Overview

Dataset statistics

Number of variables19
Number of observations44
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory7.4 KiB
Average record size in memory172.9 B

Variable types

Text1
Categorical2
Numeric16

Dataset

Description전라라북도PC보급현황(구분, 단체/개인 수, 수량 등) 통계 데이터입니다.2009년 전북특별자치도 내 중고PC보급 신청한 단체와 개인 인원 수우리기관에서는 더 이상 생성 불가 데이터입니다.
Author전북특별자치도
URLhttps://www.data.go.kr/data/15011591/fileData.do

Alerts

2009년 단체 개인 has constant value ""Constant
2009년 수량 has constant value ""Constant
2010년 단체 개인 is highly overall correlated with 2010년 수량 and 12 other fieldsHigh correlation
2010년 수량 is highly overall correlated with 2010년 단체 개인 and 12 other fieldsHigh correlation
2011년 단체 개인 is highly overall correlated with 2010년 단체 개인 and 14 other fieldsHigh correlation
2011년 수량 is highly overall correlated with 2010년 단체 개인 and 14 other fieldsHigh correlation
2012년 단체 개인 is highly overall correlated with 2010년 단체 개인 and 14 other fieldsHigh correlation
2012년 수량 is highly overall correlated with 2010년 단체 개인 and 14 other fieldsHigh correlation
2013년 단체 개인 is highly overall correlated with 2010년 단체 개인 and 12 other fieldsHigh correlation
2013년 수량 is highly overall correlated with 2010년 단체 개인 and 14 other fieldsHigh correlation
2014년 단체 개인 is highly overall correlated with 2010년 단체 개인 and 12 other fieldsHigh correlation
2014년 수량 is highly overall correlated with 2010년 단체 개인 and 12 other fieldsHigh correlation
2015년 단체 개인 is highly overall correlated with 2010년 단체 개인 and 12 other fieldsHigh correlation
2015년 수량 is highly overall correlated with 2010년 단체 개인 and 14 other fieldsHigh correlation
2016년 단체 개인 is highly overall correlated with 2010년 단체 개인 and 12 other fieldsHigh correlation
2016년 수량 is highly overall correlated with 2010년 단체 개인 and 14 other fieldsHigh correlation
2017년 단체 개인 is highly overall correlated with 2011년 단체 개인 and 7 other fieldsHigh correlation
2017년 수량 is highly overall correlated with 2011년 단체 개인 and 7 other fieldsHigh correlation
구분 has unique valuesUnique
2010년 단체 개인 has 17 (38.6%) zerosZeros
2010년 수량 has 17 (38.6%) zerosZeros
2011년 단체 개인 has 17 (38.6%) zerosZeros
2011년 수량 has 17 (38.6%) zerosZeros
2012년 단체 개인 has 14 (31.8%) zerosZeros
2012년 수량 has 14 (31.8%) zerosZeros
2013년 단체 개인 has 18 (40.9%) zerosZeros
2013년 수량 has 18 (40.9%) zerosZeros
2014년 단체 개인 has 18 (40.9%) zerosZeros
2014년 수량 has 18 (40.9%) zerosZeros
2015년 단체 개인 has 21 (47.7%) zerosZeros
2015년 수량 has 21 (47.7%) zerosZeros
2016년 단체 개인 has 19 (43.2%) zerosZeros
2016년 수량 has 19 (43.2%) zerosZeros
2017년 단체 개인 has 36 (81.8%) zerosZeros
2017년 수량 has 36 (81.8%) zerosZeros

Reproduction

Analysis started2024-03-14 10:30:02.452167
Analysis finished2024-03-14 10:31:00.136891
Duration57.68 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

구분
Text

UNIQUE 

Distinct44
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size480.0 B
2024-03-14T19:31:00.736660image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length16
Median length13
Mean length6.1363636
Min length2

Characters and Unicode

Total characters270
Distinct characters98
Distinct categories7 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique44 ?
Unique (%)100.0%

Sample

1st row시각장애인
2nd row청각장애인
3rd row지체장애인
4th row기타장애인
5th row기초생활수급자
ValueCountFrequency (%)
기타 3
 
5.8%
시각장애인 1
 
1.9%
경노당 1
 
1.9%
양로원 1
 
1.9%
아동시설 1
 
1.9%
국가유공자 1
 
1.9%
단체 1
 
1.9%
이주여성시설 1
 
1.9%
결혼이민자시설 1
 
1.9%
외국인노동자시설 1
 
1.9%
Other values (40) 40
76.9%
2024-03-14T19:31:01.999347image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
14
 
