Overview

Dataset statistics

Number of variables6
Number of observations1108
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory56.4 KiB
Average record size in memory52.1 B

Variable types

Categorical2
Text1
Numeric3

Dataset

Description김해시에서 통계기반 도시현황 파악을 위해 개발한 통계지수 중 하나로서, 통계연도, 시도명, 시군구명, 1인당 공공도서관 장서수(권), 공공도서관 총 도서(인쇄) 수(권), 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/15110185/fileData.do

Alerts

1인당 공공도서관 장서수(권) is highly overall correlated with 총인구수(명)High correlation
공공도서관 총 도서(인쇄) 수(권) is highly overall correlated with 총인구수(명)High correlation
총인구수(명) is highly overall correlated with 1인당 공공도서관 장서수(권) and 1 other fieldsHigh correlation
공공도서관 총 도서(인쇄) 수(권) has unique valuesUnique

Reproduction

Analysis started2023-12-12 04:02:34.245577
Analysis finished2023-12-12 04:02:36.373243
Duration2.13 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

통계연도
Categorical

Distinct5
Distinct (%)0.5%
Missing0
Missing (%)0.0%
Memory size8.8 KiB
2021
229 
2020
228 
2019
218 
2017
217 
2018
216 

Length

Max length4
Median length4
Mean length4
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row2017
2nd row2017
3rd row2017
4th row2017
5th row2017

Common Values

ValueCountFrequency (%)
2021 229
20.7%
2020 228
20.6%
2019 218
19.7%
2017 217
19.6%
2018 216
19.5%

Length

2023-12-12T13:02:36.458654image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T13:02:36.595839image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2021 229
20.7%
2020 228
20.6%
2019 218
19.7%
2017 217
19.6%
2018 216
19.5%

시도명
Categorical

Distinct17
Distinct (%)1.5%
Missing0
Missing (%)0.0%
Memory size8.8 KiB
경기도
135 
서울특별시
125 
경상북도
112 
전라남도
110 
강원도
90 
Other values (12)
536 

Length

Max length7
Median length5
Mean length4.1696751
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
경기도 135
12.2%
서울특별시 125
11.3%
경상북도 112
10.1%
전라남도 110
9.9%
강원도 90
8.1%
경상남도 87
7.9%
부산광역시 80
7.2%
충청남도 72
6.5%
전라북도 67
 
6.0%
충청북도 52
 
4.7%
Other values (7) 178
16.1%

Length

2023-12-12T13:02:36.794070image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
경기도 135
12.2%
서울특별시 125
11.3%
경상북도 112
10.1%
전라남도 110
9.9%
강원도 90
8.1%
경상남도 87
7.9%
부산광역시 80
7.2%
충청남도 72
6.5%
전라북도 67
 
6.0%
충청북도 52
 
4.7%
Other values (7) 178
16.1%

시군구명
Text

Distinct207
Distinct (%)18.7%
Missing0
Missing (%)0.0%
Memory size8.8 KiB
2023-12-12T13:02:37.224259image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length4
Median length3
Mean length2.9287004
Min length2

Characters and Unicode

Total characters3245
Distinct characters133
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row종로구
2nd row중구
3rd row용산구
4th row성동구
5th row광진구
ValueCountFrequency (%)
동구 30
 
2.7%
중구 30
 
2.7%
서구 25
 
2.3%
남구 21
 
1.9%
북구 20
 
1.8%
강서구 10
 
0.9%
고성군 10
 
0.9%
진안군 5
 
0.5%
나주시 5
 
0.5%
장수군 5
 
0.5%
Other values (197) 947
85.5%
2023-12-12T13:02:37.840369image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
군 425
 
13.1%
구 368
 
11.3%
시 360
 
11.1%
천 105
 
3.2%
주 94
 
2.9%
성 87
 
2.7%
동 85
 
2.6%
양 84
 
2.6%
산 77
 
2.4%
서 65
 
2.0%
Other values (123) 1495
46.1%

Most occurring categories

ValueCountFrequency (%)
Other Letter 3245
100.0%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
군 425
 
