Overview

Dataset statistics

Number of variables10
Number of observations586
Missing cells1411
Missing cells (%)24.1%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory48.2 KiB
Average record size in memory84.2 B

Variable types

Numeric4
DateTime2
Text2
Categorical2

Dataset

Description경기도 양주시 인터넷업무게시판 기부현황에 관한 데이터로 기부일자, 기부현금, 기부현물, 기부현물수량, 기부현물환가액 등의 내용을 포함하고 있습니다.
Author경기도 양주시
URLhttps://www.data.go.kr/data/15090105/fileData.do

Alerts

데이터기준일자 has constant value ""Constant
부서명 is highly overall correlated with 담당자High correlation
담당자 is highly overall correlated with 구분 and 1 other fieldsHigh correlation
구분 is highly overall correlated with 담당자High correlation
기부현금 is highly overall correlated with 기부현물환가액High correlation
기부현물수량 is highly overall correlated with 기부현물환가액High correlation
기부현물환가액 is highly overall correlated with 기부현금 and 1 other fieldsHigh correlation
기부일시 has 17 (2.9%) missing valuesMissing
기부현금 has 361 (61.6%) missing valuesMissing
기부현물품목 has 289 (49.3%) missing valuesMissing
기부현물환가액 has 300 (51.2%) missing valuesMissing
비고 has 444 (75.8%) missing valuesMissing
구분 has unique valuesUnique
기부현물수량 has 266 (45.4%) zerosZeros

Reproduction

Analysis started2023-12-12 16:49:51.760456
Analysis finished2023-12-12 16:49:54.993036
Duration3.23 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

구분
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct586
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean293.5
Minimum1
Maximum586
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size5.3 KiB
2023-12-13T01:49:55.084064image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile30.25
Q1147.25
median293.5
Q3439.75
95-th percentile556.75
Maximum586
Range585
Interquartile range (IQR)292.5

Descriptive statistics

Standard deviation169.3079
Coefficient of variation (CV)0.57685828
Kurtosis-1.2
Mean293.5
Median Absolute Deviation (MAD)146.5
Skewness0
Sum171991
Variance28665.167
MonotonicityStrictly decreasing
2023-12-13T01:49:55.281919image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
586 1
 
0.2%
183 1
 
0.2%
199 1
 
0.2%
198 1
 
0.2%
197 1
 
0.2%
196 1
 
0.2%
195 1
 
0.2%
194 1
 
0.2%
193 1
 
0.2%
192 1
 
0.2%
Other values (576) 576
98.3%
ValueCountFrequency (%)
1 1
0.2%
2 1
0.2%
3 1
0.2%
4 1
0.2%
5 1
0.2%
6 1
0.2%
7 1
0.2%
8 1
0.2%
9 1
0.2%
10 1
0.2%
ValueCountFrequency (%)
586 1
0.2%
585 1
0.2%
584 1
0.2%
583 1
0.2%
582 1
0.2%
581 1
0.2%
580 1
0.2%
579 1
0.2%
578 1
0.2%
577 1
0.2%

기부일시
Date

MISSING 

Distinct351
Distinct (%)61.7%
Missing17
Missing (%)2.9%
Memory size4.7 KiB
Minimum2017-03-09 00:00:00
Maximum2021-04-16 00:00:00
2023-12-13T01:49:55.466042image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T01:49:55.628763image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

기부현금
Real number (ℝ)

HIGH CORRELATION  MISSING 

Distinct63
Distinct (%)28.0%
Missing361
Missing (%)61.6%
Infinite0
Infinite (%)0.0%
Mean3029409.5
Minimum28500
Maximum2 × 108
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size5.3 KiB
2023-12-13T01:49:55.824833image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum28500
5-th percentile100000
Q1500000
median1000000
Q32000000
95-th percentile10000000
Maximum2 × 108
Range1.999715 × 108
Interquartile range (IQR)1500000

Descriptive statistics

Standard deviation13786662
Coefficient of variation (CV)4.5509403
Kurtosis188.63485
Mean3029409.5
Median Absolute Deviation (MAD)756390
Skewness13.317897
Sum6.8161714 × 108
Variance1.9007204 × 1014
MonotonicityNot monotonic
2023-12-13T01:49:56.070109image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1000000 56
 
