Overview

Dataset statistics

Number of variables6
Number of observations52
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory2.8 KiB
Average record size in memory55.5 B

Variable types

Text1
Numeric5

Dataset

Description농작물 중에서 재해보험에 가입된 농지수를 품목별로 사과, 배, 단감, 떫은감, 감귤 등 사고접수건에 대한 데이터를 제공합니다.
Author농업정책보험금융원
URLhttps://www.data.go.kr/data/15126077/fileData.do

Alerts

사고접수 농지수 합계 is highly overall correlated with 1회 사고접수 농지수 and 3 other fieldsHigh correlation
1회 사고접수 농지수 is highly overall correlated with 사고접수 농지수 합계 and 3 other fieldsHigh correlation
2회 사고접수 농지수 is highly overall correlated with 사고접수 농지수 합계 and 3 other fieldsHigh correlation
3회 사고접수 농지수 is highly overall correlated with 사고접수 농지수 합계 and 3 other fieldsHigh correlation
4회 이상 사고접수 농지수 is highly overall correlated with 사고접수 농지수 합계 and 3 other fieldsHigh correlation
품목 has unique valuesUnique
사고접수 농지수 합계 has unique valuesUnique
2회 사고접수 농지수 has 7 (13.5%) zerosZeros
3회 사고접수 농지수 has 20 (38.5%) zerosZeros
4회 이상 사고접수 농지수 has 29 (55.8%) zerosZeros

Reproduction

Analysis started2024-01-06 13:12:44.605272
Analysis finished2024-01-06 13:12:54.104557
Duration9.5 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

품목
Text

UNIQUE 

Distinct52
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size548.0 B
2024-01-06T13:12:54.537748image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length14
Median length13
Mean length3.1153846
Min length1

Characters and Unicode

Total characters162
Distinct characters85
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique52 ?
Unique (%)100.0%

Sample

1st row전품목
2nd row사과
3rd row배
4th row단감
5th row떫은감
ValueCountFrequency (%)
포함 2
 
3.6%
벼 2
 
3.6%
전품목 1
 
1.8%
당근 1
 
1.8%
고추 1
 
1.8%
마늘 1
 
1.8%
양배추 1
 
1.8%
브로콜리 1
 
1.8%
고랭지무 1
 
1.8%
월동무 1
 
1.8%
Other values (43) 43
78.2%
2024-01-06T13:12:56.072873image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
자 7
 
4.3%
감 6
 
3.7%
추 6
 
3.7%
배 6
 
3.7%
고 5
 
3.1%
수 4
 
2.5%
파 4
 
2.5%
사 4
 
2.5%
) 3
 
1.9%
( 3
 
1.9%
Other values (75) 114
70.4%

Most occurring categories

ValueCountFrequency (%)
Other Letter 153
94.4%
Close Punctuation 3
 
1.9%
Open Punctuation 3
 
1.9%
Space Separator 3
 
1.9%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
자 7
 
4.6%
감 6
 
3.9%
추 6
 
3.9%
배 6
 
3.9%
고 5
 
3.3%
수 4
 
2.6%
파 4
 
2.6%
사 4
 
2.6%
랭 3
 
2.0%
시 3
 
2.0%
Other values (72) 105
68.6%
Close Punctuation
ValueCountFrequency (%)
) 3
100.0%
Open Punctuation
ValueCountFrequency (%)
( 3
100.0%
Space Separator
ValueCountFrequency (%)
3
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 153
94.4%
Common 9
 
5.6%

Most frequent character per script

Hangul
ValueCountFrequency (%)
자 7
 
4.6%
감 6
 
3.9%
추 6
 
3.9%
배 6
 
3.9%
고 5
 
3.3%
수 4
 
2.6%
파 4
 
2.6%
사 4
 
2.6%
랭 3
 
2.0%
시 3
 
2.0%
Other values (72) 105
68.6%
Common
ValueCountFrequency (%)
) 3
33.3%
( 3
33.3%
3
33.3%

