Overview

Dataset statistics

Number of variables15
Number of observations32
Missing cells5
Missing cells (%)1.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory4.2 KiB
Average record size in memory135.1 B

Variable types

Categorical4
Numeric11

Dataset

Description대구광역시 달서구 내 구립도서관 도서정보 집계현황에 대한 내용 및 정보가 담겨있음. (도서관명, 구분, 총류, 철학, 종교, 사회, 순수, 기술, 예술, 언어, 문학, 역사, 소계)
URLhttps://www.data.go.kr/data/3055353/fileData.do

Alerts

담당부서 has constant value ""Constant
기준일자 has constant value ""Constant
0(총류) is highly overall correlated with 100(철학) and 9 other fieldsHigh correlation
100(철학) is highly overall correlated with 0(총류) and 9 other fieldsHigh correlation
200(종교) is highly overall correlated with 0(총류) and 9 other fieldsHigh correlation
300(사회) is highly overall correlated with 0(총류) and 9 other fieldsHigh correlation
400(순수) is highly overall correlated with 0(총류) and 9 other fieldsHigh correlation
500(기술) is highly overall correlated with 0(총류) and 9 other fieldsHigh correlation
600(예술) is highly overall correlated with 0(총류) and 9 other fieldsHigh correlation
700(언어) is highly overall correlated with 0(총류) and 9 other fieldsHigh correlation
800(문학) is highly overall correlated with 0(총류) and 9 other fieldsHigh correlation
900(역사) is highly overall correlated with 0(총류) and 9 other fieldsHigh correlation
소계 is highly overall correlated with 0(총류) and 9 other fieldsHigh correlation
0(총류) has 1 (3.1%) missing valuesMissing
400(순수) has 1 (3.1%) missing valuesMissing
500(기술) has 1 (3.1%) missing valuesMissing
600(예술) has 1 (3.1%) missing valuesMissing
700(언어) has 1 (3.1%) missing valuesMissing
소계 has unique valuesUnique
0(총류) has 2 (6.2%) zerosZeros
100(철학) has 2 (6.2%) zerosZeros
200(종교) has 2 (6.2%) zerosZeros
300(사회) has 1 (3.1%) zerosZeros
400(순수) has 1 (3.1%) zerosZeros
500(기술) has 1 (3.1%) zerosZeros
600(예술) has 1 (3.1%) zerosZeros
700(언어) has 3 (9.4%) zerosZeros
800(문학) has 2 (6.2%) zerosZeros
900(역사) has 1 (3.1%) zerosZeros

Reproduction

Analysis started2023-12-12 15:13:33.900392
Analysis finished2023-12-12 15:13:46.569119
Duration12.67 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

도서관명
Categorical

Distinct6
Distinct (%)18.8%
Missing0
Missing (%)0.0%
Memory size388.0 B
성서도서관
6 
달서가족문화
6 
달서영어
6 
도원도서관
5 
본리도서관
5 

Length

Max length6
Median length5
Mean length5
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
성서도서관 6
18.8%
달서가족문화 6
18.8%
달서영어 6
18.8%
도원도서관 5
15.6%
본리도서관 5
15.6%
달서어린이 4
12.5%

Length

2023-12-13T00:13:46.648212image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T00:13:46.762318image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
성서도서관 6
18.8%
달서가족문화 6
18.8%
달서영어 6
18.8%
도원도서관 5
15.6%
본리도서관 5
15.6%
달서어린이 4
12.5%

구분
Categorical

Distinct12
Distinct (%)37.5%
Missing0
Missing (%)0.0%
Memory size388.0 B
일반도서
5 
아동도서
5 
참고도서
5 
점자도서
5 
큰글자도서
4 
Other values (7)
8 

Length

Max length6
Median length4
Mean length4.3125
Min length4

Unique

Unique6 ?
Unique (%)18.8%

Sample

1st row일반도서
2nd row아동도서
3rd row참고도서
4th row점자도서
5th row큰글자도서

Common Values

ValueCountFrequency (%)
일반도서 5
15.6%
아동도서 5
15.6%
참고도서 5
15.6%
점자도서 5
15.6%
큰글자도서 4
12.5%
유아도서 2
 
