Overview

Dataset statistics

Number of variables18
Number of observations45
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory7.2 KiB
Average record size in memory162.9 B

Variable types

Categorical2
Numeric16

Dataset

Description광주광역시 CCTV통합관제센터에서 관제 및 운영중인 CCTV의 현황에 대한 정보로 연도별, 자치구별, 유형별로 구분하여 설치개소, 설치대수 등을 제공하는 데이터입니다.
Author광주광역시
URLhttps://www.data.go.kr/data/15112056/fileData.do

Alerts

총 수량(개소) is highly overall correlated with 총 수량(대수) and 11 other fieldsHigh correlation
총 수량(대수) is highly overall correlated with 총 수량(개소) and 11 other fieldsHigh correlation
2016년(개소) is highly overall correlated with 총 수량(개소) and 9 other fieldsHigh correlation
2016년(대수) is highly overall correlated with 총 수량(개소) and 7 other fieldsHigh correlation
2017년(개소) is highly overall correlated with 2017년(대수)High correlation
2017년(대수) is highly overall correlated with 총 수량(개소) and 7 other fieldsHigh correlation
2018년(개소) is highly overall correlated with 총 수량(개소) and 3 other fieldsHigh correlation
2018년(대수) is highly overall correlated with 총 수량(개소) and 9 other fieldsHigh correlation
2019년(개소) is highly overall correlated with 총 수량(개소) and 9 other fieldsHigh correlation
2019년(대수) is highly overall correlated with 총 수량(개소) and 10 other fieldsHigh correlation
2020년(개소) is highly overall correlated with 총 수량(개소) and 8 other fieldsHigh correlation
2020년(대수) is highly overall correlated with 총 수량(개소) and 10 other fieldsHigh correlation
2021년(개소) is highly overall correlated with 총 수량(대수) and 3 other fieldsHigh correlation
2021년(대수) is highly overall correlated with 총 수량(개소) and 6 other fieldsHigh correlation
2022년(개소) is highly overall correlated with 2021년(개소) and 2 other fieldsHigh correlation
2022년(대수) is highly overall correlated with 총 수량(개소) and 11 other fieldsHigh correlation
2016년(개소) has 15 (33.3%) zerosZeros
2016년(대수) has 15 (33.3%) zerosZeros
2017년(개소) has 31 (68.9%) zerosZeros
2017년(대수) has 23 (51.1%) zerosZeros
2018년(개소) has 19 (42.2%) zerosZeros
2018년(대수) has 17 (37.8%) zerosZeros
2019년(개소) has 19 (42.2%) zerosZeros
2019년(대수) has 19 (42.2%) zerosZeros
2020년(개소) has 14 (31.1%) zerosZeros
2020년(대수) has 14 (31.1%) zerosZeros
2021년(개소) has 28 (62.2%) zerosZeros
2021년(대수) has 17 (37.8%) zerosZeros
2022년(개소) has 24 (53.3%) zerosZeros
2022년(대수) has 16 (35.6%) zerosZeros

Reproduction

Analysis started2023-12-12 06:46:35.013387
Analysis finished2023-12-12 06:47:03.137053
Duration28.12 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

구분
Categorical

Distinct5
Distinct (%)11.1%
Missing0
Missing (%)0.0%
Memory size492.0 B
광주광역시 동구
광주광역시 서구
광주광역시 남구
광주광역시 북구
광주광역시 광산구

Length

Max length9
Median length8
Mean length8.2
Min length8

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row광주광역시 동구
2nd row광주광역시 동구
3rd row광주광역시 동구
4th row광주광역시 동구
5th row광주광역시 동구

Common Values

ValueCountFrequency (%)
광주광역시 동구 9
20.0%
광주광역시 서구 9
20.0%
광주광역시 남구 9
20.0%
광주광역시 북구 9
20.0%
광주광역시 광산구 9
20.0%

Length

2023-12-12T15:47:03.201498image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T15:47:03.337084image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
광주광역시 45
50.0%
동구 9
 
10.0%
서구 9
 
10.0%
남구 9
 
10.0%
북구 9
 
10.0%
광산구 9
 
10.0%

용도
Categorical

Distinct9
Distinct (%)20.0%
Missing0
Missing (%)0.0%
Memory size492.0 B
방범
어린이보호(계)
어린이보호(보호구역)
어린이보호(도시공원)
초등학교 교내
Other values (4)
20 

Length

Max length11
Median length8
Mean length7.5555556
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row방범
2nd row어린이보호(계)
3rd row어린이보호(보호구역)
4th row어린이보호(도시공원)
5th row초등학교 교내

Common Values

ValueCountFrequency (%)
방범 5
11.1%
어린이보호(계) 5
11.1%
어린이보호(보호구역) 5
11.1%
어린이보호(도시공원) 5
11.1%
초등학교 교내 5
11.1%
차량번호인식 5
11.1%
재난(산불, 하천) 5
11.1%
교통정보수집 5
11.1%
주정차단속연계 5
11.1%