5.2%
12
 
4.4%
12
 
4.4%
11
 
4.1%
9
 
3.3%
9
 
3.3%
8
 
3.0%
8
 
3.0%
7
 
2.6%
6
 
2.2%
Other values (88) 174
64.4%

Most occurring categories

ValueCountFrequency (%)
Other Letter 250
92.6%
Space Separator 8
 
3.0%
Close Punctuation 3
 
1.1%
Open Punctuation 3
 
1.1%
Uppercase Letter 3
 
1.1%
Decimal Number 2
 
0.7%
Other Punctuation 1
 
0.4%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
14
 
5.6%
12
 
4.8%
12
 
4.8%
11
 
4.4%
9
 
3.6%
9
 
3.6%
8
 
3.2%
7
 
2.8%
6
 
2.4%
6
 
2.4%
Other values (79) 156
62.4%
Uppercase Letter
ValueCountFrequency (%)
N 1
33.3%
G 1
33.3%
O 1
33.3%
Decimal Number
ValueCountFrequency (%)
5 1
50.0%
6 1
50.0%
Space Separator
ValueCountFrequency (%)
8
100.0%
Close Punctuation
ValueCountFrequency (%)
) 3
100.0%
Open Punctuation
ValueCountFrequency (%)
( 3
100.0%
Other Punctuation
ValueCountFrequency (%)
, 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 250
92.6%
Common 17
 
6.3%
Latin 3
 
1.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
14
 
5.6%
12
 
4.8%
12
 
4.8%
11
 
4.4%
9
 
3.6%
9
 
3.6%
8
 
3.2%
7
 
2.8%
6
 
2.4%
6
 
2.4%
Other values (79) 156
62.4%
Common
ValueCountFrequency (%)
8
47.1%
) 3
 
17.6%
( 3
 
17.6%
, 1
 
5.9%
5 1
 
5.9%
6 1
 
5.9%
Latin
ValueCountFrequency (%)
N 1
33.3%
G 1
33.3%
O 1
33.3%

Most occurring blocks

ValueCountFrequency (%)
Hangul 250
92.6%
ASCII 20
 
7.4%

Most frequent character per block

Hangul
ValueCountFrequency (%)
14
 
5.6%
12
 
4.8%
12
 
4.8%
11
 
4.4%
9
 
3.6%
9
 
3.6%
8
 
3.2%
7
 
2.8%
6
 
2.4%
6
 
2.4%
Other values (79) 156
62.4%
ASCII
ValueCountFrequency (%)
8
40.0%
) 3
 
15.0%
( 3
 
15.0%
, 1
 
5.0%
N 1
 
5.0%
G 1
 
5.0%
O 1
 
5.0%
5 1
 
5.0%
6 1
 
5.0%

2009년 단체 개인
Categorical

CONSTANT 

Distinct1
Distinct (%)2.3%
Missing0
Missing (%)0.0%
Memory size480.0 B
0
44 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 44
100.0%

Length

2024-03-14T19:31:02.400115image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-14T19:31:02.714641image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 44
100.0%

2009년 수량
Categorical

CONSTANT 

Distinct1
Distinct (%)2.3%
Missing0
Missing (%)0.0%
Memory size480.0 B
0
44 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 44
100.0%

Length

2024-03-14T19:31:03.040437image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-14T19:31:03.350024image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 44
100.0%

2010년 단체 개인
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct20
Distinct (%)45.5%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean24.272727
Minimum0
Maximum246
Zeros17
Zeros (%)38.6%
Negative0
Negative (%)0.0%
Memory size524.0 B
2024-03-14T19:31:03.660902image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median3
Q319.25
95-th percentile79.55
Maximum246
Range246
Interquartile range (IQR)19.25

Descriptive statistics

Standard deviation53.408197
Coefficient of variation (CV)2.2003377
Kurtosis12.0986
Mean24.272727
Median Absolute Deviation (MAD)3
Skewness3.4100899
Sum1068
Variance2852.4355
MonotonicityNot monotonic
2024-03-14T19:31:04.047364image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=20)
ValueCountFrequency (%)
0 17
38.6%
2 4
 
9.1%
8 3
 
6.8%
4 2
 
4.5%
18 2
 
4.5%
20 2
 
4.5%
30 1
 
2.3%
12 1
 
2.3%
74 1
 
2.3%
36 1
 
2.3%
Other values (10) 10
22.7%
ValueCountFrequency (%)
0 17
38.6%
1 1
 
2.3%
2 4
 
9.1%
4 2
 
4.5%
6 1
 
2.3%
8 3
 
6.8%
10 1
 
2.3%
12 1
 
2.3%
18 2
 
4.5%
19 1
 
2.3%
ValueCountFrequency (%)
246 1
2.3%
241 1
2.3%
80 1
2.3%
77 1
2.3%
75 1
2.3%
74 1
2.3%
45 1
2.3%
36 1
2.3%
30 1
2.3%
20 2
4.5%

2010년 수량
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct23
Distinct (%)52.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean53.5
Minimum0
Maximum352
Zeros17
Zeros (%)38.6%
Negative0
Negative (%)0.0%
Memory size524.0 B
2024-03-14T19:31:04.401032image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median9
Q377.75
95-th percentile240.85
Maximum352
Range352
Interquartile range (IQR)77.75

Descriptive statistics

Standard deviation86.38408
Coefficient of variation (CV)1.6146557
Kurtosis2.919622
Mean53.5
Median Absolute Deviation (MAD)9
Skewness1.8824085
Sum2354
Variance7462.2093
MonotonicityNot monotonic
2024-03-14T19:31:04.788101image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=23)
ValueCountFrequency (%)
0 17
38.6%
6 3
 
