Overview

Dataset statistics

Number of variables8
Number of observations1140
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory78.1 KiB
Average record size in memory70.1 B

Variable types

Categorical2
Text1
Numeric5

Dataset

Description김해시에서 통계기반 도시현황 파악을 위해 개발한 통계지수 중 하나로서, 통계연도, 시도명, 시군구명, 학급당 학생수(명), 유치원(명), 초등학교(명), 중학교(명), 고등학교(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/15110183/fileData.do

Alerts

학급당 학생수(명) is highly overall correlated with 유치원(명) and 3 other fieldsHigh correlation
유치원(명) is highly overall correlated with 학급당 학생수(명) and 3 other fieldsHigh correlation
초등학교(명) is highly overall correlated with 학급당 학생수(명) and 3 other fieldsHigh correlation
중학교(명) is highly overall correlated with 학급당 학생수(명) and 3 other fieldsHigh correlation
고등학교(명) is highly overall correlated with 학급당 학생수(명) and 3 other fieldsHigh correlation

Reproduction

Analysis started2023-12-12 11:23:28.829404
Analysis finished2023-12-12 11:23:34.021676
Duration5.19 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

통계연도
Categorical

Distinct5
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Memory size9.0 KiB
2017
228 
2018
228 
2019
228 
2020
228 
2021
228 

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 (%)
2017 228
20.0%
2018 228
20.0%
2019 228
20.0%
2020 228
20.0%
2021 228
20.0%

Length

2023-12-12T20:23:34.138179image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T20:23:34.322822image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2017 228
20.0%
2018 228
20.0%
2019 228
20.0%
2020 228
20.0%
2021 228
20.0%

시도명
Categorical

Distinct16
Distinct (%)1.4%
Missing0
Missing (%)0.0%
Memory size9.0 KiB
경기도
155 
서울특별시
125 
경상북도
115 
전라남도
110 
강원도
90 
Other values (11)
545 

Length

Max length7
Median length5
Mean length4.1359649
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
경기도 155
13.6%
서울특별시 125
11.0%
경상북도 115
10.1%
전라남도 110
9.6%
강원도 90
7.9%
경상남도 90
7.9%
부산광역시 80
7.0%
충청남도 75
6.6%
전라북도 70
 
6.1%
충청북도 55
 
4.8%
Other values (6) 175
15.4%

Length

2023-12-12T20:23:34.541939image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
경기도 155
13.6%
서울특별시 125
11.0%
경상북도 115
10.1%
전라남도 110
9.6%
강원도 90
7.9%
경상남도 90
7.9%
부산광역시 80
7.0%
충청남도 75
6.6%
전라북도 70
 
6.1%
충청북도 55
 
4.8%
Other values (6) 175
15.4%

시군구명
Text

Distinct206
Distinct (%)18.1%
Missing0
Missing (%)0.0%
Memory size9.0 KiB
2023-12-12T20:23:35.048917image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length4
Median length3
Mean length2.9307018
Min length2

Characters and Unicode

Total characters3341
Distinct characters132
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
 
2.6%
중구 30
 
2.6%
서구 25
 
2.2%
남구 22
 
1.9%
북구 20
 
1.8%
고성군 10
 
0.9%
강서구 10
 
0.9%
완주군 5
 
0.4%
무주군 5
 
0.4%
진안군 5
 
0.4%
Other values (196) 978
85.8%
2023-12-12T20:23:35.768181image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
군 425
 
12.7%
시 390
 
11.7%
구 370
 
11.1%
천 110
 
3.3%
주 100
 
3.0%
성 90
 
2.7%
양 90
 
2.7%
동 85
 
2.5%
산 80
 
2.4%
서 65
 
1.9%
Other values (122) 1536
46.0%

Most occurring categories

ValueCountFrequency (%)
Other Letter 3341
100.0%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
군 425
 
12.7%
시 390
 
11.7%
구 370
 
11.1%
천 110
 
3.3%
주 100
 
3.0%
성 90
 
2.7%
양 90
 
2.7%
동 85
 
2.5%
산 80
 
2.4%
서 65
 
1.9%
Other values (122) 1536
46.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 3341
100.0%

Most frequent character per script

Hangul
ValueCountFrequency (%)
군 425
 
12.7%
시 390
 
11.7%
구 370
 
11.1%
천 110
 
3.3%
주 100
 
3.0%
성 90
 
2.7%
양 90
 
2.7%
동 85
 
2.5%
산 80
 
2.4%
서 65
 
1.9%
Other values (122) 1536
46.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 3341
100.0%

