Overview

Dataset statistics

Number of variables6
Number of observations1247
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory63.5 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, 대상인원(명), 수검인원(명), 암검진수검률(퍼센트)로 구성되어 있습니다. 김해시 중심의 통계지수로서, 데이터 수집, 가공 등의 어려움으로 김해시 외 지역의 정보는 누락될 수 있습니다.
Author경상남도 김해시
URLhttps://bigdata.gyeongnam.go.kr/index.gn?menuCd=DOM_000000114002001000&publicdatapk=15110154

Alerts

대상인원(명) is highly overall correlated with 수검인원(명)High correlation
수검인원(명) is highly overall correlated with 대상인원(명)High correlation

Reproduction

Analysis started2023-12-11 00:07:13.556978
Analysis finished2023-12-11 00:07:15.362843
Duration1.81 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

통계연도
Categorical

Distinct5
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Memory size9.9 KiB
2016
251 
2017
249 
2018
249 
2019
249 
2020
249 

Length

Max length4
Median length4
Mean length4
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row2016
2nd row2016
3rd row2016
4th row2016
5th row2016

Common Values

ValueCountFrequency (%)
2016 251
20.1%
2017 249
20.0%
2018 249
20.0%
2019 249
20.0%
2020 249
20.0%

Length

2023-12-11T09:07:15.445330image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T09:07:15.557117image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2016 251
20.1%
2017 249
20.0%
2018 249
20.0%
2019 249
20.0%
2020 249
20.0%

시도명
Categorical

Distinct16
Distinct (%)1.3%
Missing0
Missing (%)0.0%
Memory size9.9 KiB
경기도
212 
서울특별시
125 
경상북도
120 
전라남도
110 
경상남도
110 
Other values (11)
570 

Length

Max length7
Median length5
Mean length4.0785886
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
경기도 212
17.0%
서울특별시 125
10.0%
경상북도 120
9.6%
전라남도 110
8.8%
경상남도 110
8.8%
강원도 90
7.2%
부산광역시 80
 
6.4%
충청남도 80
 
6.4%
전라북도 75
 
6.0%
충청북도 70
 
5.6%
Other values (6) 175
14.0%

Length

2023-12-11T09:07:15.678751image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
경기도 212
17.0%
서울특별시 125
10.0%
경상북도 120
9.6%
전라남도 110
8.8%
경상남도 110
8.8%
강원도 90
7.2%
부산광역시 80
 
6.4%
충청남도 80
 
6.4%
전라북도 75
 
6.0%
충청북도 70
 
5.6%
Other values (6) 175
14.0%
Distinct231
Distinct (%)18.5%
Missing0
Missing (%)0.0%
Memory size9.9 KiB
2023-12-11T09:07:16.002579image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length9
Median length3
Mean length3.3680834
Min length2

Characters and Unicode

Total characters4200
Distinct characters143
Distinct categories2 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique4 ?
Unique (%)0.3%

Sample

1st row종로구
2nd row중구
3rd row용산구
4th row성동구
5th row광진구
ValueCountFrequency (%)
동구 30
 
2.4%
중구 30
 
2.4%
창원시 25
 
2.0%
서구 25
 
2.0%
북구 20
 
1.6%
남구 20
 
1.6%
고성군 10
 
0.8%
강서구 10
 
0.8%
무주군 5
 
0.4%
진안군 5
 
0.4%
Other values (222) 1092
85.8%
2023-12-11T09:07:16.511030image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
533
 
12.7%
493
 
11.7%
429
 
10.2%
120
 
2.9%
117
 
2.8%
115
 
2.7%
110
 
2.6%
105
 
2.5%
100
 
2.4%
91
 
2.2%
Other values (133) 1987
47.3%

Most occurring categories

ValueCountFrequency (%)
Other Letter 4175
99.4%
Space Separator 25
 
0.6%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
533
 
12.8%
493
 
11.8%
429
 
10.3%
120
 
2.9%
117
 
2.8%
115
 
2.8%
110
 
2.6%
105
 
2.5%
100
 
2.4%
91
 
2.2%
Other values (132) 1962
47.0%
Space Separator
ValueCountFrequency (%)
25
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 4175
99.4%
Common 25
 
0.6%

Most frequent character per script

Hangul
ValueCountFrequency (%)
533
 
12.8%
493
 
11.8%
429
 
10.3%
120
 
2.9%
117
 
2.8%
115
 
2.8%
110
 
2.6%
105
 
2.5%
100
 
2.4%
91
 
2.2%
Other values (132) 1962
47.0%
Common
ValueCountFrequency (%)
25
100.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 4175
99.4%
ASCII 25
 
0.6%

Most frequent character per block

Hangul
ValueCountFrequency (%)
533
 
12.8%
493
 
11.8%
429
 
10.3%
120
 
2.9%
117
 
2.8%
115
 
2.8%
110
 
2.6%
105
 
2.5%
100
 
2.4%
91
 
2.2%
Other values (132) 1962
47.0%
ASCII
ValueCountFrequency (%)
25
100.0%

대상인원(명)
Real number (ℝ)