6.2%
초등도서 1
 
3.1%
학부모도서 1
 
3.1%
대활자본도서 1
 
3.1%
다문화도서 1
 
3.1%
Other values (2) 2
 
6.2%

Length

2023-12-13T00:13:46.954126image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
일반도서 5
15.6%
아동도서 5
15.6%
참고도서 5
15.6%
점자도서 5
15.6%
큰글자도서 4
12.5%
유아도서 2
 
6.2%
초등도서 1
 
3.1%
학부모도서 1
 
3.1%
대활자본도서 1
 
3.1%
다문화도서 1
 
3.1%
Other values (2) 2
 
6.2%

0(총류)
Real number (ℝ)

HIGH CORRELATION  MISSING  ZEROS 

Distinct27
Distinct (%)87.1%
Missing1
Missing (%)3.1%
Infinite0
Infinite (%)0.0%
Mean632.3871
Minimum0
Maximum2543
Zeros2
Zeros (%)6.2%
Negative0
Negative (%)0.0%
Memory size420.0 B
2023-12-13T00:13:47.425993image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0.5
Q16.5
median109
Q31311
95-th percentile2252.5
Maximum2543
Range2543
Interquartile range (IQR)1304.5

Descriptive statistics

Standard deviation882.20801
Coefficient of variation (CV)1.3950443
Kurtosis-0.4376207
Mean632.3871
Median Absolute Deviation (MAD)108
Skewness1.1189306
Sum19604
Variance778290.98
MonotonicityNot monotonic
2023-12-13T00:13:47.541190image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=27)
ValueCountFrequency (%)
1 3
 
9.4%
2233 2
 
6.2%
0 2
 
6.2%
2272 1
 
3.1%
74 1
 
3.1%
4 1
 
3.1%
412 1
 
3.1%
109 1
 
3.1%
49 1
 
3.1%
19 1
 
3.1%
Other values (17) 17
53.1%
ValueCountFrequency (%)
0 2
6.2%
1 3
9.4%
3 1
 
3.1%
4 1
 
3.1%
5 1
 
3.1%
8 1
 
3.1%
19 1
 
3.1%
28 1
 
3.1%
32 1
 
3.1%
49 1
 
3.1%
ValueCountFrequency (%)
2543 1
3.1%
2272 1
3.1%
2233 2
6.2%
1938 1
3.1%
1883 1
3.1%
1611 1
3.1%
1511 1
3.1%
1111 1
3.1%
496 1
3.1%
443 1
3.1%

100(철학)
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct27
Distinct (%)84.4%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean703.96875
Minimum0
Maximum4468
Zeros2
Zeros (%)6.2%
Negative0
Negative (%)0.0%
Memory size420.0 B
2023-12-13T00:13:47.673505image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile1.1
Q18.5
median68
Q3861.25
95-th percentile4234.95
Maximum4468
Range4468
Interquartile range (IQR)852.75

Descriptive statistics

Standard deviation1300.5893
Coefficient of variation (CV)1.84751
Kurtosis3.8359764
Mean703.96875
Median Absolute Deviation (MAD)65
Skewness2.1793938
Sum22527
Variance1691532.5
MonotonicityNot monotonic
2023-12-13T00:13:47.777286image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=27)
ValueCountFrequency (%)
3 2
 
6.2%
0 2
 
6.2%
82 2
 
6.2%
2 2
 
6.2%
11 2
 
6.2%
4241 1
 
3.1%
72 1
 
3.1%
9 1
 
3.1%
27 1
 
3.1%
115 1
 
3.1%
Other values (17) 17
53.1%
ValueCountFrequency (%)
0 2
6.2%
2 2
6.2%
3 2
6.2%
4 1
3.1%
7 1
3.1%
9 1
3.1%
11 2
6.2%
19 1
3.1%
21 1
3.1%
27 1
3.1%
ValueCountFrequency (%)
4468 1
3.1%
4241 1
3.1%
4230 1
3.1%
2261 1
3.1%
1387 1
3.1%
1253 1
3.1%
1197 1
3.1%
1105 1
3.1%
780 1
3.1%
701 1
3.1%

200(종교)
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct26
Distinct (%)81.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean331
Minimum0
Maximum1918
Zeros2
Zeros (%)6.2%
Negative0
Negative (%)0.0%
Memory size420.0 B
2023-12-13T00:13:47.915088image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0.55
Q15
median17
Q3512.25
95-th percentile1653.8
Maximum1918
Range1918
Interquartile range (IQR)507.25