6.8%
10 3
 
6.8%
80 2
 
4.5%
88 1
 
2.3%
172 1
 
2.3%
240 1
 
2.3%
18 1
 
2.3%
200 1
 
2.3%
24 1
 
2.3%
Other values (13) 13
29.5%
ValueCountFrequency (%)
0 17
38.6%
1 1
 
2.3%
6 3
 
6.8%
8 1
 
2.3%
10 3
 
6.8%
18 1
 
2.3%
19 1
 
2.3%
20 1
 
2.3%
24 1
 
2.3%
45 1
 
2.3%
ValueCountFrequency (%)
352 1
2.3%
246 1
2.3%
241 1
2.3%
240 1
2.3%
200 1
2.3%
172 1
2.3%
170 1
2.3%
94 1
2.3%
88 1
2.3%
80 2
4.5%

2011년 단체 개인
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct21
Distinct (%)47.7%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean17.886364
Minimum0
Maximum215
Zeros17
Zeros (%)38.6%
Negative0
Negative (%)0.0%
Memory size524.0 B
2024-03-14T19:31:05.165961image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median4.5
Q317.25
95-th percentile70.1
Maximum215
Range215
Interquartile range (IQR)17.25

Descriptive statistics

Standard deviation36.994793
Coefficient of variation (CV)2.0683239
Kurtosis19.038726
Mean17.886364
Median Absolute Deviation (MAD)4.5
Skewness3.9713477
Sum787
Variance1368.6147
MonotonicityNot monotonic
2024-03-14T19:31:05.527964image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=21)
ValueCountFrequency (%)
0 17
38.6%
2 4
 
9.1%
12 3
 
6.8%
39 2
 
4.5%
5 2
 
4.5%
22 1
 
2.3%
10 1
 
2.3%
41 1
 
2.3%
4 1
 
2.3%
74 1
 
2.3%
Other values (11) 11
25.0%
ValueCountFrequency (%)
0 17
38.6%
2 4
 
9.1%
4 1
 
2.3%
5 2
 
4.5%
6 1
 
2.3%
7 1
 
2.3%
8 1
 
2.3%
10 1
 
2.3%
11 1
 
2.3%
12 3
 
6.8%
ValueCountFrequency (%)
215 1
2.3%
95 1
2.3%
74 1
2.3%
48 1
2.3%
47 1
2.3%
41 1
2.3%
39 2
4.5%
30 1
2.3%
22 1
2.3%
21 1
2.3%

2011년 수량
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct23
Distinct (%)52.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean33.113636
Minimum0
Maximum332
Zeros17
Zeros (%)38.6%
Negative0
Negative (%)0.0%
Memory size524.0 B
2024-03-14T19:31:05.869624image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median8.5
Q347.25
95-th percentile129.85
Maximum332
Range332
Interquartile range (IQR)47.25

Descriptive statistics

Standard deviation62.081048
Coefficient of variation (CV)1.874788
Kurtosis13.392833
Mean33.113636
Median Absolute Deviation (MAD)8.5
Skewness3.3967922
Sum1457
Variance3854.0566
MonotonicityNot monotonic
2024-03-14T19:31:06.254289image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=23)
ValueCountFrequency (%)
0 17
38.6%
48 3
 
6.8%
39 2
 
4.5%
5 2
 
4.5%
10 2
 
4.5%
16 1
 
2.3%
136 1
 
2.3%
60 1
 
2.3%
50 1
 
2.3%
44 1
 
2.3%
Other values (13) 13
29.5%
ValueCountFrequency (%)
0 17
38.6%
2 1
 
2.3%
5 2
 
4.5%
6 1
 
2.3%
7 1
 
2.3%
10 2
 
4.5%
11 1
 
2.3%
14 1
 
2.3%
16 1
 
2.3%
21 1
 
2.3%
ValueCountFrequency (%)
332 1
 
2.3%
215 1
 
2.3%
136 1
 
2.3%
95 1
 
2.3%
68 1
 
2.3%
60 1
 
2.3%
57 1
 
2.3%
50 1
 
2.3%
48 3
6.8%
47 1
 
2.3%

2012년 단체 개인
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct20
Distinct (%)45.5%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean20.5
Minimum0
Maximum333
Zeros14
Zeros (%)31.8%
Negative0
Negative (%)0.0%
Memory size524.0 B
2024-03-14T19:31:06.614028image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median3
Q315
95-th percentile55.65
Maximum333
Range333
Interquartile range (IQR)15

Descriptive statistics

Standard deviation57.089689
Coefficient of variation (CV)2.7848629
Kurtosis22.880374
Mean20.5
Median Absolute Deviation (MAD)3
Skewness4.6181678
Sum902
Variance3259.2326
MonotonicityNot monotonic
2024-03-14T19:31:06.997466image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=20)
ValueCountFrequency (%)
0 14
31.8%
1 4
 
9.1%
15 3
 
6.8%
2 3
 
6.8%
4 3
 
6.8%
3 3
 
6.8%
17 1
 
2.3%
13 1
 
2.3%
8 1
 
2.3%
16 1
 
2.3%
Other values (10) 10
22.7%
ValueCountFrequency (%)
0 14
31.8%
1 4
 
9.1%
2 3
 
6.8%
3 3
 
6.8%
4 3
 
6.8%
5 1
 
2.3%
8 1
 
2.3%
13 1
 
2.3%
14 1
 
2.3%
15 3
 
6.8%
ValueCountFrequency (%)
333 1
2.3%
190 1
2.3%
57 1
2.3%
48 1
2.3%
45 1
2.3%
37 1
2.3%
24 1
2.3%
19 1
2.3%
17 1
2.3%
16 1
2.3%