Most occurring blocks

ValueCountFrequency (%)
Hangul 153
94.4%
ASCII 9
 
5.6%

Most frequent character per block

Hangul
ValueCountFrequency (%)
자 7
 
4.6%
감 6
 
3.9%
추 6
 
3.9%
배 6
 
3.9%
고 5
 
3.3%
수 4
 
2.6%
파 4
 
2.6%
사 4
 
2.6%
랭 3
 
2.0%
시 3
 
2.0%
Other values (72) 105
68.6%
ASCII
ValueCountFrequency (%)
) 3
33.3%
( 3
33.3%
3
33.3%

사고접수 농지수 합계
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct52
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean20238.538
Minimum4
Maximum526202
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size600.0 B
2024-01-06T13:12:56.786330image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum4
5-th percentile37.85
Q1184
median1414
Q34595
95-th percentile38727.2
Maximum526202
Range526198
Interquartile range (IQR)4411

Descriptive statistics

Standard deviation82929.226
Coefficient of variation (CV)4.0975897
Kurtosis30.248553
Mean20238.538
Median Absolute Deviation (MAD)1333
Skewness5.4066123
Sum1052404
Variance6.8772566 × 109
MonotonicityNot monotonic
2024-01-06T13:12:57.474498image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
526202 1
 
1.9%
6464 1
 
1.9%
8229 1
 
1.9%
1911 1
 
1.9%
1522 1
 
1.9%
89 1
 
1.9%
11929 1
 
1.9%
726 1
 
1.9%
557 1
 
1.9%
2101 1
 
1.9%
Other values (42) 42
80.8%
ValueCountFrequency (%)
4 1
1.9%
11 1
1.9%
34 1
1.9%
41 1
1.9%
55 1
1.9%
68 1
1.9%
70 1
1.9%
73 1
1.9%
89 1
1.9%
140 1
1.9%
ValueCountFrequency (%)
526202 1
1.9%
300281 1
1.9%
42223 1
1.9%
35867 1
1.9%
30690 1
1.9%
19814 1
1.9%
11929 1
1.9%
9447 1
1.9%
8229 1
1.9%
7119 1
1.9%

1회 사고접수 농지수
Real number (ℝ)

HIGH CORRELATION 

Distinct51
Distinct (%)98.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean17390.731
Minimum4
Maximum452159
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size600.0 B
2024-01-06T13:12:58.169674image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum4
5-th percentile37.3
Q1176
median1079.5
Q33508.25
95-th percentile25000.85
Maximum452159
Range452155
Interquartile range (IQR)3332.25

Descriptive statistics

Standard deviation73463.17
Coefficient of variation (CV)4.2242716
Kurtosis28.073846
Mean17390.731
Median Absolute Deviation (MAD)1004.5
Skewness5.2623706
Sum904318
Variance5.3968373 × 109
MonotonicityNot monotonic
2024-01-06T13:12:58.729964image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
68 2
 
3.8%
6320 1
 
1.9%
8126 1
 
1.9%
1834 1
 
1.9%
1177 1
 
1.9%
82 1
 
1.9%
10274 1
 
1.9%
681 1
 
1.9%
545 1
 
1.9%
2054 1
 
1.9%
Other values (41) 41
78.8%
ValueCountFrequency (%)
4 1
1.9%
11 1
1.9%
34 1
1.9%
40 1
1.9%
55 1
1.9%
65 1
1.9%
68 2
3.8%
82 1
1.9%
101 1
1.9%
137 1
1.9%
ValueCountFrequency (%)
452159 1
1.9%
290260 1
1.9%
29617 1
1.9%
21224 1
1.9%
17419 1
1.9%
16761 1
1.9%
10274 1
1.9%
8126 1
1.9%
6320 1
1.9%
5223 1
1.9%