Descriptive statistics

Standard deviation552.59785
Coefficient of variation (CV)1.6694799
Kurtosis2.6212398
Mean331
Median Absolute Deviation (MAD)17
Skewness1.8673375
Sum10592
Variance305364.39
MonotonicityNot monotonic
2023-12-13T00:13:48.054754image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=26)
ValueCountFrequency (%)
15 3
 
9.4%
0 2
 
6.2%
2 2
 
6.2%
1 2
 
6.2%
5 2
 
6.2%
572 1
 
3.1%
105 1
 
3.1%
37 1
 
3.1%
195 1
 
3.1%
8 1
 
3.1%
Other values (16) 16
50.0%
ValueCountFrequency (%)
0 2
6.2%
1 2
6.2%
2 2
6.2%
3 1
 
3.1%
5 2
6.2%
8 1
 
3.1%
9 1
 
3.1%
10 1
 
3.1%
11 1
 
3.1%
15 3
9.4%
ValueCountFrequency (%)
1918 1
3.1%
1832 1
3.1%
1508 1
3.1%
1175 1
3.1%
793 1
3.1%
747 1
3.1%
572 1
3.1%
543 1
3.1%
502 1
3.1%
399 1
3.1%

300(사회)
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct30
Distinct (%)93.8%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2244.6562
Minimum0
Maximum9881
Zeros1
Zeros (%)3.1%
Negative0
Negative (%)0.0%
Memory size420.0 B
2023-12-13T00:13:48.184065image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile7.95
Q135.75
median137.5
Q35189.25
95-th percentile8684.7
Maximum9881
Range9881
Interquartile range (IQR)5153.5

Descriptive statistics

Standard deviation3242.9459
Coefficient of variation (CV)1.4447405
Kurtosis-0.20335414
Mean2244.6562
Median Absolute Deviation (MAD)136
Skewness1.147701
Sum71829
Variance10516698
MonotonicityNot monotonic
2023-12-13T00:13:48.303941image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=30)
ValueCountFrequency (%)
58 2
 
6.2%
24 2
 
6.2%
9881 1
 
3.1%
126 1
 
3.1%
0 1
 
3.1%
43 1
 
3.1%
3 1
 
3.1%
454 1
 
3.1%
1024 1
 
3.1%
502 1
 
3.1%
Other values (20) 20
62.5%
ValueCountFrequency (%)
0 1
3.1%
3 1
3.1%
12 1
3.1%
15 1
3.1%
17 1
3.1%
24 2
6.2%
35 1
3.1%
36 1
3.1%
41 1
3.1%
43 1
3.1%
ValueCountFrequency (%)
9881 1
3.1%
9172 1
3.1%
8286 1
3.1%
6692 1
3.1%
6466 1
3.1%
6079 1
3.1%
5902 1
3.1%
5712 1
3.1%
5015 1
3.1%
4206 1
3.1%

400(순수)
Real number (ℝ)

HIGH CORRELATION  MISSING  ZEROS 

Distinct29
Distinct (%)93.5%
Missing1
Missing (%)3.1%
Infinite0
Infinite (%)0.0%
Mean1456.129
Minimum0
Maximum6489
Zeros1
Zeros (%)3.1%
Negative0
Negative (%)0.0%
Memory size420.0 B
2023-12-13T00:13:48.411986image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile4.5
Q114
median96
Q32089
95-th percentile6100
Maximum6489
Range6489
Interquartile range (IQR)2075

Descriptive statistics

Standard deviation2209.8034
Coefficient of variation (CV)1.5175876
Kurtosis0.39094923
Mean1456.129
Median Absolute Deviation (MAD)90
Skewness1.3838015
Sum45140
Variance4883231.1
MonotonicityNot monotonic
2023-12-13T00:13:48.562432image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=29)
ValueCountFrequency (%)
17 2
 