2012년 수량
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct24
Distinct (%)54.5%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean28.068182
Minimum0
Maximum333
Zeros14
Zeros (%)31.8%
Negative0
Negative (%)0.0%
Memory size524.0 B
2024-03-14T19:31:07.369234image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median6.5
Q320.25
95-th percentile150.5
Maximum333
Range333
Interquartile range (IQR)20.25

Descriptive statistics

Standard deviation61.315197
Coefficient of variation (CV)2.184509
Kurtosis15.121024
Mean28.068182
Median Absolute Deviation (MAD)6.5
Skewness3.680417
Sum1235
Variance3759.5534
MonotonicityNot monotonic
2024-03-14T19:31:07.759902image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=24)
ValueCountFrequency (%)
0 14
31.8%
3 2
 
4.5%
14 2
 
4.5%
15 2
 
4.5%
1 2
 
4.5%
12 2
 
4.5%
10 2
 
4.5%
6 2
 
4.5%
19 1
 
2.3%
164 1
 
2.3%
Other values (14) 14
31.8%
ValueCountFrequency (%)
0 14
31.8%
1 2
 
4.5%
2 1
 
2.3%
3 2
 
4.5%
5 1
 
2.3%
6 2
 
4.5%
7 1
 
2.3%
8 1
 
2.3%
10 2
 
4.5%
12 2
 
4.5%
ValueCountFrequency (%)
333 1
2.3%
190 1
2.3%
164 1
2.3%
74 1
2.3%
69 1
2.3%
50 1
2.3%
48 1
2.3%
45 1
2.3%
43 1
2.3%
32 1
2.3%

2013년 단체 개인
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct20
Distinct (%)45.5%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean21.795455
Minimum0
Maximum313
Zeros18
Zeros (%)40.9%
Negative0
Negative (%)0.0%
Memory size524.0 B
2024-03-14T19:31:08.117787image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median1
Q316
95-th percentile106
Maximum313
Range313
Interquartile range (IQR)16

Descriptive statistics

Standard deviation53.861398
Coefficient of variation (CV)2.4712216
Kurtosis20.402143
Mean21.795455
Median Absolute Deviation (MAD)1
Skewness4.1866719
Sum959
Variance2901.0502
MonotonicityNot monotonic
2024-03-14T19:31:08.500910image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=20)
ValueCountFrequency (%)
0 18
40.9%
1 6
 
13.6%
3 2
 
4.5%
2 2
 
4.5%
33 1
 
2.3%
8 1
 
2.3%
12 1
 
2.3%
9 1
 
2.3%
23 1
 
2.3%
27 1
 
2.3%
Other values (10) 10
22.7%
ValueCountFrequency (%)
0 18
40.9%
1 6
 
13.6%
2 2
 
4.5%
3 2
 
4.5%
8 1
 
2.3%
9 1
 
2.3%
12 1
 
2.3%
14 1
 
2.3%
15 1
 
2.3%
19 1
 
2.3%
ValueCountFrequency (%)
313 1
2.3%
134 1
2.3%
109 1
2.3%
89 1
2.3%
55 1
2.3%
42 1
2.3%
41 1
2.3%
33 1
2.3%
27 1
2.3%
23 1
2.3%

2013년 수량
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct22
Distinct (%)50.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean27.022727
Minimum0
Maximum313
Zeros18
Zeros (%)40.9%
Negative0
Negative (%)0.0%
Memory size524.0 B
2024-03-14T19:31:08.865273image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median4
Q333.25
95-th percentile106.75
Maximum313
Range313
Interquartile range (IQR)33.25

Descriptive statistics

Standard deviation55.217325
Coefficient of variation (CV)2.0433661
Kurtosis16.679754
Mean27.022727
Median Absolute Deviation (MAD)4
Skewness3.6726562
Sum1189
Variance3048.953
MonotonicityNot monotonic
2024-03-14T19:31:09.246881image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=22)
ValueCountFrequency (%)
0 18
40.9%
8 2
 
4.5%
3 2
 
4.5%
5 2
 
4.5%
1 2
 
4.5%
6 2
 
4.5%
48 1
 
2.3%
34 1
 
2.3%
30 1
 
2.3%
94 1
 
2.3%
Other values (12) 12
27.3%
ValueCountFrequency (%)
0 18
40.9%
1 2
 
4.5%
3 2
 
4.5%
5 2
 
4.5%
6 2
 
4.5%
8 2
 
4.5%
11 1
 
2.3%
15 1
 
2.3%
19 1
 
2.3%
30 1
 
2.3%
ValueCountFrequency (%)
313 1
2.3%
134 1
2.3%
109 1
2.3%
94 1
2.3%
89 1
2.3%
76 1
2.3%
55 1
2.3%
48 1
2.3%
42 1
2.3%
41 1
2.3%