Length

2023-12-12T15:47:03.470834image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T15:47:03.621131image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
방범 5
9.1%
어린이보호(계 5
9.1%
어린이보호(보호구역 5
9.1%
어린이보호(도시공원 5
9.1%
초등학교 5
9.1%
교내 5
9.1%
차량번호인식 5
9.1%
재난(산불 5
9.1%
하천 5
9.1%
교통정보수집 5
9.1%

총 수량(개소)
Real number (ℝ)

HIGH CORRELATION 

Distinct39
Distinct (%)86.7%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean105.04444
Minimum4
Maximum476
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size537.0 B
2023-12-12T15:47:03.782781image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum4
5-th percentile6.2
Q116
median50
Q3140
95-th percentile345.4
Maximum476
Range472
Interquartile range (IQR)124

Descriptive statistics

Standard deviation119.97518
Coefficient of variation (CV)1.1421373
Kurtosis1.6464536
Mean105.04444
Median Absolute Deviation (MAD)43
Skewness1.5229473
Sum4727
Variance14394.043
MonotonicityNot monotonic
2023-12-12T15:47:03.919238image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=39)
ValueCountFrequency (%)
31 2
 
4.4%
11 2
 
4.4%
7 2
 
4.4%
16 2
 
4.4%
15 2
 
4.4%
4 2
 
4.4%
246 1
 
2.2%
476 1
 
2.2%
275 1
 
2.2%
140 1
 
2.2%
Other values (29) 29
64.4%
ValueCountFrequency (%)
4 2
4.4%
6 1
2.2%
7 2
4.4%
10 1
2.2%
11 2
4.4%
12 1
2.2%
15 2
4.4%
16 2
4.4%
20 1
2.2%
23 1
2.2%
ValueCountFrequency (%)
476 1
2.2%
410 1
2.2%
349 1
2.2%
331 1
2.2%
320 1
2.2%
275 1
2.2%
246 1
2.2%
225 1
2.2%
177 1
2.2%
154 1
2.2%

총 수량(대수)
Real number (ℝ)

HIGH CORRELATION 

Distinct41
Distinct (%)91.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean277.24444
Minimum4
Maximum1350
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size537.0 B
2023-12-12T15:47:04.046803image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum4
5-th percentile7.2
Q128
median187
Q3351
95-th percentile946.2
Maximum1350
Range1346
Interquartile range (IQR)323

Descriptive statistics

Standard deviation329.98024
Coefficient of variation (CV)1.1902141
Kurtosis2.229968
Mean277.24444
Median Absolute Deviation (MAD)162
Skewness1.6308855
Sum12476
Variance108886.96
MonotonicityNot monotonic
2023-12-12T15:47:04.183558image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=41)
ValueCountFrequency (%)
108 2
 
4.4%
28 2
 
4.4%
335 2
 
4.4%
351 2
 
4.4%
678 1
 
2.2%
9 1
 
2.2%
12 1
 
2.2%
187 1
 
2.2%
1350 1
 
2.2%
686 1
 
2.2%
Other values (31) 31
68.9%
ValueCountFrequency (%)
4 1
2.2%
6 1
2.2%
7 1
2.2%
8 1
2.2%
9 1
2.2%
12 1
2.2%
16 1
2.2%
18 1
2.2%
20 1
2.2%
25 1
2.2%
ValueCountFrequency (%)
1350 1
2.2%
1141 1
2.2%
960 1
2.2%
891 1
2.2%
844 1
2.2%
686 1
2.2%
678 1
2.2%
532 1
2.2%
463 1
2.2%
381 1
2.2%

2016년(개소)
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct30
Distinct (%)66.7%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean56.955556
Minimum0
Maximum241
Zeros15
Zeros (%)33.3%
Negative0
Negative (%)0.0%
Memory size537.0 B
2023-12-12T15:47:04.330004image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median30
Q3105
95-th percentile201.6
Maximum241
Range241
Interquartile range (IQR)105

Descriptive statistics

Standard deviation69.848198
Coefficient of variation (CV)1.2263632
Kurtosis0.41870182
Mean56.955556
Median Absolute Deviation (MAD)30
Skewness1.1729494
Sum2563
Variance4878.7707
MonotonicityNot monotonic
2023-12-12T15:47:04.434669image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=30)
ValueCountFrequency (%)
0 15
33.3%
7 2
 
4.4%
114 1
 
2.2%
22 1
 
2.2%
46 1
 
2.2%
105 1
 
2.2%
121 1
 
2.2%
226 1
 
2.2%
200 1
 
2.2%
6 1
 
2.2%
Other values (20) 20
44.4%
ValueCountFrequency (%)
0 15
33.3%
3 1
 
2.2%
4 1
 
2.2%
6 1
 
2.2%
7 2
 
4.4%
10 1
 
2.2%
22 1
 
2.2%
30 1
 
2.2%
32 1
 
2.2%
42 1
 
2.2%
ValueCountFrequency (%)
241 1
2.2%
226 1
2.2%
202 1
2.2%
200 1
2.2%
164 1
2.2%
155 1
2.2%
122 1
2.2%
121 1
2.2%
114 1
2.2%
113 1
2.2%