6.2%
12 2
 
6.2%
2129 1
 
3.1%
96 1
 
3.1%
0 1
 
3.1%
36 1
 
3.1%
16 1
 
3.1%
1361 1
 
3.1%
391 1
 
3.1%
174 1
 
3.1%
Other values (19) 19
59.4%
ValueCountFrequency (%)
0 1
3.1%
3 1
3.1%
6 1
3.1%
7 1
3.1%
9 1
3.1%
11 1
3.1%
12 2
6.2%
16 1
3.1%
17 2
6.2%
22 1
3.1%
ValueCountFrequency (%)
6489 1
3.1%
6306 1
3.1%
5894 1
3.1%
5244 1
3.1%
5185 1
3.1%
4757 1
3.1%
2141 1
3.1%
2129 1
3.1%
2049 1
3.1%
1361 1
3.1%

500(기술)
Real number (ℝ)

HIGH CORRELATION  MISSING  ZEROS 

Distinct30
Distinct (%)96.8%
Missing1
Missing (%)3.1%
Infinite0
Infinite (%)0.0%
Mean904.83871
Minimum0
Maximum6395
Zeros1
Zeros (%)3.1%
Negative0
Negative (%)0.0%
Memory size420.0 B
2023-12-13T00:13:48.696782image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile2
Q116
median75
Q3992
95-th percentile5118
Maximum6395
Range6395
Interquartile range (IQR)976

Descriptive statistics

Standard deviation1701.4847
Coefficient of variation (CV)1.8804287
Kurtosis4.3842779
Mean904.83871
Median Absolute Deviation (MAD)74
Skewness2.2965046
Sum28050
Variance2895050.1
MonotonicityNot monotonic
2023-12-13T00:13:48.835464image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=30)
ValueCountFrequency (%)
4 2
 
6.2%
6395 1
 
3.1%
883 1
 
3.1%
0 1
 
3.1%
1 1
 
3.1%
436 1
 
3.1%
154 1
 
3.1%
306 1
 
3.1%
37 1
 
3.1%
88 1
 
3.1%
Other values (20) 20
62.5%
ValueCountFrequency (%)
0 1
3.1%
1 1
3.1%
3 1
3.1%
4 2
6.2%
8 1
3.1%
10 1
3.1%
13 1
3.1%
19 1
3.1%
23 1
3.1%
28 1
3.1%
ValueCountFrequency (%)
6395 1
3.1%
5203 1
3.1%
5033 1
3.1%
3347 1
3.1%
1374 1
3.1%
1325 1
3.1%
1165 1
3.1%
1101 1
3.1%
883 1
3.1%
515 1
3.1%

600(예술)
Real number (ℝ)

HIGH CORRELATION  MISSING  ZEROS 

Distinct29
Distinct (%)93.5%
Missing1
Missing (%)3.1%
Infinite0
Infinite (%)0.0%
Mean576.87097
Minimum0
Maximum3129
Zeros1
Zeros (%)3.1%
Negative0
Negative (%)0.0%
Memory size420.0 B
2023-12-13T00:13:48.998035image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile1
Q111.5
median48
Q31005
95-th percentile2733
Maximum3129
Range3129
Interquartile range (IQR)993.5

Descriptive statistics

Standard deviation899.3777
Coefficient of variation (CV)1.5590622
Kurtosis2.2981723
Mean576.87097
Median Absolute Deviation (MAD)48
Skewness1.7596426
Sum17883
Variance808880.25
MonotonicityNot monotonic
2023-12-13T00:13:49.134974image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=29)
ValueCountFrequency (%)
1 3
 
9.4%
2878 1
 
3.1%
1110 1
 
3.1%
0 1
 
3.1%
39 1
 
3.1%
395 1
 
3.1%
111 1
 
3.1%
302 1
 
3.1%
37 1
 
3.1%
191 1
 
3.1%
Other values (19) 19
59.4%
ValueCountFrequency (%)
0 1
 
3.1%
1 3
9.4%
2 1
 
3.1%
5 1
 
3.1%
6 1
 
3.1%
11 1
 
3.1%
12 1
 
3.1%
15 1
 
3.1%
17 1
 
3.1%
21 1
 
3.1%
ValueCountFrequency (%)
3129 1
3.1%
2878 1
3.1%
2588 1
3.1%
1634 1
3.1%
1245 1
3.1%
1240 1
3.1%
1110 1
3.1%
1099 1
3.1%
911 1
3.1%
681 1
3.1%

700(언어)
Real number (ℝ)