2014년 단체 개인
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct18
Distinct (%)40.9%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean18.431818
Minimum0
Maximum273
Zeros18
Zeros (%)40.9%
Negative0
Negative (%)0.0%
Memory size524.0 B
2024-03-14T19:31:09.597846image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median1
Q313.5
95-th percentile85.15
Maximum273
Range273
Interquartile range (IQR)13.5

Descriptive statistics

Standard deviation46.39236
Coefficient of variation (CV)2.5169714
Kurtosis21.684692
Mean18.431818
Median Absolute Deviation (MAD)1
Skewness4.3150165
Sum811
Variance2152.2511
MonotonicityNot monotonic
2024-03-14T19:31:09.957018image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=18)
ValueCountFrequency (%)
0 18
40.9%
1 7
 
15.9%
2 3
 
6.8%
21 2
 
4.5%
15 1
 
2.3%
10 1
 
2.3%
7 1
 
2.3%
17 1
 
2.3%
5 1
 
2.3%
13 1
 
2.3%
Other values (8) 8
18.2%
ValueCountFrequency (%)
0 18
40.9%
1 7
 
15.9%
2 3
 
6.8%
5 1
 
2.3%
7 1
 
2.3%
10 1
 
2.3%
12 1
 
2.3%
13 1
 
2.3%
15 1
 
2.3%
17 1
 
2.3%
ValueCountFrequency (%)
273 1
2.3%
113 1
2.3%
91 1
2.3%
52 1
2.3%
51 1
2.3%
50 1
2.3%
47 1
2.3%
21 2
4.5%
17 1
2.3%
15 1
2.3%

2014년 수량
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct21
Distinct (%)47.7%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean21.454545
Minimum0
Maximum273
Zeros18
Zeros (%)40.9%
Negative0
Negative (%)0.0%
Memory size524.0 B
2024-03-14T19:31:10.304120image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median2.5
Q322.5
95-th percentile86.65
Maximum273
Range273
Interquartile range (IQR)22.5

Descriptive statistics

Standard deviation46.678243
Coefficient of variation (CV)2.1756808
Kurtosis19.916729
Mean21.454545
Median Absolute Deviation (MAD)2.5
Skewness4.0584385
Sum944
Variance2178.8584
MonotonicityNot monotonic
2024-03-14T19:31:10.669089image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=21)
ValueCountFrequency (%)
0 18
40.9%
3 4
 
9.1%
2 2
 
4.5%
1 2
 
4.5%
6 2
 
4.5%
27 1
 
2.3%
18 1
 
2.3%
31 1
 
2.3%
14 1
 
2.3%
62 1
 
2.3%
Other values (11) 11
25.0%
ValueCountFrequency (%)
0 18
40.9%
1 2
 
4.5%
2 2
 
4.5%
3 4
 
9.1%
6 2
 
4.5%
12 1
 
2.3%
14 1
 
2.3%
15 1
 
2.3%
18 1
 
2.3%
21 1
 
2.3%
ValueCountFrequency (%)
273 1
2.3%
113 1
2.3%
91 1
2.3%
62 1
2.3%
52 1
2.3%
51 1
2.3%
50 1
2.3%
47 1
2.3%
37 1
2.3%
31 1
2.3%

2015년 단체 개인
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct17
Distinct (%)38.6%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean17.636364
Minimum0
Maximum292
Zeros21
Zeros (%)47.7%
Negative0
Negative (%)0.0%
Memory size524.0 B
2024-03-14T19:31:11.024711image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median1
Q314.25
95-th percentile74.9
Maximum292
Range292
Interquartile range (IQR)14.25

Descriptive statistics

Standard deviation49.072841
Coefficient of variation (CV)2.7824807
Kurtosis23.812608
Mean17.636364
Median Absolute Deviation (MAD)1
Skewness4.6066249
Sum776
Variance2408.1438
MonotonicityNot monotonic
2024-03-14T19:31:11.400429image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=17)
ValueCountFrequency (%)
0 21
47.7%
1 5
 
11.4%
2 3
 
6.8%
24 2
 
4.5%
31 1
 
2.3%
15 1
 
2.3%
10 1
 
2.3%
9 1
 
2.3%
14 1
 
2.3%
18 1
 
2.3%
Other values (7) 7
 
15.9%
ValueCountFrequency (%)
0 21
47.7%
1 5
 
11.4%
2 3
 
6.8%
7 1
 
2.3%
9 1
 
2.3%
10 1
 
2.3%
14 1
 
2.3%
15 1
 
2.3%
16 1
 
2.3%
18 1
 
2.3%
ValueCountFrequency (%)
292 1
2.3%
133 1
2.3%
77 1
2.3%
63 1
2.3%
32 1
2.3%
31 1
2.3%
24 2
4.5%
18 1
2.3%
16 1
2.3%
15 1
2.3%

2015년 수량
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct20
Distinct (%)45.5%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean22.409091
Minimum0
Maximum292
Zeros21
Zeros (%)47.7%
Negative0
Negative (%)0.0%
Memory size524.0 B
2024-03-14T19:31:11.762944image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median1
Q325.75
95-th percentile77.85
Maximum292
Range292
Interquartile range (IQR)25.75

