-12-13T05:12:23.991883image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=22)
ValueCountFrequency (%)
45.7 1
 
4.5%
21.9 1
 
4.5%
65.0 1
 
4.5%
74.2 1
 
4.5%
150.6 1
 
4.5%
186.2 1
 
4.5%
103.2 1
 
4.5%
89.0 1
 
4.5%
33.1 1
 
4.5%
18.2 1
 
4.5%
Other values (12) 12
54.5%
ValueCountFrequency (%)
18.2 1
4.5%
21.9 1
4.5%
33.1 1
4.5%
36.6 1
4.5%
42.3 1
4.5%
43.5 1
4.5%
45.0 1
4.5%
45.7 1
4.5%
65.0 1
4.5%
66.9 1
4.5%
ValueCountFrequency (%)
433.5 1
4.5%
357.1 1
4.5%
290.8 1
4.5%
186.2 1
4.5%
150.6 1
4.5%
119.5 1
4.5%
110.4 1
4.5%
105.8 1
4.5%
104.6 1
4.5%
103.2 1
4.5%

Interactions

2023-12-13T05:12:21.865835image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T05:12:21.359261image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T05:12:21.589003image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T05:12:21.957389image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T05:12:21.437716image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T05:12:21.682101image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T05:12:22.062124image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T05:12:21.513781image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T05:12:21.774786image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-13T05:12:24.088292image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
연도지급건수(건)지급보험금(백만원)손해율(퍼센트)
연도1.0001.0001.0001.000
지급건수(건)1.0001.0000.9440.920
지급보험금(백만원)1.0000.9441.0000.835
손해율(퍼센트)1.0000.9200.8351.000
2023-12-13T05:12:24.214579image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
지급건수(건)지급보험금(백만원)손해율(퍼센트)
지급건수(건)1.0000.9650.366
지급보험금(백만원)0.9651.0000.433
손해율(퍼센트)0.3660.4331.000

Missing values

2023-12-13T05:12:22.187472image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-13T05:12:22.318454image/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

연도지급건수(건)지급보험금(백만원)손해율(퍼센트)
02001년410137945.7
12002년694534709433.5
22003년1015650018290.8
32004년33541359942.3
42005년63442387143.5
52006년60772111236.6
62007년930061464110.4
72008년44192493245.0
82009년1111066176105.8
92010년1795190330104.6
연도지급건수(건)지급보험금(백만원)손해율(퍼센트)
122013년106304508821.9
132014년1525914497866.9
142015년71505244418.2
152016년14710910690433.1
162017년3357727967389.0
172018년85099534450103.2
182019년190492898048186.2
192020년2252401015827150.6
202021년17282257398974.2
212022년16223255577765.0