13.1%
구 368
 
11.3%
시 360
 
11.1%
천 105
 
3.2%
주 94
 
2.9%
성 87
 
2.7%
동 85
 
2.6%
양 84
 
2.6%
산 77
 
2.4%
서 65
 
2.0%
Other values (123) 1495
46.1%

Most occurring scripts

ValueCountFrequency (%)
Hangul 3245
100.0%

Most frequent character per script

Hangul
ValueCountFrequency (%)
군 425
 
13.1%
구 368
 
11.3%
시 360
 
11.1%
천 105
 
3.2%
주 94
 
2.9%
성 87
 
2.7%
동 85
 
2.6%
양 84
 
2.6%
산 77
 
2.4%
서 65
 
2.0%
Other values (123) 1495
46.1%

Most occurring blocks

ValueCountFrequency (%)
Hangul 3245
100.0%

Most frequent character per block

Hangul
ValueCountFrequency (%)
군 425
 
13.1%
구 368
 
11.3%
시 360
 
11.1%
천 105
 
3.2%
주 94
 
2.9%
성 87
 
2.7%
동 85
 
2.6%
양 84
 
2.6%
산 77
 
2.4%
서 65
 
2.0%
Other values (123) 1495
46.1%

1인당 공공도서관 장서수(권)
Real number (ℝ)

HIGH CORRELATION 

Distinct445
Distinct (%)40.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2.8849278
Minimum0.37
Maximum12.19
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size9.9 KiB
2023-12-12T13:02:38.366501image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0.37
5-th percentile1.06
Q11.76
median2.53
Q33.73
95-th percentile5.8355
Maximum12.19
Range11.82
Interquartile range (IQR)1.97

Descriptive statistics

Standard deviation1.5802
Coefficient of variation (CV)0.54774335
Kurtosis4.3229386
Mean2.8849278
Median Absolute Deviation (MAD)0.94
Skewness1.5890084
Sum3196.5
Variance2.4970321
MonotonicityNot monotonic
2023-12-12T13:02:38.572871image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
2.32 7
 
0.6%
2.53 7
 
0.6%
1.1 7
 
0.6%
1.9 7
 
0.6%
2.27 7
 
0.6%
1.86 7
 
0.6%
1.97 7
 
0.6%
1.35 6
 
0.5%
1.83 6
 
0.5%
1.87 6
 
0.5%
Other values (435) 1041
94.0%
ValueCountFrequency (%)
0.37 1
 
0.1%
0.51 1
 
0.1%
0.59 1
 
0.1%
0.64 1
 
0.1%
0.69 2
 
0.2%
0.76 1
 
0.1%
0.78 3
0.3%
0.79 1
 
0.1%
0.81 3
0.3%
0.82 6
0.5%
ValueCountFrequency (%)
12.19 1
0.1%
11.57 1
0.1%
11.47 1
0.1%
11.31 1
0.1%
10.56 1
0.1%
9.08 1
0.1%
9.03 1
0.1%
8.61 1
0.1%
8.56 1
0.1%
8.35 1
0.1%

공공도서관 총 도서(인쇄) 수(권)
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct1108
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean447548.94
Minimum24795
Maximum3926786
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size9.9 KiB
2023-12-12T13:02:38.744091image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum24795
5-th percentile83104.85
Q1170405
median356986
Q3609397.25
95-th percentile1108491
Maximum3926786
Range3901991
Interquartile range (IQR)438992.25

Descriptive statistics

Standard deviation378559.89
Coefficient of variation (CV)0.84585138
Kurtosis13.523817
Mean447548.94
Median Absolute Deviation (MAD)206218.5
Skewness2.6138346
Sum4.9588422 × 108
Variance1.4330759 × 1011
MonotonicityNot monotonic
2023-12-12T13:02:38.918168image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1160477 1
 
0.1%
686691 1
 
0.1%
1181825 1
 
0.1%
1563128 1
 
0.1%
482700 1
 
0.1%
541119 1
 
0.1%
1081654 1
 
0.1%
931059 1
 
0.1%
1369039 1
 
0.1%
1520427 1
 
0.1%
Other values (1098) 1098
99.1%
ValueCountFrequency (%)
24795 1
0.1%
25095 1
0.1%
27473 1
0.1%
46576 1
0.1%
46797 1
0.1%
49986 1
0.1%
51584 1
0.1%
53187 1
0.1%
55738 1
0.1%
59029 1
0.1%
ValueCountFrequency (%)
3926786 1
0.1%
3326340 1
0.1%
3006462 1
0.1%
2533642 1
0.1%
2507872 1
0.1%
2137793 1
0.1%
2134554 1
0.1%
2062591 1
0.1%
2026496 1
0.1%
1888788 1
0.1%

