Overview

Dataset statistics

Number of variables6
Number of observations95
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory5.0 KiB
Average record size in memory53.4 B

Variable types

Numeric4
Categorical2

Dataset

Description김해시에서 통계기반 도시현황 파악을 위해 개발한 통계지수 중 하나로서, 통계연도, 시도명, 시군구명, 공공도서관 1개소당 주민수(명), 공공도서관 수(개), 총인구수(명)로 구성되어 있습니다. 김해시 중심의 통계지수로서, 데이터 수집, 가공 등의 어려움으로 김해시 외 지역의 정보는 누락될 수 있습니다.
Author경상남도 김해시
URLhttps://www.data.go.kr/data/15110184/fileData.do

Alerts

시도명 is highly overall correlated with 공공도서관 1개소당 주민수(명) and 3 other fieldsHigh correlation
시군구명 is highly overall correlated with 공공도서관 1개소당 주민수(명) and 3 other fieldsHigh correlation
공공도서관 1개소당 주민수(명) is highly overall correlated with 시도명 and 1 other fieldsHigh correlation
공공도서관 수(개) is highly overall correlated with 총인구수(명) and 2 other fieldsHigh correlation
총인구수(명) is highly overall correlated with 공공도서관 수(개) and 2 other fieldsHigh correlation
공공도서관 1개소당 주민수(명) has unique valuesUnique
총인구수(명) has unique valuesUnique

Reproduction

Analysis started2023-12-12 21:05:26.870585
Analysis finished2023-12-12 21:05:28.531668
Duration1.66 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

통계연도
Real number (ℝ)

Distinct6
Distinct (%)6.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2018.0526
Minimum2016
Maximum2021
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size987.0 B
2023-12-13T06:05:28.593268image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum2016
5-th percentile2016
Q12017
median2018
Q32019
95-th percentile2020
Maximum2021
Range5
Interquartile range (IQR)2

Descriptive statistics

Standard deviation1.4393292
Coefficient of variation (CV)0.00071322679
Kurtosis-1.2305269
Mean2018.0526
Median Absolute Deviation (MAD)1
Skewness0.015446021
Sum191715
Variance2.0716685
MonotonicityIncreasing
2023-12-13T06:05:28.741713image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=6)
ValueCountFrequency (%)
2017 19
20.0%
2018 19
20.0%
2019 19
20.0%
2020 19
20.0%
2016 18
18.9%
2021 1
 
1.1%
ValueCountFrequency (%)
2016 18
18.9%
2017 19
20.0%
2018 19
20.0%
2019 19
20.0%
2020 19
20.0%
2021 1
 
1.1%
ValueCountFrequency (%)
2021 1
 
1.1%
2020 19
20.0%
2019 19
20.0%
2018 19
20.0%
2017 19
20.0%
2016 18
18.9%

시도명
Categorical

HIGH CORRELATION 

Distinct18
Distinct (%)18.9%
Missing0
Missing (%)0.0%
Memory size892.0 B
경상남도
10 
전국
 
5
부산광역시
 
5
대구광역시
 
5
인천광역시
 
5
Other values (13)
65 

Length

Max length7
Median length5
Mean length4.4736842
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row전국
2nd row서울특별시
3rd row부산광역시
4th row대구광역시
5th row인천광역시

Common Values

ValueCountFrequency (%)
경상남도 10
 
10.5%
전국 5
 
5.3%
부산광역시 5
 
5.3%
대구광역시 5
 
5.3%
인천광역시 5
 
5.3%
광주광역시 5
 
5.3%
대전광역시 5
 
5.3%
울산광역시 5
 
5.3%
세종특별자치시 5
 
5.3%
경기도 5
 
5.3%
Other values (8) 40
42.1%

Length

2023-12-13T06:05:28.893283image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
경상남도 10
 
10.5%
전국 5
 
5.3%
서울특별시 5
 
5.3%
경상북도 5
 
5.3%
전라남도 5
 
5.3%
전라북도 5
 
5.3%
충청남도 5
 
5.3%
충청북도 5
 
5.3%
강원도 5
 
5.3%
경기도 5
 
5.3%
Other values (8) 40
42.1%

시군구명
Categorical

HIGH CORRELATION 

Distinct19
Distinct (%)20.0%
Missing0
Missing (%)0.0%
Memory size892.0 B
전국
 
5
서울특별시
 
5
부산광역시
 
5
대구광역시
 
5
인천광역시
 
5
Other values (14)
70 

Length

Max length7
Median length5
Mean length4.4210526
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row전국
2nd row서울특별시
3rd row부산광역시
4th row대구광역시
5th row인천광역시