Most frequent character per block

Hangul
ValueCountFrequency (%)
군 425
 
12.7%
시 390
 
11.7%
구 370
 
11.1%
천 110
 
3.3%
주 100
 
3.0%
성 90
 
2.7%
양 90
 
2.7%
동 85
 
2.5%
산 80
 
2.4%
서 65
 
1.9%
Other values (122) 1536
46.0%

학급당 학생수(명)
Real number (ℝ)

HIGH CORRELATION 

Distinct765
Distinct (%)67.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean19.911421
Minimum8.91
Maximum27.95
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size10.1 KiB
2023-12-12T20:23:35.980932image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum8.91
5-th percentile12.2465
Q116.0825
median21.425
Q323.45
95-th percentile25.2015
Maximum27.95
Range19.04
Interquartile range (IQR)7.3675

Descriptive statistics

Standard deviation4.3623226
Coefficient of variation (CV)0.21908645
Kurtosis-0.93411874
Mean19.911421
Median Absolute Deviation (MAD)2.805
Skewness-0.55794145
Sum22699.02
Variance19.029858
MonotonicityNot monotonic
2023-12-12T20:23:36.220922image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
21.96 6
 
0.5%
23.56 5
 
0.4%
24.24 4
 
0.4%
24.12 4
 
0.4%
24.78 4
 
0.4%
24.39 4
 
0.4%
22.86 4
 
0.4%
21.92 4
 
0.4%
23.21 4
 
0.4%
22.28 4
 
0.4%
Other values (755) 1097
96.2%
ValueCountFrequency (%)
8.91 1
0.1%
8.98 1
0.1%
9.15 1
0.1%
9.45 1
0.1%
9.74 1
0.1%
9.84 1
0.1%
9.89 1
0.1%
10.0 1
0.1%
10.02 1
0.1%
10.47 1
0.1%
ValueCountFrequency (%)
27.95 1
0.1%
27.43 1
0.1%
27.3 1
0.1%
26.68 1
0.1%
26.56 1
0.1%
26.5 1
0.1%
26.46 2
0.2%
26.43 1
0.1%
26.38 1
0.1%
26.37 1
0.1%

유치원(명)
Real number (ℝ)

HIGH CORRELATION 

Distinct789
Distinct (%)69.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean15.52536
Minimum5
Maximum25.55
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size10.1 KiB
2023-12-12T20:23:36.462197image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum5
5-th percentile8.6495
Q112.415
median16.165
Q318.6025
95-th percentile21.38
Maximum25.55
Range20.55
Interquartile range (IQR)6.1875

Descriptive statistics

Standard deviation3.9850697
Coefficient of variation (CV)0.25668131
Kurtosis-0.7394038
Mean15.52536
Median Absolute Deviation (MAD)2.945
Skewness-0.29075268
Sum17698.91
Variance15.880781
MonotonicityNot monotonic
2023-12-12T20:23:36.704163image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
9.8 5
 
0.4%
18.6 5
 
0.4%
16.16 4
 
0.4%
17.93 4
 
0.4%
19.47 4
 
0.4%
17.18 4
 
0.4%
18.13 4
 
0.4%
12.0 4
 
0.4%
19.1 4
 
0.4%
18.01 4
 
0.4%
Other values (779) 1098
96.3%
ValueCountFrequency (%)
5.0 1
0.1%
5.95 1
0.1%
6.08 1
0.1%
6.13 1
0.1%
6.2 1
0.1%
6.26 1
0.1%
6.33 1
0.1%
6.37 1
0.1%
6.55 1
0.1%
6.6 1
0.1%
ValueCountFrequency (%)
25.55 1
0.1%
25.18 1
0.1%
24.21 1
0.1%
24.16 1
0.1%
24.02 1
0.1%
23.36 1
0.1%
23.08 1
0.1%
23.07 1
0.1%
23.04 1
0.1%
22.85 1
0.1%

초등학교(명)
Real number (ℝ)

HIGH CORRELATION 

Distinct806
Distinct (%)70.7%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean18.716947
Minimum7.42
Maximum27.43
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size10.1 KiB
2023-12-12T20:23:37.401054image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum7.42
5-th percentile10.0595
Q113.9675
median20.395
Q322.8525
95-th percentile25.2205
Maximum27.43
Range20.01
Interquartile range (IQR)8.885