Descriptive statistics

Standard deviation50.446526
Coefficient of variation (CV)2.2511634
Kurtosis19.335885
Mean22.409091
Median Absolute Deviation (MAD)1
Skewness4.0149285
Sum986
Variance2544.852
MonotonicityNot monotonic
2024-03-14T19:31:12.146772image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=20)
ValueCountFrequency (%)
0 21
47.7%
6 2
 
4.5%
3 2
 
4.5%
63 2
 
4.5%
1 2
 
4.5%
18 1
 
2.3%
54 1
 
2.3%
35 1
 
2.3%
34 1
 
2.3%
78 1
 
2.3%
Other values (10) 10
22.7%
ValueCountFrequency (%)
0 21
47.7%
1 2
 
4.5%
3 2
 
4.5%
4 1
 
2.3%
5 1
 
2.3%
6 2
 
4.5%
7 1
 
2.3%
16 1
 
2.3%
18 1
 
2.3%
24 1
 
2.3%
ValueCountFrequency (%)
292 1
2.3%
133 1
2.3%
78 1
2.3%
77 1
2.3%
63 2
4.5%
54 1
2.3%
35 1
2.3%
34 1
2.3%
32 1
2.3%
31 1
2.3%

2016년 단체 개인
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct16
Distinct (%)36.4%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean13.409091
Minimum0
Maximum215
Zeros19
Zeros (%)43.2%
Negative0
Negative (%)0.0%
Memory size524.0 B
2024-03-14T19:31:12.511407image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median1
Q310.25
95-th percentile57.25
Maximum215
Range215
Interquartile range (IQR)10.25

Descriptive statistics

Standard deviation36.277559
Coefficient of variation (CV)2.7054451
Kurtosis23.281921
Mean13.409091
Median Absolute Deviation (MAD)1
Skewness4.554656
Sum590
Variance1316.0613
MonotonicityNot monotonic
2024-03-14T19:31:13.067120image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=16)
ValueCountFrequency (%)
0 19
43.2%
1 7
 
15.9%
4 3
 
6.8%
22 2
 
4.5%
11 2
 
4.5%
26 1
 
2.3%
2 1
 
2.3%
5 1
 
2.3%
8 1
 
2.3%
14 1
 
2.3%
Other values (6) 6
 
13.6%
ValueCountFrequency (%)
0 19
43.2%
1 7
 
15.9%
2 1
 
2.3%
4 3
 
6.8%
5 1
 
2.3%
8 1
 
2.3%
10 1
 
2.3%
11 2
 
4.5%
14 1
 
2.3%
22 2
 
4.5%
ValueCountFrequency (%)
215 1
2.3%
101 1
2.3%
61 1
2.3%
36 1
2.3%
27 1
2.3%
26 1
2.3%
22 2
4.5%
14 1
2.3%
11 2
4.5%
10 1
2.3%

2016년 수량
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct20
Distinct (%)45.5%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean15.977273
Minimum0
Maximum215
Zeros19
Zeros (%)43.2%
Negative0
Negative (%)0.0%
Memory size524.0 B
2024-03-14T19:31:13.432909image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median2.5
Q314.25
95-th percentile58.6
Maximum215
Range215
Interquartile range (IQR)14.25

Descriptive statistics

Standard deviation36.510902
Coefficient of variation (CV)2.2851774
Kurtosis21.274545
Mean15.977273
Median Absolute Deviation (MAD)2.5
Skewness4.2725395
Sum703
Variance1333.046
MonotonicityNot monotonic
2024-03-14T19:31:13.799945image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=20)
ValueCountFrequency (%)
0 19
43.2%
3 4
 
9.1%
10 2
 
4.5%
2 2
 
4.5%
11 2
 
4.5%
26 1
 
2.3%
45 1
 
2.3%
4 1
 
2.3%
18 1
 
2.3%
12 1
 
2.3%
Other values (10) 10
22.7%
ValueCountFrequency (%)
0 19
43.2%
1 1
 
2.3%
2 2
 
4.5%
3 4
 
9.1%
4 1
 
2.3%
10 2
 
4.5%
11 2
 
4.5%
12 1
 
2.3%
13 1
 
2.3%
18 1
 
2.3%
ValueCountFrequency (%)
215 1
2.3%
101 1
2.3%
61 1
2.3%
45 1
2.3%
36 1
2.3%
34 1
2.3%
30 1
2.3%
27 1
2.3%
26 1
2.3%
22 1
2.3%

2017년 단체 개인
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct7
Distinct (%)15.9%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean6.2272727
Minimum0
Maximum247
Zeros36
Zeros (%)81.8%
Negative0
Negative (%)0.0%
Memory size524.0 B
2024-03-14T19:31:14.136356image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile5
Maximum247
Range247
Interquartile range (IQR)0

Descriptive statistics

Standard deviation37.18831
Coefficient of variation (CV)5.9718454
Kurtosis43.765371
Mean6.2272727
Median Absolute Deviation (MAD)0
Skewness6.607789
Sum274
Variance1382.9704
MonotonicityNot monotonic
2024-03-14T19:31:14.492464image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=7)
ValueCountFrequency (%)
0 36
81.8%
1 2
 