2016년(대수)
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct29
Distinct (%)64.4%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean78.311111
Minimum0
Maximum284
Zeros15
Zeros (%)33.3%
Negative0
Negative (%)0.0%
Memory size537.0 B
2023-12-12T15:47:04.554093image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median52
Q3141
95-th percentile242.4
Maximum284
Range284
Interquartile range (IQR)141

Descriptive statistics

Standard deviation86.973042
Coefficient of variation (CV)1.1106092
Kurtosis-0.50734156
Mean78.311111
Median Absolute Deviation (MAD)52
Skewness0.80967158
Sum3524
Variance7564.3101
MonotonicityNot monotonic
2023-12-12T15:47:04.652486image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=29)
ValueCountFrequency (%)
0 15
33.3%
142 2
 
4.4%
7 2
 
4.4%
141 1
 
2.2%
52 1
 
2.2%
184 1
 
2.2%
284 1
 
2.2%
232 1
 
2.2%
6 1
 
2.2%
188 1
 
2.2%
Other values (19) 19
42.2%
ValueCountFrequency (%)
0 15
33.3%
3 1
 
2.2%
4 1
 
2.2%
6 1
 
2.2%
7 2
 
4.4%
39 1
 
2.2%
40 1
 
2.2%
52 1
 
2.2%
55 1
 
2.2%
69 1
 
2.2%
ValueCountFrequency (%)
284 1
2.2%
263 1
2.2%
245 1
2.2%
232 1
2.2%
215 1
2.2%
205 1
2.2%
188 1
2.2%
184 1
2.2%
145 1
2.2%
142 2
4.4%

2017년(개소)
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct8
Distinct (%)17.8%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean3.1333333
Minimum0
Maximum37
Zeros31
Zeros (%)68.9%
Negative0
Negative (%)0.0%
Memory size537.0 B
2023-12-12T15:47:04.743125image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q31
95-th percentile22.8
Maximum37
Range37
Interquartile range (IQR)1

Descriptive statistics

Standard deviation8.622381
Coefficient of variation (CV)2.7518237
Kurtosis8.1735718
Mean3.1333333
Median Absolute Deviation (MAD)0
Skewness2.9935275
Sum141
Variance74.345455
MonotonicityNot monotonic
2023-12-12T15:47:05.116565image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=8)
ValueCountFrequency (%)
0 31
68.9%
1 8
 
17.8%
33 1
 
2.2%
15 1
 
2.2%
22 1
 
2.2%
23 1
 
2.2%
37 1
 
2.2%
3 1
 
2.2%
ValueCountFrequency (%)
0 31
68.9%
1 8
 
17.8%
3 1
 
2.2%
15 1
 
2.2%
22 1
 
2.2%
23 1
 
2.2%
33 1
 
2.2%
37 1
 
2.2%
ValueCountFrequency (%)
37 1
 
2.2%
33 1
 
2.2%
23 1
 
2.2%
22 1
 
2.2%
15 1
 
2.2%
3 1
 
2.2%
1 8
 
17.8%
0 31
68.9%

2017년(대수)
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct12
Distinct (%)26.7%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean7.5555556
Minimum0
Maximum75
Zeros23
Zeros (%)51.1%
Negative0
Negative (%)0.0%
Memory size537.0 B
2023-12-12T15:47:05.234334image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q34
95-th percentile48.4
Maximum75
Range75
Interquartile range (IQR)4

Descriptive statistics

Standard deviation17.612696
Coefficient of variation (CV)2.3310922
Kurtosis7.5244824
Mean7.5555556
Median Absolute Deviation (MAD)0
Skewness2.8764496
Sum340
Variance310.20707
MonotonicityNot monotonic
2023-12-12T15:47:05.361728image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=12)
ValueCountFrequency (%)
0 23
51.1%
4 7
 
15.6%
3 4
 
8.9%
1 2
 
4.4%
8 2
 
4.4%
68 1
 
2.2%
33 1
 
2.2%
46 1
 
2.2%
49 1
 
2.2%
2 1
 
2.2%
Other values (2) 2
 
4.4%
ValueCountFrequency (%)
0 23
51.1%
1 2
 
4.4%
2 1
 
2.2%
3 4
 
8.9%
4 7
 
15.6%
8 2
 
4.4%
9 1
 
2.2%
33 1
 
2.2%
46 1
 
2.2%
49 1
 
2.2%
ValueCountFrequency (%)
75 1
 
2.2%
68 1
 
2.2%
49 1
 
2.2%
46 1
 
2.2%
33 1
 
2.2%
9 1
 
2.2%
8 2
 
4.4%
4 7
15.6%
3 4
8.9%
2 1
 
2.2%

2018년(개소)
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct21
Distinct (%)46.7%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean7.4
Minimum0
Maximum42
Zeros19
Zeros (%)42.2%
Negative0
Negative (%)0.0%
Memory size537.0 B
2023-12-12T15:47:05.500724image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median1
Q313
95-th percentile26.8
Maximum42
Range42
Interquartile range (IQR)13