Descriptive statistics

Standard deviation5.0524964
Coefficient of variation (CV)0.26994233
Kurtosis-1.1168543
Mean18.716947
Median Absolute Deviation (MAD)3.34
Skewness-0.47771619
Sum21337.32
Variance25.52772
MonotonicityNot monotonic
2023-12-12T20:23:37.630778image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
22.76 6
 
0.5%
23.22 5
 
0.4%
22.09 4
 
0.4%
23.44 4
 
0.4%
22.97 4
 
0.4%
20.11 4
 
0.4%
22.64 4
 
0.4%
23.19 4
 
0.4%
22.04 4
 
0.4%
20.97 4
 
0.4%
Other values (796) 1097
96.2%
ValueCountFrequency (%)
7.42 1
0.1%
7.56 1
0.1%
7.58 1
0.1%
7.67 1
0.1%
7.85 1
0.1%
8.03 1
0.1%
8.18 1
0.1%
8.29 1
0.1%
8.41 1
0.1%
8.49 1
0.1%
ValueCountFrequency (%)
27.43 1
0.1%
27.18 1
0.1%
26.76 1
0.1%
26.49 1
0.1%
26.31 1
0.1%
26.24 1
0.1%
26.23 1
0.1%
26.2 1
0.1%
26.18 2
0.2%
26.17 1
0.1%

중학교(명)
Real number (ℝ)

HIGH CORRELATION 

Distinct820
Distinct (%)71.9%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean22.523658
Minimum9.36
Maximum32.11
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size10.1 KiB
2023-12-12T20:23:37.858241image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum9.36
5-th percentile14.16
Q119.165
median23.39
Q325.9525
95-th percentile29.0605
Maximum32.11
Range22.75
Interquartile range (IQR)6.7875

Descriptive statistics

Standard deviation4.7263822
Coefficient of variation (CV)0.20984079
Kurtosis-0.41156346
Mean22.523658
Median Absolute Deviation (MAD)3.19
Skewness-0.511028
Sum25676.97
Variance22.338689
MonotonicityNot monotonic
2023-12-12T20:23:38.077381image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
25.37 5
 
0.4%
15.26 4
 
0.4%
21.51 4
 
0.4%
23.99 4
 
0.4%
23.56 4
 
0.4%
24.9 4
 
0.4%
22.51 4
 
0.4%
26.24 4
 
0.4%
23.31 4
 
0.4%
23.2 4
 
0.4%
Other values (810) 1099
96.4%
ValueCountFrequency (%)
9.36 1
0.1%
9.45 1
0.1%
9.52 1
0.1%
9.67 1
0.1%
9.69 1
0.1%
9.98 1
0.1%
10.23 1
0.1%
10.25 1
0.1%
10.37 1
0.1%
10.5 1
0.1%
ValueCountFrequency (%)
32.11 1
0.1%
31.83 1
0.1%
31.7 2
0.2%
31.68 1
0.1%
31.44 1
0.1%
31.42 1
0.1%
31.3 1
0.1%
31.1 1
0.1%
31.01 1
0.1%
30.86 1
0.1%

고등학교(명)
Real number (ℝ)

HIGH CORRELATION 

Distinct773
Distinct (%)67.8%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean23.06643
Minimum6.1
Maximum33.59
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size10.1 KiB
2023-12-12T20:23:38.311039image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum6.1
5-th percentile16.059
Q120.3975
median23.29
Q325.8475
95-th percentile29.441
Maximum33.59
Range27.49
Interquartile range (IQR)5.45

Descriptive statistics

Standard deviation4.1205757
Coefficient of variation (CV)0.17863951
Kurtosis0.23225678
Mean23.06643
Median Absolute Deviation (MAD)2.71
Skewness-0.29716585
Sum26295.73
Variance16.979144
MonotonicityNot monotonic
2023-12-12T20:23:38.587445image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
23.52 5
 