Common Values

ValueCountFrequency (%)
전국 5
 
5.3%
서울특별시 5
 
5.3%
부산광역시 5
 
5.3%
대구광역시 5
 
5.3%
인천광역시 5
 
5.3%
광주광역시 5
 
5.3%
대전광역시 5
 
5.3%
울산광역시 5
 
5.3%
세종특별자치시 5
 
5.3%
경기도 5
 
5.3%
Other values (9) 45
47.4%

Length

2023-12-13T06:05:29.039169image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
전국 5
 
5.3%
강원도 5
 
5.3%
제주특별자치도 5
 
5.3%
경상남도 5
 
5.3%
경상북도 5
 
5.3%
전라남도 5
 
5.3%
전라북도 5
 
5.3%
충청남도 5
 
5.3%
충청북도 5
 
5.3%
경기도 5
 
5.3%
Other values (9) 45
47.4%

공공도서관 1개소당 주민수(명)
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct95
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean45182.044
Minimum407.64
Maximum87463.23
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size987.0 B
2023-12-13T06:05:29.183585image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum407.64
5-th percentile18398.267
Q131351.135
median46947.6
Q359916.76
95-th percentile71341.856
Maximum87463.23
Range87055.59
Interquartile range (IQR)28565.625

Descriptive statistics

Standard deviation18511.566
Coefficient of variation (CV)0.40971068
Kurtosis0.18798074
Mean45182.044
Median Absolute Deviation (MAD)14661.31
Skewness-0.27239141
Sum4292294.2
Variance3.4267808 × 108
MonotonicityNot monotonic
2023-12-13T06:05:29.672895image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
51184.37 1
 
1.1%
67555.21 1
 
1.1%
26696.36 1
 
1.1%
30829.1 1
 
1.1%
33709.67 1
 
1.1%
33333.48 1
 
1.1%
26577.62 1
 
1.1%
47796.63 1
 
1.1%
30961.36 1
 
1.1%
60422.05 1
 
1.1%
Other values (85) 85
89.5%
ValueCountFrequency (%)
407.64 1
1.1%
422.71 1
1.1%
443.91 1
1.1%
450.74 1
1.1%
478.54 1
1.1%
26078.15 1
1.1%
26149.83 1
1.1%
26577.62 1
1.1%
26696.36 1
1.1%
27071.09 1
1.1%
ValueCountFrequency (%)
87463.23 1
1.1%
86766.33 1
1.1%
80033.79 1
1.1%
77587.3 1
1.1%
72169.06 1
1.1%
70987.34 1
1.1%
68959.06 1
1.1%
68756.42 1
1.1%
67555.21 1
1.1%
66782.45 1
1.1%

공공도서관 수(개)
Real number (ℝ)

HIGH CORRELATION 

Distinct61
Distinct (%)64.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean179.24211
Minimum5
Maximum1319
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size987.0 B
2023-12-13T06:05:29.837601image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum5
5-th percentile15.5
Q125.5
median57
Q370.5
95-th percentile1145.4
Maximum1319
Range1314
Interquartile range (IQR)45

Descriptive statistics

Standard deviation343.63581
Coefficient of variation (CV)1.9171601
Kurtosis4.7883758
Mean179.24211
Median Absolute Deviation (MAD)18
Skewness2.5240139
Sum17028
Variance118085.57
MonotonicityNot monotonic
2023-12-13T06:05:30.013489image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
58 4
 
4.2%
22 4
 
4.2%
24 4
 
4.2%
59 4
 
4.2%
63 3
 
3.2%
23 3
 
3.2%
19 3
 
3.2%
44 3
 
3.2%
65 3
 
3.2%
64 2
 
2.1%
Other values (51) 62
65.3%
ValueCountFrequency (%)
5 2
2.1%
10 1
 
1.1%
11 1
 
1.1%
12 1
 
1.1%
17 1
 
1.1%
18 1
 
1.1%
19 3
3.2%
21 2
2.1%
22 4
4.2%
23 3
3.2%
ValueCountFrequency (%)
1319 1
1.1%
1283 1
1.1%
1222 1
1.1%
1184 1
1.1%
1172 1
1.1%
1134 1
1.1%
1112 1
1.1%
1096 1
1.1%
1042 1
1.1%
1010 1
1.1%