Descriptive statistics

Standard deviation10.859432
Coefficient of variation (CV)1.4674909
Kurtosis2.4246218
Mean7.4
Median Absolute Deviation (MAD)1
Skewness1.6777372
Sum333
Variance117.92727
MonotonicityNot monotonic
2023-12-12T15:47:05.622394image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=21)
ValueCountFrequency (%)
0 19
42.2%
1 4
 
8.9%
2 3
 
6.7%
17 2
 
4.4%
40 1
 
2.2%
14 1
 
2.2%
27 1
 
2.2%
3 1
 
2.2%
4 1
 
2.2%
16 1
 
2.2%
Other values (11) 11
24.4%
ValueCountFrequency (%)
0 19
42.2%
1 4
 
8.9%
2 3
 
6.7%
3 1
 
2.2%
4 1
 
2.2%
5 1
 
2.2%
7 1
 
2.2%
9 1
 
2.2%
10 1
 
2.2%
12 1
 
2.2%
ValueCountFrequency (%)
42 1
2.2%
40 1
2.2%
27 1
2.2%
26 1
2.2%
22 1
2.2%
20 1
2.2%
19 1
2.2%
17 2
4.4%
16 1
2.2%
14 1
2.2%

2018년(대수)
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct22
Distinct (%)48.9%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean21.688889
Minimum0
Maximum153
Zeros17
Zeros (%)37.8%
Negative0
Negative (%)0.0%
Memory size537.0 B
2023-12-12T15:47:05.758196image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median3
Q326
95-th percentile103.8
Maximum153
Range153
Interquartile range (IQR)26

Descriptive statistics

Standard deviation37.372098
Coefficient of variation (CV)1.7230988
Kurtosis3.8641293
Mean21.688889
Median Absolute Deviation (MAD)3
Skewness2.115838
Sum976
Variance1396.6737
MonotonicityNot monotonic
2023-12-12T15:47:05.960198image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=22)
ValueCountFrequency (%)
0 17
37.8%
3 5
 
11.1%
10 2
 
4.4%
4 2
 
4.4%
1 2
 
4.4%
42 1
 
2.2%
27 1
 
2.2%
53 1
 
2.2%
63 1
 
2.2%
105 1
 
2.2%
Other values (12) 12
26.7%
ValueCountFrequency (%)
0 17
37.8%
1 2
 
4.4%
3 5
 
11.1%
4 2
 
4.4%
7 1
 
2.2%
9 1
 
2.2%
10 2
 
4.4%
16 1
 
2.2%
19 1
 
2.2%
20 1
 
2.2%
ValueCountFrequency (%)
153 1
2.2%
125 1
2.2%
105 1
2.2%
99 1
2.2%
93 1
2.2%
63 1
2.2%
53 1
2.2%
42 1
2.2%
38 1
2.2%
36 1
2.2%

2019년(개소)
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct21
Distinct (%)46.7%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean10.755556
Minimum0
Maximum69
Zeros19
Zeros (%)42.2%
Negative0
Negative (%)0.0%
Memory size537.0 B
2023-12-12T15:47:06.109740image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median1
Q314
95-th percentile42.2
Maximum69
Range69
Interquartile range (IQR)14

Descriptive statistics

Standard deviation17.10018
Coefficient of variation (CV)1.5898928
Kurtosis2.7104419
Mean10.755556
Median Absolute Deviation (MAD)1
Skewness1.8064357
Sum484
Variance292.41616
MonotonicityNot monotonic
2023-12-12T15:47:06.248149image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=21)
ValueCountFrequency (%)
0 19
42.2%
1 4
 
8.9%
3 3
 
6.7%
6 2
 
4.4%
69 1
 
2.2%
43 1
 
2.2%
14 1
 
2.2%
57 1
 
2.2%
39 1
 
2.2%
26 1
 
2.2%
Other values (11) 11
24.4%
ValueCountFrequency (%)
0 19
42.2%
1 4
 
8.9%
2 1
 
2.2%
3 3
 
6.7%
5 1
 
2.2%
6 2
 
4.4%
8 1
 
2.2%
9 1
 
2.2%
12 1
 
2.2%
14 1
 
2.2%
ValueCountFrequency (%)
69 1
2.2%
57 1
2.2%
43 1
2.2%
39 1
2.2%
37 1
2.2%
36 1
2.2%
35 1
2.2%
26 1
2.2%
25 1
2.2%
22 1
2.2%

2019년(대수)
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct25
Distinct (%)55.6%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean44.244444
Minimum0
Maximum344
Zeros19
Zeros (%)42.2%
Negative0
Negative (%)0.0%
Memory size537.0 B
2023-12-12T15:47:06.436218image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median4
Q357
95-th percentile169.8
Maximum344
Range344
Interquartile range (IQR)57

Descriptive statistics

Standard deviation72.528413
Coefficient of variation (CV)1.639266
Kurtosis5.7198997
Mean44.244444
Median Absolute Deviation (MAD)4
Skewness2.2093302
Sum1991
Variance5260.3707
MonotonicityNot monotonic
2023-12-12T15:47:06.578421image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=25)
ValueCountFrequency (%)
0 19
42.2%
13 2
 