9.6%
2000000 25
 
4.3%
500000 21
 
3.6%
5000000 16
 
2.7%
3000000 13
 
2.2%
10000000 11
 
1.9%
100000 7
 
1.2%
1500000 6
 
1.0%
300000 4
 
0.7%
200000 4
 
0.7%
Other values (53) 62
 
10.6%
(Missing) 361
61.6%
ValueCountFrequency (%)
28500 1
 
0.2%
29810 1
 
0.2%
30000 1
 
0.2%
50000 1
 
0.2%
63000 1
 
0.2%
82100 1
 
0.2%
90000 1
 
0.2%
100000 7
1.2%
112210 1
 
0.2%
120000 1
 
0.2%
ValueCountFrequency (%)
200000000 1
 
0.2%
50000000 1
 
0.2%
10500000 1
 
0.2%
10000000 11
1.9%
7500000 1
 
0.2%
7000000 1
 
0.2%
5500000 2
 
0.3%
5000000 16
2.7%
4000000 1
 
0.2%
3450000 1
 
0.2%

기부현물품목
Text

MISSING 

Distinct60
Distinct (%)20.2%
Missing289
Missing (%)49.3%
Memory size4.7 KiB
2023-12-13T01:49:56.336329image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length12
Median length10
Mean length4.2962963
Min length1

Characters and Unicode

Total characters1276
Distinct characters91
Distinct categories8 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique29 ?
Unique (%)9.8%

Sample

1st row마스크
2nd row라면
3rd row쌀10kg
4th row쌀10kg
5th row쌀10kg
ValueCountFrequency (%)
쌀10kg 90
26.6%
마스크 33
 
9.8%
기타 24
 
7.1%
빵 16
 
4.7%
10kg 16
 
4.7%
고기류 16
 
4.7%
라면 15
 
4.4%
상품권 12
 
3.6%
선물셋트 12
 
3.6%
손소독제 8
 
2.4%
Other values (48) 96
28.4%
2023-12-13T01:49:56.760804image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 134
 
10.5%
g 131
 
10.3%
k 130
 
10.2%
1 115
 
9.0%
쌀 103
 
8.1%
기 46
 
3.6%
41
 
3.2%
마 33
 
2.6%
스 33
 
2.6%
크 33
 
2.6%
Other values (81) 477
37.4%

Most occurring categories

ValueCountFrequency (%)
Other Letter 654
51.3%
Decimal Number 282
22.1%
Lowercase Letter 263
20.6%
Space Separator 41
 
3.2%
Close Punctuation 13
 
1.0%
Open Punctuation 13
 
1.0%
Other Punctuation 7
 
0.5%
Uppercase Letter 3
 
0.2%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
쌀 103
 
15.7%
기 46
 
7.0%
마 33
 
5.0%
스 33
 
5.0%
크 33
 
5.0%
타 24
 
3.7%
트 21
 
3.2%
품 21
 
3.2%
류 20
 
3.1%
셋 18
 
2.8%
Other values (62) 302
46.2%
Decimal Number
ValueCountFrequency (%)
0 134
47.5%
1 115
40.8%
2 11
 
3.9%
5 7
 
2.5%
3 5
 
1.8%
4 4
 
1.4%
8 3
 
1.1%
6 3
 
1.1%
Lowercase Letter
ValueCountFrequency (%)
g 131
49.8%
k 130
49.4%
l 1
 
0.4%
m 1
 
0.4%
Other Punctuation
ValueCountFrequency (%)
/ 6
85.7%
. 1
 
14.3%
Uppercase Letter
ValueCountFrequency (%)
L 2
66.7%
M 1
33.3%
Space Separator
ValueCountFrequency (%)
41
100.0%
Close Punctuation
ValueCountFrequency (%)
) 13
100.0%
Open Punctuation
ValueCountFrequency (%)
( 13
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 654
51.3%
Common 356
27.9%
Latin 266
20.8%