HIGH CORRELATION  MISSING  ZEROS 

Distinct28
Distinct (%)90.3%
Missing1
Missing (%)3.1%
Infinite0
Infinite (%)0.0%
Mean1572.6774
Minimum0
Maximum5849
Zeros3
Zeros (%)9.4%
Negative0
Negative (%)0.0%
Memory size420.0 B
2023-12-13T00:13:49.287146image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q16
median132
Q33055.5
95-th percentile5342
Maximum5849
Range5849
Interquartile range (IQR)3049.5

Descriptive statistics

Standard deviation2022.4593
Coefficient of variation (CV)1.2859975
Kurtosis-0.66850792
Mean1572.6774
Median Absolute Deviation (MAD)132
Skewness0.92583011
Sum48753
Variance4090341.6
MonotonicityNot monotonic
2023-12-13T00:13:49.420074image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=28)
ValueCountFrequency (%)
0 3
 
9.4%
4 2
 
6.2%
2840 1
 
3.1%
4996 1
 
3.1%
891 1
 
3.1%
38 1
 
3.1%
3331 1
 
3.1%
3271 1
 
3.1%
786 1
 
3.1%
274 1
 
3.1%
Other values (18) 18
56.2%
ValueCountFrequency (%)
0 3
9.4%
1 1
 
3.1%
2 1
 
3.1%
3 1
 
3.1%
4 2
6.2%
8 1
 
3.1%
32 1
 
3.1%
37 1
 
3.1%
38 1
 
3.1%
50 1
 
3.1%
ValueCountFrequency (%)
5849 1
3.1%
5409 1
3.1%
5275 1
3.1%
4996 1
3.1%
4260 1
3.1%
4189 1
3.1%
3331 1
3.1%
3271 1
3.1%
2840 1
3.1%
2590 1
3.1%

800(문학)
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct30
Distinct (%)93.8%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean6288.4688
Minimum0
Maximum23085
Zeros2
Zeros (%)6.2%
Negative0
Negative (%)0.0%
Memory size420.0 B
2023-12-13T00:13:49.583826image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile1.1
Q1188.5
median673.5
Q315223.5
95-th percentile19187.7
Maximum23085
Range23085
Interquartile range (IQR)15035

Descriptive statistics

Standard deviation8165.8171
Coefficient of variation (CV)1.2985382
Kurtosis-1.048361
Mean6288.4688
Median Absolute Deviation (MAD)672.5
Skewness0.85202925
Sum201231
Variance66680568
MonotonicityNot monotonic
2023-12-13T00:13:49.722790image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=30)
ValueCountFrequency (%)
2 2
 
6.2%
0 2
 
6.2%
23085 1
 
3.1%
21 1
 
3.1%
23 1
 
3.1%
1122 1
 
3.1%
11356 1
 
3.1%
5603 1
 
3.1%
4061 1
 
3.1%
673 1
 
3.1%
Other values (20) 20
62.5%
ValueCountFrequency (%)
0 2
6.2%
2 2
6.2%
21 1
3.1%
23 1
3.1%
101 1
3.1%
127 1
3.1%
209 1
3.1%
210 1
3.1%
211 1
3.1%
248 1
3.1%
ValueCountFrequency (%)
23085 1
3.1%
19455 1
3.1%
18969 1
3.1%
18925 1
3.1%
18758 1
3.1%
18312 1
3.1%
16358 1
3.1%
16344 1
3.1%
14850 1
3.1%
11356 1
3.1%

900(역사)
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct31
Distinct (%)96.9%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1339.1875
Minimum0
Maximum6244
Zeros1
Zeros (%)3.1%
Negative0
Negative (%)0.0%
Memory size420.0 B
2023-12-13T00:13:49.874144image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile5.75
Q119.5
median70.5
Q32581.75
95-th percentile4724.05
Maximum6244
Range6244
Interquartile range (IQR)2562.25

Descriptive statistics

Standard deviation1989.1248
Coefficient of variation (CV)1.4853221
Kurtosis-0.15945813
Mean1339.1875
Median Absolute Deviation (MAD)65
Skewness1.2008148
Sum42854
Variance3956617.4
MonotonicityNot monotonic
2023-12-13T00:13:50.015665image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=31)
ValueCountFrequency (%)
8 2
 