4.4%
3 2
 
4.4%
119 1
 
2.2%
7 1
 
2.2%
19 1
 
2.2%
147 1
 
2.2%
57 1
 
2.2%
204 1
 
2.2%
175 1
 
2.2%
Other values (15) 15
33.3%
ValueCountFrequency (%)
0 19
42.2%
2 1
 
2.2%
3 2
 
4.4%
4 1
 
2.2%
7 1
 
2.2%
13 2
 
4.4%
17 1
 
2.2%
19 1
 
2.2%
27 1
 
2.2%
30 1
 
2.2%
ValueCountFrequency (%)
344 1
2.2%
204 1
2.2%
175 1
2.2%
149 1
2.2%
147 1
2.2%
126 1
2.2%
124 1
2.2%
119 1
2.2%
118 1
2.2%
93 1
2.2%

2020년(개소)
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct18
Distinct (%)40.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean9.5555556
Minimum0
Maximum63
Zeros14
Zeros (%)31.1%
Negative0
Negative (%)0.0%
Memory size537.0 B
2023-12-12T15:47:06.728887image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median3
Q38
95-th percentile58.2
Maximum63
Range63
Interquartile range (IQR)8

Descriptive statistics

Standard deviation16.592106
Coefficient of variation (CV)1.7363832
Kurtosis5.344364
Mean9.5555556
Median Absolute Deviation (MAD)3
Skewness2.4655247
Sum430
Variance275.29798
MonotonicityNot monotonic
2023-12-12T15:47:06.861503image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=18)
ValueCountFrequency (%)
0 14
31.1%
1 4
 
8.9%
6 4
 
8.9%
3 3
 
6.7%
7 2
 
4.4%
2 2
 
4.4%
4 2
 
4.4%
11 2
 
4.4%
5 2
 
4.4%
22 2
 
4.4%
Other values (8) 8
17.8%
ValueCountFrequency (%)
0 14
31.1%
1 4
 
8.9%
2 2
 
4.4%
3 3
 
6.7%
4 2
 
4.4%
5 2
 
4.4%
6 4
 
8.9%
7 2
 
4.4%
8 1
 
2.2%
11 2
 
4.4%
ValueCountFrequency (%)
63 1
2.2%
62 1
2.2%
61 1
2.2%
47 1
2.2%
22 2
4.4%
19 1
2.2%
16 1
2.2%
15 1
2.2%
11 2
4.4%
8 1
2.2%

2020년(대수)
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct28
Distinct (%)62.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean34.4
Minimum0
Maximum194
Zeros14
Zeros (%)31.1%
Negative0
Negative (%)0.0%
Memory size537.0 B
2023-12-12T15:47:06.996005image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median8
Q347
95-th percentile168.8
Maximum194
Range194
Interquartile range (IQR)47

Descriptive statistics

Standard deviation53.270493
Coefficient of variation (CV)1.5485609
Kurtosis2.5755994
Mean34.4
Median Absolute Deviation (MAD)8
Skewness1.8554271
Sum1548
Variance2837.7455
MonotonicityNot monotonic
2023-12-12T15:47:07.151756image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=28)
ValueCountFrequency (%)
0 14
31.1%
1 3
 
6.7%
14 2
 
4.4%
22 2
 
4.4%
63 1
 
2.2%
2 1
 
2.2%
13 1
 
2.2%
67 1
 
2.2%
47 1
 
2.2%
114 1
 
2.2%
Other values (18) 18
40.0%
ValueCountFrequency (%)
0 14
31.1%
1 3
 
6.7%
2 1
 
2.2%
3 1
 
2.2%
5 1
 
2.2%
6 1
 
2.2%
7 1
 
2.2%
8 1
 
2.2%
13 1
 
2.2%
14 2
 
4.4%
ValueCountFrequency (%)
194 1
2.2%
182 1
2.2%
177 1
2.2%
136 1
2.2%
127 1
2.2%
114 1
2.2%
70 1
2.2%
67 1
2.2%
66 1
2.2%
63 1
2.2%

2021년(개소)
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct13
Distinct (%)28.9%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean10.755556
Minimum0
Maximum110
Zeros28
Zeros (%)62.2%
Negative0
Negative (%)0.0%
Memory size537.0 B
2023-12-12T15:47:07.280497image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q36
95-th percentile70.8
Maximum110
Range110
Interquartile range (IQR)6

Descriptive statistics

Standard deviation24.207583
Coefficient of variation (CV)2.250705
Kurtosis7.7208217
Mean10.755556
Median Absolute Deviation (MAD)0
Skewness2.7984659
Sum484
Variance586.00707
MonotonicityNot monotonic
2023-12-12T15:47:07.389986image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=13)
ValueCountFrequency (%)
0 28
62.2%
1 4
 