Most frequent character per script

Hangul
ValueCountFrequency (%)
쌀 103
 
15.7%
기 46
 
7.0%
마 33
 
5.0%
스 33
 
5.0%
크 33
 
5.0%
타 24
 
3.7%
트 21
 
3.2%
품 21
 
3.2%
류 20
 
3.1%
셋 18
 
2.8%
Other values (62) 302
46.2%
Common
ValueCountFrequency (%)
0 134
37.6%
1 115
32.3%
41
 
11.5%
) 13
 
3.7%
( 13
 
3.7%
2 11
 
3.1%
5 7
 
2.0%
/ 6
 
1.7%
3 5
 
1.4%
4 4
 
1.1%
Other values (3) 7
 
2.0%
Latin
ValueCountFrequency (%)
g 131
49.2%
k 130
48.9%
L 2
 
0.8%
l 1
 
0.4%
m 1
 
0.4%
M 1
 
0.4%

Most occurring blocks

ValueCountFrequency (%)
Hangul 654
51.3%
ASCII 622
48.7%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 134
21.5%
g 131
21.1%
k 130
20.9%
1 115
18.5%
41
 
6.6%
) 13
 
2.1%
( 13
 
2.1%
2 11
 
1.8%
5 7
 
1.1%
/ 6
 
1.0%
Other values (9) 21
 
3.4%
Hangul
ValueCountFrequency (%)
쌀 103
 
15.7%
기 46
 
7.0%
마 33
 
5.0%
스 33
 
5.0%
크 33
 
5.0%
타 24
 
3.7%
트 21
 
3.2%
품 21
 
3.2%
류 20
 
3.1%
셋 18
 
2.8%
Other values (62) 302
46.2%

기부현물수량
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct128
Distinct (%)21.8%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1288.6297
Minimum0
Maximum200000
Zeros266
Zeros (%)45.4%
Negative0
Negative (%)0.0%
Memory size5.3 KiB
2023-12-13T01:49:56.948807image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median5.5
Q365.25
95-th percentile2391.5
Maximum200000
Range200000
Interquartile range (IQR)65.25

Descriptive statistics

Standard deviation9660.3121
Coefficient of variation (CV)7.4965773
Kurtosis310.89948
Mean1288.6297
Median Absolute Deviation (MAD)5.5
Skewness15.987542
Sum755137
Variance93321629
MonotonicityNot monotonic
2023-12-13T01:49:57.111388image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 266
45.4%
10 24
 
4.1%
5 19
 
3.2%
50 15
 
2.6%
100 15
 
2.6%
15 14
 
2.4%
200 9
 
1.5%
30 9
 
1.5%
40 9
 
1.5%
20 9
 
1.5%
Other values (118) 197
33.6%
ValueCountFrequency (%)
0 266
45.4%
1 1
 
0.2%
2 1
 
0.2%
3 1
 
0.2%
4 5
 
0.9%
5 19
 
3.2%
6 2
 
0.3%
7 1
 
0.2%
8 3
 
0.5%
9 1
 
0.2%
ValueCountFrequency (%)
200000 1
 
0.2%
50000 3
0.5%
40000 1
 
0.2%
36667 1
 
0.2%
36000 1
 
0.2%
33334 1
 
0.2%
25680 1
 
0.2%
20000 1
 
0.2%
15000 2
0.3%
13334 1
 
0.2%

기부현물환가액
Real number (ℝ)

HIGH CORRELATION  MISSING 

Distinct180
Distinct (%)62.9%
Missing300
Missing (%)51.2%
Infinite0
Infinite (%)0.0%
Mean3089932.2
Minimum21000
Maximum68000000
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size5.3 KiB
2023-12-13T01:49:57.271903image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum21000
5-th percentile87750
Q1441000
median999500
Q33150000
95-th percentile10150000
Maximum68000000
Range67979000
Interquartile range (IQR)2709000

Descriptive statistics

Standard deviation6715710.9
Coefficient of variation (CV)2.1734169
Kurtosis43.913688
Mean3089932.2
Median Absolute Deviation (MAD)817800
Skewness5.8789863
Sum8.8372062 × 108
Variance4.5100774 × 1013
MonotonicityNot monotonic
2023-12-13T01:49:57.469049image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
500000 13
 
