Overview

Dataset statistics

Number of variables8
Number of observations429
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory29.5 KiB
Average record size in memory70.3 B

Variable types

Categorical2
Text1
Numeric5

Dataset

Description김해시에서 통계기반 도시현황 파악을 위해 개발한 통계지수 중 하나로서, 통계연도, 시도명, 시군구명, 평균기온(섭씨), 평균최고기온(섭씨), 평균최저기온(섭씨), 최고기온(섭씨), 최저기온(섭씨)으로 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=15110171

Alerts

평균기온(섭씨) is highly overall correlated with 평균최고기온(섭씨) and 2 other fieldsHigh correlation
평균최고기온(섭씨) is highly overall correlated with 평균기온(섭씨)High correlation
평균최저기온(섭씨) is highly overall correlated with 평균기온(섭씨) and 1 other fieldsHigh correlation
최저기온(섭씨) is highly overall correlated with 평균기온(섭씨) and 1 other fieldsHigh correlation

Reproduction

Analysis started2023-12-11 00:04:25.225341
Analysis finished2023-12-11 00:04:28.937085
Duration3.71 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

통계연도
Categorical

Distinct5
Distinct (%)1.2%
Missing0
Missing (%)0.0%
Memory size3.5 KiB
2018
87 
2019
86 
2020
86 
2017
85 
2021
85 

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 (%)
2018 87
20.3%
2019 86
20.0%
2020 86
20.0%
2017 85
19.8%
2021 85
19.8%

Length

2023-12-11T09:04:29.005820image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T09:04:29.125674image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2018 87
20.3%
2019 86
20.0%
2020 86
20.0%
2017 85
19.8%
2021 85
19.8%

시도명
Categorical

Distinct10
Distinct (%)2.3%
Missing0
Missing (%)0.0%
Memory size3.5 KiB
강원도
70 
경상북도
70 
경상남도
69 
전라남도
65 
전라북도
50 
Other values (5)
105 

Length

Max length7
Median length4
Mean length3.9067599
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row강원도
2nd row강원도
3rd row인천광역시
4th row강원도
5th row강원도

Common Values

ValueCountFrequency (%)
강원도 70
16.3%
경상북도 70
16.3%
경상남도 69
16.1%
전라남도 65
15.2%
전라북도 50
11.7%
충청남도 30
7.0%
경기도 25
 
5.8%
충청북도 25
 
5.8%
제주특별자치도 15
 
3.5%
인천광역시 10
 
2.3%

Length

2023-12-11T09:04:29.298102image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T09:04:29.485632image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
강원도 70
16.3%
경상북도 70
16.3%
경상남도 69
16.1%
전라남도 65
15.2%
전라북도 50
11.7%
충청남도 30
7.0%
경기도 25
 
5.8%
충청북도 25
 
5.8%
제주특별자치도 15
 
3.5%
인천광역시 10
 
2.3%
Distinct87
Distinct (%)20.3%
Missing0
Missing (%)0.0%
Memory size3.5 KiB
2023-12-11T09:04:29.849463image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length7
Median length2
Mean length2.1515152
Min length2

Characters and Unicode

Total characters923
Distinct characters84
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks2 ?
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 row대관령
2nd row춘천
3rd row백령도
4th row북강릉
5th row강릉
ValueCountFrequency (%)
대관령 5
 
1.2%
영광 5
 
1.2%
함양 5
 
1.2%
의령 5
 
1.2%
고흥 5
 
1.2%
해남 5
 
1.2%
강진 5
 
1.2%
보성 5
 
1.2%
북창원 5
 
1.2%
순창 5
 
1.2%
Other values (77) 379
88.3%
2023-12-11T09:04:30.361379image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
50
 
5.4%
45
 
4.9%
41
 
4.4%
30
 
3.3%
30
 
3.3%
30
 
3.3%
26
 
2.8%
25
 
2.7%
24
 
2.6%
21
 
2.3%
Other values (74) 601
65.1%

Most occurring categories

ValueCountFrequency (%)
Other Letter 919
99.6%
Open Punctuation 2
 
0.2%
Close Punctuation 2
 
0.2%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
50
 
5.4%
45
 
4.9%
41
 
4.5%
30
 
3.3%
30
 
3.3%
30
 
3.3%
26
 
2.8%
25
 
2.7%
24
 
2.6%
21
 
2.3%
Other values (72) 597
65.0%
Open Punctuation
ValueCountFrequency (%)
( 2
100.0%
Close Punctuation
ValueCountFrequency (%)
) 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 919
99.6%
Common 4
 
0.4%

Most frequent character per script

Hangul
ValueCountFrequency (%)
50
 
5.4%
45
 
4.9%
41
 
4.5%
30
 
3.3%
30
 
3.3%
30
 
3.3%
26
 
2.8%
25
 
2.7%
24
 
2.6%
21
 
2.3%
Other values (72) 597
65.0%
Common
ValueCountFrequency (%)
( 2
50.0%
) 2
50.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 919
99.6%
ASCII 4
 
0.4%

Most frequent character per block

Hangul
ValueCountFrequency (%)
50
 
5.4%
45
 
4.9%
41
 
4.5%
30
 
3.3%
30
 
3.3%
30
 
3.3%
26
 
2.8%
25
 
2.7%
24
 
2.6%
21
 
2.3%
Other values (72) 597
65.0%
ASCII
ValueCountFrequency (%)
( 2
50.0%
) 2
50.0%

평균기온(섭씨)
Real number (ℝ)