8.9%
17 2
 
4.4%
6 2
 
4.4%
33 1
 
2.2%
14 1
 
2.2%
110 1
 
2.2%
31 1
 
2.2%
54 1
 
2.2%
25 1
 
2.2%
Other values (3) 3
 
6.7%
ValueCountFrequency (%)
0 28
62.2%
1 4
 
8.9%
6 2
 
4.4%
10 1
 
2.2%
14 1
 
2.2%
17 2
 
4.4%
25 1
 
2.2%
31 1
 
2.2%
33 1
 
2.2%
54 1
 
2.2%
ValueCountFrequency (%)
110 1
2.2%
82 1
2.2%
75 1
2.2%
54 1
2.2%
33 1
2.2%
31 1
2.2%
25 1
2.2%
17 2
4.4%
14 1
2.2%
10 1
2.2%

2021년(대수)
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct26
Distinct (%)57.8%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean40.266667
Minimum0
Maximum356
Zeros17
Zeros (%)37.8%
Negative0
Negative (%)0.0%
Memory size537.0 B
2023-12-12T15:47:07.542478image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median6
Q346
95-th percentile204.6
Maximum356
Range356
Interquartile range (IQR)46

Descriptive statistics

Standard deviation75.254538
Coefficient of variation (CV)1.8689041
Kurtosis7.6014966
Mean40.266667
Median Absolute Deviation (MAD)6
Skewness2.6715836
Sum1812
Variance5663.2455
MonotonicityNot monotonic
2023-12-12T15:47:07.727450image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=26)
ValueCountFrequency (%)
0 17
37.8%
6 2
 
4.4%
1 2
 
4.4%
2 2
 
4.4%
14 1
 
2.2%
254 1
 
2.2%
40 1
 
2.2%
46 1
 
2.2%
60 1
 
2.2%
213 1
 
2.2%
Other values (16) 16
35.6%
ValueCountFrequency (%)
0 17
37.8%
1 2
 
4.4%
2 2
 
4.4%
5 1
 
2.2%
6 2
 
4.4%
10 1
 
2.2%
11 1
 
2.2%
12 1
 
2.2%
13 1
 
2.2%
14 1
 
2.2%
ValueCountFrequency (%)
356 1
2.2%
254 1
2.2%
213 1
2.2%
171 1
2.2%
108 1
2.2%
101 1
2.2%
99 1
2.2%
79 1
2.2%
73 1
2.2%
60 1
2.2%

2022년(개소)
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct13
Distinct (%)28.9%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean6.4888889
Minimum0
Maximum45
Zeros24
Zeros (%)53.3%
Negative0
Negative (%)0.0%
Memory size537.0 B
2023-12-12T15:47:07.835927image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q33
95-th percentile38.2
Maximum45
Range45
Interquartile range (IQR)3

Descriptive statistics

Standard deviation12.909866
Coefficient of variation (CV)1.9895342
Kurtosis2.7598273
Mean6.4888889
Median Absolute Deviation (MAD)0
Skewness2.0578147
Sum292
Variance166.66465
MonotonicityNot monotonic
2023-12-12T15:47:07.971698image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=13)
ValueCountFrequency (%)
0 24
53.3%
3 5
 
11.1%
2 4
 
8.9%
1 2
 
4.4%
7 2
 
4.4%
23 1
 
2.2%
41 1
 
2.2%
33 1
 
2.2%
6 1
 
2.2%
35 1
 
2.2%
Other values (3) 3
 
6.7%
ValueCountFrequency (%)
0 24
53.3%
1 2
 
4.4%
2 4
 
8.9%
3 5
 
11.1%
6 1
 
2.2%
7 2
 
4.4%
23 1
 
2.2%
31 1
 
2.2%
33 1
 
2.2%
35 1
 
2.2%
ValueCountFrequency (%)
45 1
 
2.2%
41 1
 
2.2%
39 1
 
2.2%
35 1
 
2.2%
33 1
 
2.2%
31 1
 
2.2%
23 1
 
2.2%
7 2
 
4.4%
6 1
 
2.2%
3 5
11.1%

2022년(대수)
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct25
Distinct (%)55.6%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean50.777778
Minimum0
Maximum323
Zeros16
Zeros (%)35.6%
Negative0
Negative (%)0.0%
Memory size537.0 B
2023-12-12T15:47:08.086177image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median15
Q368
95-th percentile225.6
Maximum323
Range323
Interquartile range (IQR)68

Descriptive statistics

Standard deviation80.31271
Coefficient of variation (CV)1.5816507
Kurtosis3.9939484
Mean50.777778
Median Absolute Deviation (MAD)15
Skewness2.0882022
Sum2285
Variance6450.1313
MonotonicityNot monotonic
2023-12-12T15:47:08.206741image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=25)
ValueCountFrequency (%)
0 16
35.6%
3 3
 