2.2%
2000000 9
 
1.5%
1000000 7
 
1.2%
3000000 7
 
1.2%
5000000 7
 
1.2%
200000 6
 
1.0%
1500000 6
 
1.0%
972000 5
 
0.9%
87750 5
 
0.9%
600000 4
 
0.7%
Other values (170) 217
37.0%
(Missing) 300
51.2%
ValueCountFrequency (%)
21000 3
0.5%
27000 2
 
0.3%
30000 1
 
0.2%
40000 1
 
0.2%
45000 4
0.7%
47600 1
 
0.2%
76000 2
 
0.3%
87750 5
0.9%
90000 3
0.5%
92000 1
 
0.2%
ValueCountFrequency (%)
68000000 1
0.2%
50000000 1
0.2%
44000000 1
0.2%
29691660 1
0.2%
24620000 1
0.2%
24318386 1
0.2%
20900000 1
0.2%
20440325 1
0.2%
17000000 1
0.2%
15000000 2
0.3%

부서명
Categorical

HIGH CORRELATION 

Distinct11
Distinct (%)1.9%
Missing0
Missing (%)0.0%
Memory size4.7 KiB
사회복지과
228 
기부식품제공사업장(뱅크)
102 
양주2동
92 
회천2동
85 
양주1동
 
20
Other values (6)
59 

Length

Max length13
Median length5
Mean length6.1484642
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row사회복지과
2nd row사회복지과
3rd row사회복지과
4th row사회복지과
5th row사회복지과

Common Values

ValueCountFrequency (%)
사회복지과 228
38.9%
기부식품제공사업장(뱅크) 102
17.4%
양주2동 92
15.7%
회천2동 85
 
14.5%
양주1동 20
 
3.4%
광적면 17
 
2.9%
기부식품제공사업장(마켓) 17
 
2.9%
은현면 9
 
1.5%
회천4동 7
 
1.2%
남면 5
 
0.9%

Length

2023-12-13T01:49:57.614458image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
사회복지과 228
38.9%
기부식품제공사업장(뱅크 102
17.4%
양주2동 92
15.7%
회천2동 85
 
14.5%
양주1동 20
 
3.4%
광적면 17
 
2.9%
기부식품제공사업장(마켓 17
 
2.9%
은현면 9
 
1.5%
회천4동 7
 
1.2%
남면 5
 
0.9%

담당자
Categorical

HIGH CORRELATION 

Distinct18
Distinct (%)3.1%
Missing0
Missing (%)0.0%
Memory size4.7 KiB
김란희
207 
김평화
85 
신예선
77 
나현철1
56 
강슬기1
46 
Other values (13)
115 

Length

Max length4
Median length3
Mean length3.2030717
Min length3

Unique

Unique2 ?
Unique (%)0.3%

Sample

1st row김란희
2nd row김란희
3rd row김란희
4th row김란희
5th row김란희

Common Values

ValueCountFrequency (%)
김란희 207
35.3%
김평화 85
14.5%
신예선 77
 
13.1%
나현철1 56
 
9.6%
강슬기1 46
 
7.8%
고예은 19
 
3.2%
강슬기2 17
 
2.9%
유정관 17
 
2.9%
최미영 15
 
2.6%
권윤희 14
 
2.4%
Other values (8) 33
 
5.6%

Length

2023-12-13T01:49:57.721966image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
김란희 207
35.3%
김평화 85
14.5%
신예선 77
 
13.1%
나현철1 56
 
9.6%
강슬기1 46
 
7.8%
고예은 19
 
3.2%
강슬기2 17
 
2.9%
유정관 17
 
2.9%
최미영 15
 
2.6%
권윤희 14
 
2.4%
Other values (8) 33
 
5.6%

비고
Text

MISSING 

Distinct54
Distinct (%)38.0%
Missing444
Missing (%)75.8%
Memory size4.7 KiB
2023-12-13T01:49:57.960913image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length31
Median length29
Mean length8.7394366
Min length2

Characters and Unicode

Total characters1241
Distinct characters127
Distinct categories8 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique43 ?
Unique (%)30.3%