총인구수(명)
Real number (ℝ)

HIGH CORRELATION 

Distinct1107
Distinct (%)99.9%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean206578.58
Minimum8867
Maximum1186078
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size9.9 KiB
2023-12-12T13:02:39.074052image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum8867
5-th percentile26772.05
Q151755.5
median135609.5
Q3314828.5
95-th percentile542423.15
Maximum1186078
Range1177211
Interquartile range (IQR)263073

Descriptive statistics

Standard deviation192365.83
Coefficient of variation (CV)0.93119929
Kurtosis3.085026
Mean206578.58
Median Absolute Deviation (MAD)96506
Skewness1.530248
Sum2.2888906 × 108
Variance3.7004611 × 1010
MonotonicityNot monotonic
2023-12-12T13:02:39.253859image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
122499 2
 
0.2%
154770 1
 
0.1%
218388 1
 
0.1%
1074176 1
 
0.1%
293452 1
 
0.1%
163795 1
 
0.1%
273791 1
 
0.1%
500895 1
 
0.1%
229725 1
 
0.1%
713321 1
 
0.1%
Other values (1097) 1097
99.0%
ValueCountFrequency (%)
8867 1
0.1%
9077 1
0.1%
9617 1
0.1%
9832 1
0.1%
9975 1
0.1%
16320 1
0.1%
16692 1
0.1%
16993 1
0.1%
17356 1
0.1%
17479 1
0.1%
ValueCountFrequency (%)
1186078 1
0.1%
1183714 1
0.1%
1079353 1
0.1%
1079216 1
0.1%
1077508 1
0.1%
1074176 1
0.1%
1036738 1
0.1%
1032741 1
0.1%
940064 1
0.1%
930948 1
0.1%

Interactions

2023-12-12T13:02:35.688152image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:02:34.633849image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:02:35.115530image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:02:35.837717image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:02:34.777530image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:02:35.366566image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:02:36.000714image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:02:34.913729image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:02:35.537844image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-12T13:02:39.390376image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
통계연도시도명1인당 공공도서관 장서수(권)공공도서관 총 도서(인쇄) 수(권)총인구수(명)
통계연도1.0000.0000.0000.1150.000
시도명0.0001.0000.5610.5020.601
1인당 공공도서관 장서수(권)0.0000.5611.0000.2570.543
공공도서관 총 도서(인쇄) 수(권)0.1150.5020.2571.0000.907
총인구수(명)0.0000.6010.5430.9071.000
2023-12-12T13:02:39.502734image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
통계연도시도명
통계연도1.0000.000
시도명0.0001.000
2023-12-12T13:02:39.613551image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
1인당 공공도서관 장서수(권)공공도서관 총 도서(인쇄) 수(권)총인구수(명)통계연도시도명
1인당 공공도서관 장서수(권)1.000-0.162-0.6230.0000.256
공공도서관 총 도서(인쇄) 수(권)-0.1621.0000.8550.0470.220
총인구수(명)-0.6230.8551.0000.0000.283
통계연도0.0000.0470.0001.0000.000
시도명0.2560.2200.2830.0001.000

Missing values

2023-12-12T13:02:36.144807image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-12T13:02:36.309387image/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

통계연도시도명시군구명1인당 공공도서관 장서수(권)공공도서관 총 도서(인쇄) 수(권)총인구수(명)
02017서울특별시종로구7.51160477154770
12017서울특별시중구4.19526971125709
22017서울특별시용산구3.73853811229161
32017서울특별시성동구1.57479499304808
42017서울특별시광진구0.94337735357703
52017서울특별시동대문구1.22428589350647
62017서울특별시중랑구0.84341732408226
72017서울특별시성북구1.3577308444055
82017서울특별시강북구1.27413532324479
92017서울특별시도봉구1.77609326344166
통계연도시도명시군구명1인당 공공도서관 장서수(권)공공도서관 총 도서(인쇄) 수(권)총인구수(명)
10982021경상남도창녕군4.2625637860129
10992021경상남도고성군2.7914084050478
11002021경상남도남해군3.8316194342266
11012021경상남도하동군2.139266843449
11022021경상남도산청군3.7813002634360
11032021경상남도함양군2.559777538310
11042021경상남도거창군3.0118369961073
11052021경상남도합천군2.29466942935
11062021제주특별자치도제주시3.231592359493096
11072021제주특별자치도서귀포시5.961093808183663