HIGH CORRELATION 

Distinct1234
Distinct (%)99.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean90359.488
Minimum5063
Maximum381090
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size11.1 KiB
2023-12-11T09:07:16.655786image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum5063
5-th percentile15021.3
Q131254.5
median77885
Q3134868
95-th percentile209276.6
Maximum381090
Range376027
Interquartile range (IQR)103613.5

Descriptive statistics

Standard deviation66693.186
Coefficient of variation (CV)0.73808725
Kurtosis0.43864653
Mean90359.488
Median Absolute Deviation (MAD)50169
Skewness0.87731996
Sum1.1267828 × 108
Variance4.4479811 × 109
MonotonicityNot monotonic
2023-12-11T09:07:16.825183image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
27534 2
 
0.2%
19776 2
 
0.2%
45045 2
 
0.2%
121321 2
 
0.2%
42702 2
 
0.2%
18681 2
 
0.2%
31742 2
 
0.2%
21883 2
 
0.2%
126759 2
 
0.2%
5361 2
 
0.2%
Other values (1224) 1227
98.4%
ValueCountFrequency (%)
5063 1
0.1%
5305 1
0.1%
5361 2
0.2%
5411 1
0.1%
9747 1
0.1%
9912 1
0.1%
9981 1
0.1%
10044 1
0.1%
10059 1
0.1%
10143 1
0.1%
ValueCountFrequency (%)
381090 1
0.1%
372436 1
0.1%
371574 1
0.1%
371372 1
0.1%
309343 1
0.1%
294929 1
0.1%
290105 1
0.1%
289805 1
0.1%
287134 1
0.1%
286360 1
0.1%

수검인원(명)
Real number (ℝ)

HIGH CORRELATION 

Distinct1236
Distinct (%)99.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean46778.204
Minimum1957
Maximum223191
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size11.1 KiB
2023-12-11T09:07:16.994933image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1957
5-th percentile7819.9
Q115661
median39212
Q371660.5
95-th percentile111608.1
Maximum223191
Range221234
Interquartile range (IQR)55999.5

Descriptive statistics

Standard deviation35002.132
Coefficient of variation (CV)0.74825729
Kurtosis0.72004472
Mean46778.204
Median Absolute Deviation (MAD)25667
Skewness0.92995426
Sum58332420
Variance1.2251492 × 109
MonotonicityNot monotonic
2023-12-11T09:07:17.164792image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
14893 2
 
0.2%
11498 2
 
0.2%
26053 2
 
0.2%
43242 2
 
0.2%
82576 2
 
0.2%
10129 2
 
0.2%
12837 2
 
0.2%
21116 2
 
0.2%
8037 2
 
0.2%
7305 2
 
0.2%
Other values (1226) 1227
98.4%
ValueCountFrequency (%)
1957 1
0.1%
2229 1
0.1%
2677 1
0.1%
2720 1
0.1%
2857 1
0.1%
4377 1
0.1%
4557 1
0.1%
4576 1
0.1%
4585 1
0.1%
4664 1
0.1%
ValueCountFrequency (%)
223191 1
0.1%
210318 1
0.1%
189354 1
0.1%
185331 1
0.1%
163754 1
0.1%
162481 1
0.1%
154184 1
0.1%
152597 1
0.1%
150940 1
0.1%
146923 1
0.1%
Distinct838
Distinct (%)67.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean51.536592
Minimum38.65
Maximum64.04
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size11.1 KiB
2023-12-11T09:07:17.328841image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum38.65
5-th percentile44.923
Q148.575
median51.61
Q354.555
95-th percentile58.041
Maximum64.04
Range25.39
Interquartile range (IQR)5.98

Descriptive statistics

Standard deviation4.0569495
Coefficient of variation (CV)0.078719786
Kurtosis-0.32687305
Mean51.536592
Median Absolute Deviation (MAD)3.01
Skewness-0.024171567
Sum64266.13
Variance16.458839
MonotonicityNot monotonic
2023-12-11T09:07:17.513998image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
48.56 6
 
0.5%
52.83 5
 
0.4%
48.3 4
 
0.3%
47.3 4
 
0.3%
49.73 4
 
0.3%
54.64 4
 
0.3%
49.49 4
 
0.3%
53.12 4
 
0.3%
49.3 4
 
0.3%
49.64 4
 
0.3%
Other values (828) 1204
96.6%
ValueCountFrequency (%)
38.65 1
0.1%
40.07 1
0.1%
40.87 1
0.1%
40.88 1
0.1%
41.13 1
0.1%
41.52 1
0.1%
41.59 1
0.1%
41.63 1
0.1%
41.75 1
0.1%
41.79 1
0.1%
ValueCountFrequency (%)
64.04 1
0.1%
62.95 1
0.1%
61.78 1
0.1%
61.62 1
0.1%
61.45 1
0.1%
61.26 1
0.1%
61.12 1
0.1%
61.02 1
0.1%
60.87 1
0.1%
60.86 1
0.1%

Interactions

2023-12-11T09:07:14.557723image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T09:07:13.906985image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T09:07:14.241594image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T09:07:14.654566image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T09:07:14.018315image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T09:07:14.350070image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T09:07:15.019326image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/