2회 사고접수 농지수
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct42
Distinct (%)80.8%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2199.6538
Minimum0
Maximum57191
Zeros7
Zeros (%)13.5%
Negative0
Negative (%)0.0%
Memory size600.0 B
2024-01-06T13:12:59.157468image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q17.75
median46.5
Q3536
95-th percentile11498.25
Maximum57191
Range57191
Interquartile range (IQR)528.25

Descriptive statistics

Standard deviation8387.6579
Coefficient of variation (CV)3.8131718
Kurtosis37.826928
Mean2199.6538
Median Absolute Deviation (MAD)46.5
Skewness5.8919556
Sum114382
Variance70352806
MonotonicityNot monotonic
2024-01-06T13:12:59.697284image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=42)
ValueCountFrequency (%)
0 7
 
13.5%
3 3
 
5.8%
8 2
 
3.8%
20 2
 
3.8%
12 1
 
1.9%
13998 1
 
1.9%
99 1
 
1.9%
75 1
 
1.9%
313 1
 
1.9%
7 1
 
1.9%
Other values (32) 32
61.5%
ValueCountFrequency (%)
0 7
13.5%
1 1
 
1.9%
2 1
 
1.9%
3 3
5.8%
7 1
 
1.9%
8 2
 
3.8%
12 1
 
1.9%
20 2
 
3.8%
24 1
 
1.9%
29 1
 
1.9%
ValueCountFrequency (%)
57191 1
1.9%
15892 1
1.9%
13998 1
1.9%
9453 1
1.9%
2530 1
1.9%
2512 1
1.9%
2282 1
1.9%
2214 1
1.9%
1820 1
1.9%
1510 1
1.9%

3회 사고접수 농지수
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct25
Distinct (%)48.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean485
Minimum0
Maximum12610
Zeros20
Zeros (%)38.5%
Negative0
Negative (%)0.0%
Memory size600.0 B
2024-01-06T13:13:00.242407image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median1.5
Q366.5
95-th percentile2461.1
Maximum12610
Range12610
Interquartile range (IQR)66.5

Descriptive statistics

Standard deviation1874.8484
Coefficient of variation (CV)3.8656668
Kurtosis35.813185
Mean485
Median Absolute Deviation (MAD)1.5
Skewness5.7216291
Sum25220
Variance3515056.5
MonotonicityNot monotonic
2024-01-06T13:13:00.619218image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=25)
ValueCountFrequency (%)
0 20
38.5%
1 6
 
11.5%
2 3
 
5.8%
6 2
 
3.8%
12610 1
 
1.9%
434 1
 
1.9%
9 1
 
1.9%
68 1
 
1.9%
18 1
 
1.9%
138 1
 
1.9%
Other values (15) 15
28.8%
ValueCountFrequency (%)
0 20
38.5%
1 6
 
11.5%
2 3
 
5.8%
3 1
 
1.9%
6 2
 
3.8%
8 1
 
1.9%
9 1
 
1.9%
10 1
 
1.9%
18 1
 
1.9%
31 1
 
1.9%
ValueCountFrequency (%)
12610 1
1.9%
3879 1
1.9%
3615 1
1.9%
1517 1
1.9%
1043 1
1.9%
562 1
1.9%
539 1
1.9%
434 1
1.9%
357 1
1.9%
138 1
1.9%

4회 이상 사고접수 농지수
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct16
Distinct (%)30.8%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean163.15385
Minimum0
Maximum4242
Zeros29
Zeros (%)55.8%
Negative0
Negative (%)0.0%
Memory size600.0 B
2024-01-06T13:13:01.306147image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q34.5
95-th percentile851.7
Maximum4242
Range4242
Interquartile range (IQR)4.5

Descriptive statistics

Standard deviation639.03617
Coefficient of variation (CV)3.9167705
Kurtosis33.952411
Mean163.15385
Median Absolute Deviation (MAD)0
Skewness5.5497037
Sum8484
Variance408367.23
MonotonicityNot monotonic
2024-01-06T13:13:02.063665image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=16)
ValueCountFrequency (%)
0 29
55.8%
1 6
 