6.2%
4470 1
 
3.1%
81 1
 
3.1%
0 1
 
3.1%
46 1
 
3.1%
3 1
 
3.1%
945 1
 
3.1%
77 1
 
3.1%
332 1
 
3.1%
36 1
 
3.1%
Other values (21) 21
65.6%
ValueCountFrequency (%)
0 1
3.1%
3 1
3.1%
8 2
6.2%
11 1
3.1%
12 1
3.1%
14 1
3.1%
18 1
3.1%
20 1
3.1%
31 1
3.1%
36 1
3.1%
ValueCountFrequency (%)
6244 1
3.1%
4938 1
3.1%
4549 1
3.1%
4470 1
3.1%
4376 1
3.1%
4346 1
3.1%
4230 1
3.1%
3433 1
3.1%
2298 1
3.1%
1081 1
3.1%

소계
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct32
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean15889.469
Minimum24
Maximum60023
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size420.0 B
2023-12-13T00:13:50.169179image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum24
5-th percentile119.35
Q1406
median1682
Q337189.25
95-th percentile50824
Maximum60023
Range59999
Interquartile range (IQR)36783.25

Descriptive statistics

Standard deviation21054.384
Coefficient of variation (CV)1.3250527
Kurtosis-0.92912293
Mean15889.469
Median Absolute Deviation (MAD)1596.5
Skewness0.91346035
Sum508463
Variance4.4328708 × 108
MonotonicityNot monotonic
2023-12-13T00:13:50.361856image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=32)
ValueCountFrequency (%)
60023 1
 
3.1%
454 1
 
3.1%
24 1
 
3.1%
2206 1
 
3.1%
66 1
 
3.1%
18877 1
 
3.1%
10804 1
 
3.1%
6822 1
 
3.1%
1052 1
 
3.1%
183 1
 
3.1%
Other values (22) 22
68.8%
ValueCountFrequency (%)
24 1
3.1%
66 1
3.1%
163 1
3.1%
183 1
3.1%
272 1
3.1%
284 1
3.1%
332 1
3.1%
352 1
3.1%
424 1
3.1%
436 1
3.1%
ValueCountFrequency (%)
60023 1
3.1%
53079 1
3.1%
48979 1
3.1%
48183 1
3.1%
46699 1
3.1%
46507 1
3.1%
44133 1
3.1%
40409 1
3.1%
36116 1
3.1%
29629 1
3.1%

담당부서
Categorical

CONSTANT 

Distinct1
Distinct (%)3.1%
Missing0
Missing (%)0.0%
Memory size388.0 B
대구광역시 달서구 평생교육과
32 

Length

Max length15
Median length15
Mean length15
Min length15

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row대구광역시 달서구 평생교육과
2nd row대구광역시 달서구 평생교육과
3rd row대구광역시 달서구 평생교육과
4th row대구광역시 달서구 평생교육과
5th row대구광역시 달서구 평생교육과

Common Values

ValueCountFrequency (%)
대구광역시 달서구 평생교육과 32
100.0%

Length

2023-12-13T00:13:50.546662image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T00:13:50.701626image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
대구광역시 32
33.3%
달서구 32
33.3%
평생교육과 32
33.3%

기준일자
Categorical

CONSTANT 

Distinct1
Distinct (%)3.1%
Missing0
Missing (%)0.0%
Memory size388.0 B
2023-03-01
32 

Length

Max length10
Median length10
Mean length10
Min length10

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row2023-03-01
2nd row2023-03-01
3rd row2023-03-01
4th row2023-03-01
5th row2023-03-01

Common Values

ValueCountFrequency (%)
2023-03-01 32
100.0%

Length

2023-12-13T00:13:50.825814image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T00:13:50.947824image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2023-03-01 32
100.0%