총인구수(명)
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct95
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean5480501.9
Minimum243048
Maximum51849861
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size987.0 B
2023-12-13T06:05:30.189987image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum243048
5-th percentile479241.7
Q11463826
median1882970
Q33351384.5
95-th percentile24907775
Maximum51849861
Range51606813
Interquartile range (IQR)1887558.5

Descriptive statistics

Standard deviation11408088
Coefficient of variation (CV)2.0815772
Kurtosis12.330713
Mean5480501.9
Median Absolute Deviation (MAD)793861
Skewness3.621397
Sum5.2064768 × 108
Variance1.3014447 × 1014
MonotonicityNot monotonic
2023-12-13T06:05:30.396465image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
51696216 1
 
1.1%
9930616 1
 
1.1%
1868745 1
 
1.1%
1818917 1
 
1.1%
2123709 1
 
1.1%
1600007 1
 
1.1%
1541502 1
 
1.1%
13239666 1
 
1.1%
340575 1
 
1.1%
1148019 1
 
1.1%
Other values (85) 85
89.5%
ValueCountFrequency (%)
243048 1
1.1%
280100 1
1.1%
314126 1
1.1%
340575 1
1.1%
355831 1
1.1%
532132 1
1.1%
533672 1
1.1%
537673 1
1.1%
542338 1
1.1%
542455 1
1.1%
ValueCountFrequency (%)
51849861 1
1.1%
51829023 1
1.1%
51826059 1
1.1%
51778544 1
1.1%
51696216 1
1.1%
13427014 1
1.1%
13239666 1
1.1%
13077153 1
1.1%
12873895 1
1.1%
12716780 1
1.1%

Interactions

2023-12-13T06:05:28.071110image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T06:05:27.113808image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T06:05:27.471437image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T06:05:27.759596image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T06:05:28.148134image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T06:05:27.207980image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T06:05:27.541599image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T06:05:27.837925image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T06:05:28.214008image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T06:05:27.291833image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T06:05:27.610426image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T06:05:27.920327image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T06:05:28.294168image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T06:05:27.392499image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T06:05:27.682785image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T06:05:27.995102image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-13T06:05:30.531394image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
통계연도시도명시군구명공공도서관 1개소당 주민수(명)공공도서관 수(개)총인구수(명)
통계연도1.0000.0000.0000.0980.3020.000
시도명0.0001.0001.0000.9340.8981.000
시군구명0.0001.0001.0000.9210.8871.000
공공도서관 1개소당 주민수(명)0.0980.9340.9211.0000.6520.547
공공도서관 수(개)0.3020.8980.8870.6521.0000.916
총인구수(명)0.0001.0001.0000.5470.9161.000
2023-12-13T06:05:30.653273image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
시도명시군구명
시도명1.0000.993
시군구명0.9931.000
2023-12-13T06:05:30.750403image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
통계연도공공도서관 1개소당 주민수(명)공공도서관 수(개)총인구수(명)시도명시군구명
통계연도1.000-0.2370.138-0.0640.0000.000
공공도서관 1개소당 주민수(명)-0.2371.000-0.3510.3450.5890.651
공공도서관 수(개)0.138-0.3511.0000.5810.5540.619
총인구수(명)-0.0640.3450.5811.0000.9200.914
시도명0.0000.5890.5540.9201.0000.993
시군구명0.0000.6510.6190.9140.9931.000

Missing values

2023-12-13T06:05:28.387281image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-13T06:05:28.492269image/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

통계연도시도명시군구명공공도서관 1개소당 주민수(명)공공도서관 수(개)총인구수(명)
02016전국전국51184.37101051696216
12016서울특별시서울특별시67555.211479930616
22016부산광역시부산광역시87463.23403498529
32016대구광역시대구광역시70987.34352484557
42016인천광역시인천광역시62618.49472943069
52016광주광역시광주광역시66782.45221469214
62016대전광역시대전광역시63098.75241514370
72016울산광역시울산광역시68959.06171172304
82016세종특별자치시세종특별자치시48609.65243048
92016경기도경기도52117.9524412716780
통계연도시도명시군구명공공도서관 1개소당 주민수(명)공공도서관 수(개)총인구수(명)
852020강원도강원도26149.83591542840
862020충청북도충청북도32016.74501600837
872020충청남도충청남도33667.13632121029
882020전라북도전라북도28636.57631804104
892020전라남도전라남도26078.15711851549
902020경상북도경상북도38252.49692639422
912020경상남도경상남도44536.21753340216
922020경상남도김해시422.711283542338
932020제주특별자치도제주특별자치도30665.2322674635
942021경상남도김해시407.641319537673