11.5%
2 3
 
5.8%
13 2
 
3.8%
107 1
 
1.9%
7 1
 
1.9%
571 1
 
1.9%
6 1
 
1.9%
4242 1
 
1.9%
1492 1
 
1.9%
Other values (6) 6
 
11.5%
ValueCountFrequency (%)
0 29
55.8%
1 6
 
11.5%
2 3
 
5.8%
4 1
 
1.9%
6 1
 
1.9%
7 1
 
1.9%
13 2
 
3.8%
66 1
 
1.9%
92 1
 
1.9%
107 1
 
1.9%
ValueCountFrequency (%)
4242 1
1.9%
1492 1
1.9%
1097 1
1.9%
651 1
1.9%
571 1
1.9%
111 1
1.9%
107 1
1.9%
92 1
1.9%
66 1
1.9%
13 2
3.8%

Interactions

2024-01-06T13:12:51.813450image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-06T13:12:44.971147image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-06T13:12:46.424700image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-06T13:12:48.504030image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-06T13:12:50.286455image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-06T13:12:52.081551image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-06T13:12:45.204707image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-06T13:12:46.796406image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-06T13:12:48.847300image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-06T13:12:50.554434image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-06T13:12:52.362731image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-06T13:12:45.441788image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-06T13:12:47.210310image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-06T13:12:49.233082image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-06T13:12:50.866596image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-06T13:12:52.667275image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-06T13:12:45.715685image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-06T13:12:47.526769image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-06T13:12:49.629684image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-06T13:12:51.298437image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-06T13:12:52.954450image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-06T13:12:46.144905image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-06T13:12:48.125674image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-06T13:12:49.984067image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-06T13:12:51.592260image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-01-06T13:13:02.336089image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
품목사고접수 농지수 합계1회 사고접수 농지수2회 사고접수 농지수3회 사고접수 농지수4회 이상 사고접수 농지수
품목1.0001.0001.0001.0001.0001.000
사고접수 농지수 합계1.0001.0001.0001.0000.6960.696
1회 사고접수 농지수1.0001.0001.0001.0000.6960.696
2회 사고접수 농지수1.0001.0001.0001.0000.8290.784
3회 사고접수 농지수1.0000.6960.6960.8291.0000.998
4회 이상 사고접수 농지수1.0000.6960.6960.7840.9981.000
2024-01-06T13:13:02.873404image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
사고접수 농지수 합계1회 사고접수 농지수2회 사고접수 농지수3회 사고접수 농지수4회 이상 사고접수 농지수
사고접수 농지수 합계1.0000.9910.9230.8020.789
1회 사고접수 농지수0.9911.0000.8840.7490.732
2회 사고접수 농지수0.9230.8841.0000.9180.892
3회 사고접수 농지수0.8020.7490.9181.0000.904
4회 이상 사고접수 농지수0.7890.7320.8920.9041.000

Missing values

2024-01-06T13:12:53.429018image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-01-06T13:12:53.968979image/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

품목사고접수 농지수 합계1회 사고접수 농지수2회 사고접수 농지수3회 사고접수 농지수4회 이상 사고접수 농지수
0전품목52620245215957191126104242
1사과42223212241589236151492
2배71192291221415171097
3단감1737100853313066
4떫은감658843001820357111
5감귤71134200228253992
6복숭아9447522325301043651
7포도18641151643664
8자두3026245344811213
9매실133813172010
품목사고접수 농지수 합계1회 사고접수 농지수2회 사고접수 농지수3회 사고접수 농지수4회 이상 사고접수 농지수
42차249246300
43오디156155100
44인삼397233465456813
45대추3748355718092
46밤293928974110
47복분자191183800
48오미자140137300
49호두3434000
50원예시설(시설작물 포함)19814167612512434107
51버섯재배사(버섯작물 포함)2171872910