Interactions

2023-12-13T00:13:44.936437image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T00:13:34.352226image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T00:13:35.675134image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T00:13:36.688202image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T00:13:37.680879image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T00:13:38.590133image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T00:13:39.444463image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T00:13:40.296252image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T00:13:41.720125image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T00:13:42.901352image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T00:13:43.945204image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T00:13:45.031898image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T00:13:34.421808image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T00:13:35.761919image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T00:13:36.790975image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T00:13:37.768571image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T00:13:38.671204image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T00:13:39.521124image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T00:13:40.372519image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T00:13:41.821190image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T00:13:42.999426image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T00:13:44.037453image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T00:13:45.130823image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T00:13:34.504429image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T00:13:35.848504image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T00:13:36.903493image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T00:13:37.856163image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T00:13:38.750753image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T00:13:39.595331image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T00:13:40.454339image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T00:13:41.938314image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T00:13:43.081816image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T00:13:44.121507image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T00:13:45.253555image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T00:13:34.621342image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T00:13:35.947066image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T00:13:37.000722image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T00:13:37.949485image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T00:13:38.846263image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T00:13:39.676822image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T00:13:40.550900image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T00:13:42.039842image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T00:13:43.167007image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T00:13:44.212604image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T00:13:45.344619image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T00:13:34.710748image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T00:13:36.046439image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T00:13:37.085447image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T00:13:38.021899image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T00:13:38.919564image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T00:13:39.749207image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T00:13:40.632864image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T00:13:42.126317image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T00:13:43.246742image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T00:13:44.304199image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T00:13:45.458179image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T00:13:34.802948image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T00:13:36.154249image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T00:13:37.167495image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T00:13:38.111648image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T00:13:38.997834image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T00:13:39.823939image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T00:13:41.097960image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T00:13:42.212757image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T00:13:43.339545image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T00:13:44.412651image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T00:13:45.567416image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T00:13:34.893266image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T00:13:36.261698image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T00:13:37.253481image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T00:13:38.190160image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T00:13:39.069469image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T00:13:39.915397image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T00:13:41.186478image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T00:13:42.360651image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T00:13:43.438531image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T00:13:44.503732image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T00:13:45.665452image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T00:13:34.988430image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T00:13:36.359891image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T00:13:37.338048image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T00:13:38.275682image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T00:13:39.142570image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T00:13:39.995642image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T00:13:41.320124image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T00:13:42.488464image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T00:13:43.525187image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T00:13:44.588813image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T00:13:45.766153image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T00:13:35.067516image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T00:13:36.442191image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T00:13:37.423000image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T00:13:38.349637image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T00:13:39.216513image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T00:13:40.071042image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T00:13:41.438772image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T00:13:42.623991image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T00:13:43.641889image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T00:13:44.673934image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T00:13:45.863541image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T00:13:35.432501image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T00:13:36.523180image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T00:13:37.502292image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T00:13:38.422070image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T00:13:39.297931image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T00:13:40.142096image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T00:13:41.529315image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T00:13:42.698763image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T00:13:43.740760image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T00:13:44.755308image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T00:13:45.978506image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T00:13:35.532588image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T00:13:36.603669image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T00:13:37.590052image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T00:13:38.507998image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T00:13:39.370376image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T00:13:40.220163image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T00:13:41.626700image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T00:13:42.786503image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T00:13:43.832477image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T00:13:44.844161image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-13T00:13:51.053227image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
도서관명구분0(총류)100(철학)200(종교)300(사회)400(순수)500(기술)600(예술)700(언어)800(문학)900(역사)소계
도서관명1.0000.0000.0000.0000.0000.0000.2070.3870.0000.4470.0000.0000.000
구분0.0001.0000.3990.8710.5340.2520.5440.4140.0000.6090.2870.6290.324
0(총류)0.0000.3991.0000.9260.9780.8250.8620.8470.8760.9060.8180.9490.928
100(철학)0.0000.8710.9261.0000.9540.8400.8680.8960.9350.8890.9290.8860.951
200(종교)0.0000.5340.9780.9541.0000.8740.7990.9050.9150.9330.8690.9030.957
300(사회)0.0000.2520.8250.8400.8741.0000.9550.9350.9670.8250.8610.9160.822
400(순수)0.2070.5440.8620.8680.7990.9551.0000.8570.9800.7880.8840.9290.877
500(기술)0.3870.4140.8470.8960.9050.9350.8571.0000.9740.8170.8430.9680.884
600(예술)0.0000.0000.8760.9350.9150.9670.9800.9741.0000.8540.9300.9640.947
700(언어)0.4470.6090.9060.8890.9330.8250.7880.8170.8541.0000.8660.7480.960
800(문학)0.0000.2870.8180.9290.8690.8610.8840.8430.9300.8661.0000.8010.965
900(역사)0.0000.6290.9490.8860.9030.9160.9290.9680.9640.7480.8011.0000.826
소계0.0000.3240.9280.9510.9570.8220.8770.8840.9470.9600.9650.8261.000
2023-12-13T00:13:51.210357image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
구분도서관명
구분1.0000.000
도서관명0.0001.000
2023-12-13T00:13:51.303437image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
0(총류)100(철학)200(종교)300(사회)400(순수)500(기술)600(예술)700(언어)800(문학)900(역사)소계도서관명구분
0(총류)1.0000.8050.8350.8700.8580.8870.9010.8300.7180.9140.8680.0000.110
100(철학)0.8051.0000.9500.9040.7200.9220.8690.6770.8800.8460.9160.0000.458
200(종교)0.8350.9501.0000.8950.7730.8910.9110.7420.8750.8680.9170.0000.206
300(사회)0.8700.9040.8951.0000.8250.9410.9260.8150.8540.9240.9490.0000.000
400(순수)0.8580.7200.7730.8251.0000.7770.8730.9350.7680.9200.8530.0850.242
500(기술)0.8870.9220.8910.9410.7771.0000.9040.7480.7810.9010.9240.2210.151
600(예술)0.9010.8690.9110.9260.8730.9041.0000.8560.8080.9210.9290.0000.000
700(언어)0.8300.6770.7420.8150.9350.7480.8561.0000.7500.8870.8450.2400.255
800(문학)0.7180.8800.8750.8540.7680.7810.8080.7501.0000.8360.9180.0000.000
900(역사)0.9140.8460.8680.9240.9200.9010.9210.8870.8361.0000.9450.0000.313
소계0.8680.9160.9170.9490.8530.9240.9290.8450.9180.9451.0000.0000.055
도서관명0.0000.0000.0000.0000.0850.2210.0000.2400.0000.0000.0001.0000.000
구분0.1100.4580.2060.0000.2420.1510.0000.2550.0000.3130.0550.0001.000