4.5%
5 2
 
4.5%
2 1
 
2.3%
247 1
 
2.3%
10 1
 
2.3%
3 1
 
2.3%
ValueCountFrequency (%)
0 36
81.8%
1 2
 
4.5%
2 1
 
2.3%
3 1
 
2.3%
5 2
 
4.5%
10 1
 
2.3%
247 1
 
2.3%
ValueCountFrequency (%)
247 1
 
2.3%
10 1
 
2.3%
5 2
 
4.5%
3 1
 
2.3%
2 1
 
2.3%
1 2
 
4.5%
0 36
81.8%

2017년 수량
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct9
Distinct (%)20.5%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean8.5681818
Minimum0
Maximum247
Zeros36
Zeros (%)81.8%
Negative0
Negative (%)0.0%
Memory size524.0 B
2024-03-14T19:31:14.822852image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile24.25
Maximum247
Range247
Interquartile range (IQR)0

Descriptive statistics

Standard deviation38.142571
Coefficient of variation (CV)4.4516528
Kurtosis37.688095
Mean8.5681818
Median Absolute Deviation (MAD)0
Skewness5.9969618
Sum377
Variance1454.8557
MonotonicityNot monotonic
2024-03-14T19:31:15.176726image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=9)
ValueCountFrequency (%)
0 36
81.8%
2 1
 