Sample

1st row현금기부
2nd row현금기부
3rd row현금기부
4th row현금기부
5th row현금기부
ValueCountFrequency (%)
현금기부 33
 
13.5%
현금 23
 
9.4%
양주2동 18
 
7.4%
연합모금성금기탁 15
 
6.1%
배분 15
 
6.1%
송금 10
 
4.1%
관내저소득 10
 
4.1%
지역밀착형지정기탁금 8
 
3.3%
지원 6
 
2.5%
및 5
 
2.0%
Other values (68) 101
41.4%
2023-12-13T01:49:58.346227image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
금 114
 
9.2%
102
 
8.2%
기 65
 
5.2%
현 58
 
4.7%
가 40
 
3.2%
부 37
 
3.0%
지 34
 
2.7%
2 32
 
2.6%
주 28
 
2.3%
동 27
 
2.2%
Other values (117) 704
56.7%

Most occurring categories

ValueCountFrequency (%)
Other Letter 1001
80.7%
Decimal Number 104
 
8.4%
Space Separator 102
 
8.2%
Open Punctuation 13
 
1.0%
Close Punctuation 13
 
1.0%
Dash Punctuation 5
 
0.4%
Other Punctuation 2
 
0.2%
Math Symbol 1
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
금 114
 
11.4%
기 65
 
6.5%
현 58
 
5.8%
가 40
 
4.0%
부 37
 
3.7%
지 34
 
3.4%
주 28
 
2.8%
동 27
 
2.7%
탁 27
 
2.7%
양 27
 
2.7%
Other values (100) 544
54.3%
Decimal Number
ValueCountFrequency (%)
2 32
30.8%
1 15
14.4%
4 14
13.5%
0 13
12.5%
5 10
 
9.6%
6 8
 
7.7%
9 5
 
4.8%
7 3
 
2.9%
3 2
 
1.9%
8 2
 
1.9%
Other Punctuation
ValueCountFrequency (%)
, 1
50.0%
% 1
50.0%
Space Separator
ValueCountFrequency (%)
102
100.0%
Open Punctuation
ValueCountFrequency (%)
( 13
100.0%
Close Punctuation
ValueCountFrequency (%)
) 13
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 5
100.0%
Math Symbol
ValueCountFrequency (%)
> 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 1001
80.7%
Common 240
 
19.3%

Most frequent character per script

Hangul
ValueCountFrequency (%)
금 114
 
11.4%
기 65
 
6.5%
현 58
 
5.8%
가 40
 
4.0%
부 37
 
3.7%
지 34
 
3.4%
주 28
 
2.8%
동 27
 
2.7%
탁 27
 
2.7%
양 27
 
2.7%
Other values (100) 544
54.3%
Common
ValueCountFrequency (%)
102
42.5%
2 32
 
13.3%
1 15
 
6.2%
4 14
 
5.8%
( 13
 
5.4%
) 13
 
5.4%
0 13
 
5.4%
5 10
 
4.2%
6 8
 
3.3%
9 5
 
2.1%
Other values (7) 15
 
6.2%

Most occurring blocks

ValueCountFrequency (%)
Hangul 1001
80.7%
ASCII 240
 
19.3%

Most frequent character per block

Hangul
ValueCountFrequency (%)
금 114
 
11.4%
기 65
 
6.5%
현 58
 
5.8%
가 40
 
4.0%
부 37
 
3.7%
지 34
 
3.4%
주 28
 
2.8%
동 27
 
2.7%
탁 27
 
2.7%
양 27
 
2.7%
Other values (100) 544
54.3%
ASCII
ValueCountFrequency (%)
102
42.5%
2 32
 
13.3%
1 15
 
6.2%
4 14
 
5.8%
( 13
 
5.4%
) 13
 
5.4%
0 13
 
5.4%
5 10
 
4.2%
6 8
 
3.3%
9 5
 
2.1%
Other values (7) 15
 
6.2%

데이터기준일자
Date

CONSTANT 

Distinct1
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size4.7 KiB
Minimum2022-11-02 00:00:00
Maximum2022-11-02 00:00:00
2023-12-13T01:49:58.458288image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T01:49:58.541941image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=1)