Missing values

2023-12-13T00:13:46.117533image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-13T00:13:46.374746image/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.
2023-12-13T00:13:46.496508image/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

도서관명구분0(총류)100(철학)200(종교)300(사회)400(순수)500(기술)600(예술)700(언어)800(문학)900(역사)소계담당부서기준일자
0도원도서관일반도서2272424118329881212963952878284023085447060023대구광역시 달서구 평생교육과2023-03-01
1도원도서관아동도서151111975026079518511011099426018969423044133대구광역시 달서구 평생교육과2023-03-01
2도원도서관참고도서1233349562822100250436대구광역시 달서구 평생교육과2023-03-01
3도원도서관점자도서51910351785420920332대구광역시 달서구 평생교육과2023-03-01
4도원도서관큰글자도서3264155865011324838525대구광역시 달서구 평생교육과2023-03-01
5달서어린이유아도서49670139966924757380911584914850108136116대구광역시 달서구 평생교육과2023-03-01
6달서어린이초등도서254313877475015630613251245540918758624448979대구광역시 달서구 평생교육과2023-03-01
7달서어린이학부모도서1822026579110713741311321011743259대구광역시 달서구 평생교육과2023-03-01
8달서어린이점자도서132171731021018272대구광역시 달서구 평생교육과2023-03-01
9성서도서관일반도서2233446819189172214150333129232718312434653079대구광역시 달서구 평생교육과2023-03-01
도서관명구분0(총류)100(철학)200(종교)300(사회)400(순수)500(기술)600(예술)700(언어)800(문학)900(역사)소계담당부서기준일자
22달서가족문화참고도서2845419131532214163대구광역시 달서구 평생교육과2023-03-01
23달서가족문화교과연계도서4431118089012878819127416188795861대구광역시 달서구 평생교육과2023-03-01
24달서가족문화점자도서<NA>11924<NA><NA><NA><NA>12712183대구광역시 달서구 평생교육과2023-03-01
25달서가족문화큰글자도서19828149737374673361052대구광역시 달서구 평생교육과2023-03-01
26달서영어일반도서4911519550217430630278640613326822대구광역시 달서구 평생교육과2023-03-01
27달서영어유아도서10927371024391154111327156037710804대구광역시 달서구 평생교육과2023-03-01
28달서영어아동도서41282105454136143639533311135694518877대구광역시 달서구 평생교육과2023-03-01
29달서영어참고도서40031611380366대구광역시 달서구 평생교육과2023-03-01
30달서영어특화도서191543364398911122462206대구광역시 달서구 평생교육과2023-03-01
31달서영어큰글자도서0010000023024대구광역시 달서구 평생교육과2023-03-01