2.3%
247 1
 
2.3%
1 1
 
2.3%
5 1
 
2.3%
19 1
 
2.3%
58 1
 
2.3%
20 1
 
2.3%
25 1
 
2.3%
ValueCountFrequency (%)
0 36
81.8%
1 1
 
2.3%
2 1
 
2.3%
5 1
 
2.3%
19 1
 
2.3%
20 1
 
2.3%
25 1
 
2.3%
58 1
 
2.3%
247 1
 
2.3%
ValueCountFrequency (%)
247 1
 
2.3%
58 1
 
2.3%
25 1
 
2.3%
20 1
 
2.3%
19 1
 
2.3%
5 1
 
2.3%
2 1
 
2.3%
1 1
 
2.3%
0 36
81.8%

Interactions

2024-03-14T19:30:54.973596image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T19:30:03.251486image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T19:30:06.455278image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T19:30:10.454757image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T19:30:14.306678image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T19:30:18.218421image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T19:30:21.302045image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T19:30:25.097389image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T19:30:29.039517image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T19:30:31.606698image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T19:30:34.269336image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T19:30:36.682252image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T19:30:39.419939image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T19:30:43.346030image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T19:30:47.351510image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T19:30:51.134631image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T19:30:55.209039image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T19:30:03.440550image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T19:30:06.702502image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T19:30:10.893393image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T19:30:14.548903image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T19:30:18.458028image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T19:30:21.445681image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T19:30:25.341677image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T19:30:29.299294image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T19:30:31.783724image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T19:30:34.405638image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T19:30:36.824848image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T19:30:39.660297image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T19:30:43.803879image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T19:30:47.586154image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T19:30:51.372384image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T19:30:55.462839image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
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2024-03-14T19:30:31.277122image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T19:30:33.918840image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T19:30:36.351712image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T19:30:38.934761image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T19:30:42.860811image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T19:30:46.882149image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T19:30:50.668854image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T19:30:54.501482image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T19:30:58.765996image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T19:30:06.215719image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T19:30:10.208311image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T19:30:14.070295image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T19:30:17.977608image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T19:30:21.160677image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T19:30:24.856745image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T19:30:28.795340image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T19:30:31.419212image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T19:30:34.130382image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T19:30:36.545721image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T19:30:39.175944image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T19:30:43.102201image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T19:30:47.119114image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T19:30:50.903670image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T19:30:54.736313image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-03-14T19:31:15.437551image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
구분2010년 단체 개인2010년 수량2011년 단체 개인2011년 수량2012년 단체 개인2012년 수량2013년 단체 개인2013년 수량2014년 단체 개인2014년 수량2015년 단체 개인2015년 수량2016년 단체 개인2016년 수량2017년 단체 개인2017년 수량
구분1.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.000
2010년 단체 개인1.0001.0000.8630.8960.8010.8430.7400.8270.9080.6880.8480.6620.7140.6790.7140.8690.821
2010년 수량1.0000.8631.0000.7520.7780.5120.7100.4690.6860.4730.7190.4820.6600.4560.5810.4280.598
2011년 단체 개인1.0000.8960.7521.0000.9750.9310.9690.9750.9760.8800.9950.8360.8600.8600.8571.0000.729
2011년 수량1.0000.8010.7780.9751.0000.8100.9670.8730.9590.7300.9670.7190.8160.7020.8071.0000.919
2012년 단체 개인1.0000.8430.5120.9310.8101.0000.9960.9490.8790.7330.8690.8010.7730.8670.8011.0000.871
2012년 수량1.0000.7400.7100.9690.9670.9961.0000.9320.9490.6850.9520.7540.7730.8190.8001.0000.905
2013년 단체 개인1.0000.8270.4690.9750.8730.9490.9321.0000.9870.9680.9840.9120.8420.9370.8831.0000.672
2013년 수량1.0000.9080.6860.9760.9590.8790.9490.9871.0000.8960.9850.8630.9030.8740.9241.0000.837
2014년 단체 개인1.0000.6880.4730.8800.7300.7330.6850.9680.8961.0000.9560.9900.9690.9690.9601.0000.592
2014년 수량1.0000.8480.7190.9950.9670.8690.9520.9840.9850.9561.0000.8650.8860.8370.8711.0000.719
2015년 단체 개인1.0000.6620.4820.8360.7190.8010.7540.9120.8630.9900.8651.0000.9850.9860.9741.0000.591
2015년 수량1.0000.7140.6600.8600.8160.7730.7730.8420.9030.9690.8860.9851.0000.9750.9881.0000.709
2016년 단체 개인1.0000.6790.4560.8600.7020.8670.8190.9370.8740.9690.8370.9860.9751.0000.9951.0000.593
2016년 수량1.0000.7140.5810.8570.8070.8010.8000.8830.9240.9600.8710.9740.9880.9951.0001.0000.728
2017년 단체 개인1.0000.8690.4281.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.000
2017년 수량1.0000.8210.5980.7290.9190.8710.9050.6720.8370.5920.7190.5910.7090.5930.7281.0001.000
2024-03-14T19:31:15.797204image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2010년 단체 개인2010년 수량2011년 단체 개인2011년 수량2012년 단체 개인2012년 수량2013년 단체 개인2013년 수량2014년 단체 개인2014년 수량2015년 단체 개인2015년 수량2016년 단체 개인2016년 수량2017년 단체 개인2017년 수량
2010년 단체 개인1.0000.9380.8010.7450.7480.7390.7670.7760.8390.8450.7120.7300.6740.6820.4230.423
2010년 수량0.9381.0000.6920.7180.6610.6850.6070.6450.6960.7310.5860.6420.5360.5770.4130.417
2011년 단체 개인0.8010.6921.0000.9490.7990.7740.7600.7660.7740.7710.7210.7320.6790.6920.5040.501
2011년 수량0.7450.7180.9491.0000.7500.7640.6420.6850.6540.6760.6320.6860.5970.6430.5650.563
2012년 단체 개인0.7480.6610.7990.7501.0000.9860.7910.7900.7220.7250.6500.6700.6530.6620.5190.519
2012년 수량0.7390.6850.7740.7640.9861.0000.7520.7720.6840.6970.6430.6850.6320.6590.5680.569
2013년 단체 개인0.7670.6070.7600.6420.7910.7521.0000.9830.9170.8980.8540.8420.8500.8340.4630.460
2013년 수량0.7760.6450.7660.6850.7900.7720.9831.0000.9010.8990.8440.8650.8350.8470.5460.545
2014년 단체 개인0.8390.6960.7740.6540.7220.6840.9170.9011.0000.9890.8250.8060.8260.8080.3890.382
2014년 수량0.8450.7310.7710.6760.7250.6970.8980.8990.9891.0000.7900.7950.8020.8010.4290.423
2015년 단체 개인0.7120.5860.7210.6320.6500.6430.8540.8440.8250.7901.0000.9770.8910.8770.4690.465
2015년 수량0.7300.6420.7320.6860.6700.6850.8420.8650.8060.7950.9771.0000.8700.8860.5650.563
2016년 단체 개인0.6740.5360.6790.5970.6530.6320.8500.8350.8260.8020.8910.8701.0000.9840.4670.464
2016년 수량0.6820.5770.6920.6430.6620.6590.8340.8470.8080.8010.8770.8860.9841.0000.5390.540
2017년 단체 개인0.4230.4130.5040.5650.5190.5680.4630.5460.3890.4290.4690.5650.4670.5391.0000.999
2017년 수량0.4230.4170.5010.5630.5190.5690.4600.5450.3820.4230.4650.5630.4640.5400.9991.000

Missing values

2024-03-14T19:30:59.142745image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-03-14T19:30:59.841651image/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

구분2009년 단체 개인2009년 수량2010년 단체 개인2010년 수량2011년 단체 개인2011년 수량2012년 단체 개인2012년 수량2013년 단체 개인2013년 수량2014년 단체 개인2014년 수량2015년 단체 개인2015년 수량2016년 단체 개인2016년 수량2017년 단체 개인2017년 수량
0시각장애인00757516161919333315151818262600
1청각장애인0020201111221515121277111100
2지체장애인002412419595454513413411311313313310110100
3기타장애인0077774848190190898951517777616122
4기초생활수급자00246246215215333333313313273273292292215215247247
5차상위계층00191939394848555547476363111111
6소년소녀가장001122000011110000
7국가유공자(상이등급판정자)001010551414191921211616101000
8다문화가정00454539391515424252523232222200
9노인(65세이상)008080474724241091099191000000
구분2009년 단체 개인2009년 수량2010년 단체 개인2010년 수량2011년 단체 개인2011년 수량2012년 단체 개인2012년 수량2013년 단체 개인2013년 수량2014년 단체 개인2014년 수량2015년 단체 개인2015년 수량2016년 단체 개인2016년 수량2017년 단체 개인2017년 수량
34농어촌지역 시설(마을회관 등)000022508100000000000
35사회시민단체00122401248131326261300
36대안학교0021000001513131300
37기타단체00301721260133212481027156351800
38마을회관000000351113002400
39정부기관000000000000000000
40NGO000000000000000000
41재외공관000000000000000000
42학교시설000000000000000000
43기타000000000000000000