6.7%
56 3
 
6.7%
16 2
 
4.4%
148 1
 
2.2%
36 1
 
2.2%
83 1
 
2.2%
68 1
 
2.2%
124 1
 
2.2%
300 1
 
2.2%
Other values (15) 15
33.3%
ValueCountFrequency (%)
0 16
35.6%
1 1
 
2.2%
3 3
 
6.7%
4 1
 
2.2%
9 1
 
2.2%
15 1
 
2.2%
16 2
 
4.4%
29 1
 
2.2%
31 1
 
2.2%
33 1
 
2.2%
ValueCountFrequency (%)
323 1
2.2%
300 1
2.2%
226 1
2.2%
224 1
2.2%
148 1
2.2%
138 1
2.2%
124 1
2.2%
92 1
2.2%
85 1
2.2%
83 1
2.2%

Interactions

2023-12-12T15:47:01.139130image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:46:35.799771image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:46:37.421435image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:46:39.223534image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:46:40.693647image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:46:42.423775image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:46:44.010381image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:46:45.808543image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:46:47.814653image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:46:49.600724image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:46:51.279875image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:46:52.942045image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:46:54.813516image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:46:56.551848image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:46:57.896009image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:46:59.425184image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:47:01.237298image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:46:35.883802image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:46:37.516863image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:46:39.322495image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:46:41.058978image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:46:42.498043image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:46:44.092723image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:46:45.884655image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:46:47.925168image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:46:49.693537image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:46:51.370726image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:46:53.070474image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:46:54.943665image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:46:56.628749image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:46:57.965454image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:46:59.513049image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:47:01.360613image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:46:35.992695image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:46:37.626255image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:46:39.409712image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:46:41.149278image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:46:42.582679image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:46:44.200164image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:46:45.977122image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:46:48.038871image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:46:49.802919image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:46:51.477727image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:46:53.197735image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:46:55.048989image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:46:56.718850image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:46:58.036919image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:46:59.604600image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:47:01.443876image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:46:36.095437image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:46:37.733819image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:46:39.503953image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
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2023-12-12T15:46:54.698980image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:46:56.467392image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:46:57.828248image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:46:59.317995image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:47:01.030864image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-12T15:47:08.344694image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
구분용도총 수량(개소)총 수량(대수)2016년(개소)2016년(대수)2017년(개소)2017년(대수)2018년(개소)2018년(대수)2019년(개소)2019년(대수)2020년(개소)2020년(대수)2021년(개소)2021년(대수)2022년(개소)2022년(대수)
구분1.0000.0000.5240.0000.0000.2860.0000.5000.3580.0000.0000.0970.0000.0000.3180.2920.0000.000
용도0.0001.0000.4650.6140.6760.6750.3190.5520.6320.6250.5370.5600.6870.6270.3530.4030.5150.689
총 수량(개소)0.5240.4651.0000.9800.8480.8810.9470.9650.8250.8620.8700.8950.7890.8470.5680.7410.8090.864
총 수량(대수)0.0000.6140.9801.0000.9150.7630.9740.8600.8040.8270.8460.8750.8280.8340.4750.7160.7790.845
2016년(개소)0.0000.6760.8480.9151.0000.8670.8070.7300.7040.7900.8220.8160.7120.8390.2430.4150.4950.779
2016년(대수)0.2860.6750.8810.7630.8671.0000.6870.7420.6490.7240.7540.7220.7870.8500.0000.0790.1700.782
2017년(개소)0.0000.3190.9470.9740.8070.6871.0000.9030.8170.8730.7900.8050.9460.7830.4220.6860.8650.809
2017년(대수)0.5000.5520.9650.8600.7300.7420.9031.0000.6880.8320.7460.7010.8090.8370.5160.5050.8170.754
2018년(개소)0.3580.6320.8250.8040.7040.6490.8170.6881.0000.9530.8240.7040.6090.7760.0000.6070.6380.707
2018년(대수)0.0000.6250.8620.8270.7900.7240.8730.8320.9531.0000.9160.7280.7600.9320.0000.0000.7550.864
2019년(개소)0.0000.5370.8700.8460.8220.7540.7900.7460.8240.9161.0000.9070.7690.9380.0000.7960.5710.807
2019년(대수)0.0970.5600.8950.8750.8160.7220.8050.7010.7040.7280.9071.0000.6770.7600.4640.7050.7860.879
2020년(개소)0.0000.6870.7890.8280.7120.7870.9460.8090.6090.7600.7690.6771.0000.8970.2740.4360.7120.738
2020년(대수)0.0000.6270.8470.8340.8390.8500.7830.8370.7760.9320.9380.7600.8971.0000.0000.1960.6080.871
2021년(개소)0.3180.3530.5680.4750.2430.0000.4220.5160.0000.0000.0000.4640.2740.0001.0000.9610.9700.676
2021년(대수)0.2920.4030.7410.7160.4150.0790.6860.5050.6070.0000.7960.7050.4360.1960.9611.0000.8610.725
2022년(개소)0.0000.5150.8090.7790.4950.1700.8650.8170.6380.7550.5710.7860.7120.6080.9700.8611.0000.894
2022년(대수)0.0000.6890.8640.8450.7790.7820.8090.7540.7070.8640.8070.8790.7380.8710.6760.7250.8941.000
2023-12-12T15:47:08.586803image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
구분용도
구분1.0000.000
용도0.0001.000
2023-12-12T15:47:08.725376image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
총 수량(개소)총 수량(대수)2016년(개소)2016년(대수)2017년(개소)2017년(대수)2018년(개소)2018년(대수)2019년(개소)2019년(대수)2020년(개소)2020년(대수)2021년(개소)2021년(대수)2022년(개소)2022년(대수)구분용도
총 수량(개소)1.0000.9760.7700.7060.2970.5770.5130.6120.7280.7370.5850.7000.4610.7690.4860.8480.2180.217
총 수량(대수)0.9761.0000.7520.7130.3850.6380.4240.5320.6890.7000.5190.6370.5060.7770.4820.8230.0000.227
2016년(개소)0.7700.7521.0000.9600.3840.6980.4360.5690.8320.8390.5800.7380.0390.3860.2340.6710.0000.266
2016년(대수)0.7060.7130.9601.0000.4350.7300.3540.4810.7130.7160.4540.606-0.0120.2760.1290.5400.0910.377
2017년(개소)0.2970.3850.3840.4351.0000.8150.2460.2780.1990.2270.2690.2600.1960.0850.2760.2320.0000.143
2017년(대수)0.5770.6380.6980.7300.8151.0000.4680.5460.4830.5050.4810.5430.1350.2130.1860.4800.2010.335
2018년(개소)0.5130.4240.4360.3540.2460.4681.0000.9630.4720.4920.6770.670-0.0280.0910.0920.4140.2110.364
2018년(대수)0.6120.5320.5690.4810.2780.5460.9631.0000.5860.6100.7730.779-0.0310.1670.1510.5380.0000.358
2019년(개소)0.7280.6890.8320.7130.1990.4830.4720.5861.0000.9970.7570.8690.2010.5040.3790.7650.0000.288
2019년(대수)0.7370.7000.8390.7160.2270.5050.4920.6100.9971.0000.7710.8800.2030.5050.3930.7810.0180.323
2020년(개소)0.5850.5190.5800.4540.2690.4810.6770.7730.7570.7711.0000.9430.1260.3310.3920.6640.0000.404
2020년(대수)0.7000.6370.7380.6060.2600.5430.6700.7790.8690.8800.9431.0000.1090.4210.3580.7570.0000.359
2021년(개소)0.4610.5060.039-0.0120.1960.135-0.028-0.0310.2010.2030.1260.1091.0000.8110.6800.5160.1960.177
2021년(대수)0.7690.7770.3860.2760.0850.2130.0910.1670.5040.5050.3310.4210.8111.0000.6980.7880.1660.196
2022년(개소)0.4860.4820.2340.1290.2760.1860.0920.1510.3790.3930.3920.3580.6800.6981.0000.7090.0000.288
2022년(대수)0.8480.8230.6710.5400.2320.4800.4140.5380.7650.7810.6640.7570.5160.7880.7091.0000.0000.440
구분0.2180.0000.0000.0910.0000.2010.2110.0000.0000.0180.0000.0000.1960.1660.0000.0001.0000.000
용도0.2170.2270.2660.3770.1430.3350.3640.3580.2880.3230.4040.3590.1770.1960.2880.4400.0001.000