0.4%
23.58 5
 
0.4%
22.44 5
 
0.4%
24.27 5
 
0.4%
24.25 5
 
0.4%
24.08 4
 
0.4%
23.86 4
 
0.4%
23.29 4
 
0.4%
25.52 4
 
0.4%
23.98 4
 
0.4%
Other values (763) 1095
96.1%
ValueCountFrequency (%)
6.1 1
0.1%
7.6 1
0.1%
7.67 1
0.1%
9.41 1
0.1%
10.48 1
0.1%
10.7 1
0.1%
10.89 1
0.1%
11.1 1
0.1%
11.32 1
0.1%
12.58 1
0.1%
ValueCountFrequency (%)
33.59 1
0.1%
33.5 1
0.1%
33.26 1
0.1%
33.15 1
0.1%
32.66 1
0.1%
32.6 1
0.1%
32.04 1
0.1%
32.03 1
0.1%
31.88 1
0.1%
31.8 1
0.1%

Interactions

2023-12-12T20:23:32.826550image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T20:23:29.446118image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T20:23:30.389664image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T20:23:31.180899image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T20:23:32.052710image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T20:23:33.010465image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T20:23:29.640924image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T20:23:30.561538image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T20:23:31.390148image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T20:23:32.210179image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T20:23:33.162421image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T20:23:29.828369image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T20:23:30.709418image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T20:23:31.531740image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T20:23:32.363227image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T20:23:33.330543image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T20:23:30.042520image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T20:23:30.897297image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T20:23:31.713128image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T20:23:32.543237image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T20:23:33.467196image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T20:23:30.217937image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T20:23:31.038901image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T20:23:31.888440image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T20:23:32.687329image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-12T20:23:38.783690image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
통계연도시도명학급당 학생수(명)유치원(명)초등학교(명)중학교(명)고등학교(명)
통계연도1.0000.0000.3310.3290.0000.0000.542
시도명0.0001.0000.5700.5900.6360.6740.473
학급당 학생수(명)0.3310.5701.0000.7720.9420.9050.825
유치원(명)0.3290.5900.7721.0000.7570.7020.632
초등학교(명)0.0000.6360.9420.7571.0000.8650.727
중학교(명)0.0000.6740.9050.7020.8651.0000.751
고등학교(명)0.5420.4730.8250.6320.7270.7511.000
2023-12-12T20:23:39.009139image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
통계연도시도명
통계연도1.0000.000
시도명0.0001.000
2023-12-12T20:23:39.173666image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
학급당 학생수(명)유치원(명)초등학교(명)중학교(명)고등학교(명)통계연도시도명
학급당 학생수(명)1.0000.8070.9650.9270.8400.1430.264
유치원(명)0.8071.0000.7500.6690.6680.1430.276
초등학교(명)0.9650.7501.0000.9060.7310.0000.310
중학교(명)0.9270.6690.9061.0000.7500.0000.340
고등학교(명)0.8400.6680.7310.7501.0000.2540.206
통계연도0.1430.1430.0000.0000.2541.0000.000
시도명0.2640.2760.3100.3400.2060.0001.000

Missing values

2023-12-12T20:23:33.663681image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-12T20:23:33.920266image/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

통계연도시도명시군구명학급당 학생수(명)유치원(명)초등학교(명)중학교(명)고등학교(명)
02017서울특별시종로구24.620.3120.1523.2929.02
12017서울특별시중구22.4716.0521.3918.1626.66
22017서울특별시용산구23.2421.1621.2423.2326.51
32017서울특별시성동구22.5722.1720.7323.825.97
42017서울특별시광진구25.3823.0823.0526.0630.65
52017서울특별시동대문구24.1319.9322.8724.4628.33
62017서울특별시중랑구23.4320.5222.0324.7326.97
72017서울특별시성북구24.7920.5424.1426.0527.84
82017서울특별시강북구24.8418.523.0527.3428.7
92017서울특별시도봉구23.4619.5322.3725.0826.31
통계연도시도명시군구명학급당 학생수(명)유치원(명)초등학교(명)중학교(명)고등학교(명)
11302021경상남도창녕군15.5312.2213.7518.5217.92
11312021경상남도고성군15.167.5213.0718.8419.32
11322021경상남도남해군14.1911.3511.4316.2117.78
11332021경상남도하동군12.386.3710.1617.6316.36
11342021경상남도산청군12.538.949.0917.3617.6
11352021경상남도함양군13.8612.9111.6617.9615.83
11362021경상남도거창군17.7512.7715.9121.5920.07
11372021경상남도합천군11.5110.169.0715.9814.26
11382021제주특별자치도제주시24.6222.2223.4726.7826.2
11392021제주특별자치도서귀포시21.0617.2119.3725.1123.11