Interactions

2023-12-13T01:49:53.683680image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T01:49:52.334806image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T01:49:52.826089image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T01:49:53.231857image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T01:49:53.789374image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T01:49:52.453637image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T01:49:52.932112image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T01:49:53.332882image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T01:49:53.896560image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T01:49:52.577614image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T01:49:53.032985image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T01:49:53.444312image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T01:49:54.017038image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T01:49:52.701465image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T01:49:53.131619image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T01:49:53.571418image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-13T01:49:58.616024image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
구분기부현금기부현물품목기부현물수량기부현물환가액부서명담당자비고
구분1.0000.0000.8030.2530.1720.7950.8770.951
기부현금0.0001.000NaNNaNNaN0.0000.0000.000
기부현물품목0.803NaN1.0000.0000.6490.8740.9020.981
기부현물수량0.253NaN0.0001.0000.9410.0000.000NaN
기부현물환가액0.172NaN0.6490.9411.0000.0000.000NaN
부서명0.7950.0000.8740.0000.0001.0001.0000.999
담당자0.8770.0000.9020.0000.0001.0001.0001.000
비고0.9510.0000.981NaNNaN0.9991.0001.000
2023-12-13T01:49:58.714365image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
부서명담당자
부서명1.0000.994
담당자0.9941.000
2023-12-13T01:49:58.786783image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
구분기부현금기부현물수량기부현물환가액부서명담당자
구분1.0000.105-0.0190.1880.4970.585
기부현금0.1051.0000.067-0.8110.0000.000
기부현물수량-0.0190.0671.0000.6930.0000.000
기부현물환가액0.188-0.8110.6931.0000.0000.000
부서명0.4970.0000.0000.0001.0000.994
담당자0.5850.0000.0000.0000.9941.000

Missing values

2023-12-13T01:49:54.218610image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-13T01:49:54.754677image/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.
2023-12-13T01:49:54.894967image/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

구분기부일시기부현금기부현물품목기부현물수량기부현물환가액부서명담당자비고데이터기준일자
05862021-04-16<NA>마스크105003150000사회복지과김란희<NA>2022-11-02
15852021-04-01950000라면0<NA>사회복지과김란희<NA>2022-11-02
25842021-04-05<NA>쌀10kg27972000사회복지과김란희<NA>2022-11-02
35832021-03-171350000쌀10kg50<NA>사회복지과김란희<NA>2022-11-02
45822021-03-231000000<NA>0<NA>사회복지과김란희<NA>2022-11-02
55812021-03-233450000쌀10kg100<NA>사회복지과김란희<NA>2022-11-02
65802021-03-155000000<NA>0<NA>사회복지과김란희<NA>2022-11-02
75792021-03-19<NA>마스크105003150000사회복지과김란희<NA>2022-11-02
85782021-03-195000000<NA>0<NA>사회복지과김란희<NA>2022-11-02
95772021-02-15<NA>마스크4000010000000사회복지과김란희<NA>2022-11-02
구분기부일시기부현금기부현물품목기부현물수량기부현물환가액부서명담당자비고데이터기준일자
576102017-09-26<NA>담요2102700000사회복지과최미영<NA>2022-11-02
57792017-09-07<NA>쌀10kg1583000000사회복지과최미영<NA>2022-11-02
57882017-09-15<NA>쌀10kg2003900000사회복지과최미영<NA>2022-11-02
57972017-09-271000000<NA>0<NA>사회복지과최미영<NA>2022-11-02
58062017-09-271000000<NA>0<NA>사회복지과최미영<NA>2022-11-02
58152017-09-07<NA>쌀10kg50975000사회복지과최미영<NA>2022-11-02
58242017-09-07<NA>쌀10kg2003900000사회복지과최미영<NA>2022-11-02
58332017-09-28<NA>쌀10kg1002000000사회복지과최미영<NA>2022-11-02
58422017-09-29<NA>선물셋트30277200백석읍한보슬<NA>2022-11-02
58512017-09-22<NA>쌀10kg10195000양주1동서미현<NA>2022-11-02