Missing values

2023-12-12T15:47:02.829049image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-12T15:47:03.049399image/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

구분용도총 수량(개소)총 수량(대수)2016년(개소)2016년(대수)2017년(개소)2017년(대수)2018년(개소)2018년(대수)2019년(개소)2019년(대수)2020년(개소)2020년(대수)2021년(개소)2021년(대수)2022년(개소)2022년(대수)
0광주광역시 동구방범24667811414133684012520119156311423148
1광주광역시 동구어린이보호(계)8920174940001840622013131
2광주광역시 동구어린이보호(보호구역)50108425500015273801016
3광주광역시 동구어린이보호(도시공원)399332390000313314012115
4광주광역시 동구초등학교 교내11441040140000000000
5광주광역시 동구차량번호인식6800000012111233
6광주광역시 동구재난(산불, 하천)7777000000000000
7광주광역시 동구교통정보수집161600009900770000
8광주광역시 동구주정차단속연계361080000000000339939
9광주광역시 서구방범320891164215153317932211847127147941226
구분용도총 수량(개소)총 수량(대수)2016년(개소)2016년(대수)2017년(개소)2017년(대수)2018년(개소)2018년(대수)2019년(개소)2019년(대수)2020년(개소)2020년(대수)2021년(개소)2021년(대수)2022년(개소)2022년(대수)
35광주광역시 북구주정차단속연계11435100000000007521339138
36광주광역시 광산구방범41011412002323775171053917562194106045300
37광주광역시 광산구어린이보호(계)33184422628409206357204221146460124
38광주광역시 광산구어린이보호(보호구역)154381121142081653145734706068
39광주광역시 광산구어린이보호(도시공원)17746310514201410431471967640056
40광주광역시 광산구초등학교 교내4718846184140000000000
41광주광역시 광산구차량번호인식1528003813008131123
42광주광역시 광산구재난(산불, 하천)1629770033619000000
43광주광역시 광산구교통정보수집28280000272700110000
44광주광역시 광산구주정차단속연계1133370000000000822543183