HIGH CORRELATION 

Distinct74
Distinct (%)17.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean13.123776
Minimum7.2
Maximum17.5
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size3.9 KiB
2023-12-11T09:04:30.545198image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum7.2
5-th percentile10.68
Q112.2
median13.2
Q314.1
95-th percentile15.5
Maximum17.5
Range10.3
Interquartile range (IQR)1.9

Descriptive statistics

Standard deviation1.5488898
Coefficient of variation (CV)0.11802165
Kurtosis1.1900439
Mean13.123776
Median Absolute Deviation (MAD)1
Skewness-0.33721544
Sum5630.1
Variance2.3990595
MonotonicityNot monotonic
2023-12-11T09:04:30.694524image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
13.3 19
 
4.4%
13.5 17
 
4.0%
13.1 16
 
3.7%
12.7 15
 
3.5%
13.9 14
 
3.3%
13.2 14
 
3.3%
13.4 13
 
3.0%
14.2 11
 
2.6%
12.4 11
 
2.6%
12.0 11
 
2.6%
Other values (64) 288
67.1%
ValueCountFrequency (%)
7.2 1
0.2%
7.3 1
0.2%
7.8 1
0.2%
7.9 1
0.2%
8.1 1
0.2%
9.0 1
0.2%
9.3 1
0.2%
9.5 1
0.2%
9.6 1
0.2%
9.9 1
0.2%
ValueCountFrequency (%)
17.5 1
 
0.2%
17.3 1
 
0.2%
17.0 2
0.5%
16.8 2
0.5%
16.7 2
0.5%
16.2 1
 
0.2%
16.1 2
0.5%
16.0 4
0.9%
15.8 1
 
0.2%
15.7 2
0.5%

평균최고기온(섭씨)
Real number (ℝ)

HIGH CORRELATION 

Distinct65
Distinct (%)15.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean18.661772
Minimum12.5
Maximum21.4
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size3.9 KiB
2023-12-11T09:04:30.870366image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum12.5
5-th percentile16.54
Q118
median18.7
Q319.6
95-th percentile20.5
Maximum21.4
Range8.9
Interquartile range (IQR)1.6

Descriptive statistics

Standard deviation1.3523371
Coefficient of variation (CV)0.072465632
Kurtosis3.1651024
Mean18.661772
Median Absolute Deviation (MAD)0.8
Skewness-1.1664755
Sum8005.9
Variance1.8288155
MonotonicityNot monotonic
2023-12-11T09:04:31.019247image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
18.0 22
 
5.1%
18.7 19
 
4.4%
19.8 16
 
3.7%
19.2 16
 
3.7%
18.5 16
 
3.7%
18.4 15
 
3.5%
19.3 15
 
3.5%
18.9 14
 
3.3%
19.5 14
 
3.3%
19.9 13
 
3.0%
Other values (55) 269
62.7%
ValueCountFrequency (%)
12.5 2
0.5%
13.1 1
 
0.2%
13.3 1
 
0.2%
13.6 1
 
0.2%
14.1 1
 
0.2%
14.5 1
 
0.2%
14.8 1
 
0.2%
14.9 1
 
0.2%
15.0 3
0.7%
15.3 1
 
0.2%
ValueCountFrequency (%)
21.4 1
 
0.2%
21.3 2
 
0.5%
21.2 1
 
0.2%
21.1 2
 
0.5%
21.0 2
 
0.5%
20.9 3
 
0.7%
20.8 1
 
0.2%
20.7 5
1.2%
20.6 2
 
0.5%
20.5 11
2.6%

평균최저기온(섭씨)
Real number (ℝ)

HIGH CORRELATION 

Distinct97
Distinct (%)22.6%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean8.3109557
Minimum2
Maximum14.7
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size3.9 KiB
2023-12-11T09:04:31.199606image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum2
5-th percentile4.9
Q16.7
median8.3
Q39.7
95-th percentile11.9
Maximum14.7
Range12.7
Interquartile range (IQR)3

Descriptive statistics

Standard deviation2.2044764
Coefficient of variation (CV)0.26524944
Kurtosis0.15751918
Mean8.3109557
Median Absolute Deviation (MAD)1.4
Skewness0.22450162
Sum3565.4
Variance4.8597161
MonotonicityNot monotonic
2023-12-11T09:04:31.378766image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
8.3 14
 
3.3%
9.1 12
 
2.8%
7.3 12
 
2.8%
8.5 11
 
2.6%
8.2 10
 
2.3%
8.8 10
 
2.3%
6.6 9
 
2.1%
8.6 8
 
1.9%
7.5 8
 
1.9%
8.7 8
 
1.9%
Other values (87) 327
76.2%
ValueCountFrequency (%)
2.0 2
0.5%
2.7 2
0.5%
2.9 1
0.2%
3.9 2
0.5%
4.0 1
0.2%
4.2 1
0.2%
4.3 1
0.2%
4.5 2
0.5%
4.6 2
0.5%
4.7 1
0.2%
ValueCountFrequency (%)
14.7 1
0.2%
14.4 1
0.2%
14.3 1
0.2%
14.0 2
0.5%
13.9 2
0.5%
13.7 1
0.2%
13.6 2
0.5%
13.4 1
0.2%
13.3 1
0.2%
12.8 1
0.2%

최고기온(섭씨)
Real number (ℝ)

Distinct92
Distinct (%)21.4%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean35.718881
Minimum29.9
Maximum41
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size3.9 KiB
2023-12-11T09:04:31.542949image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum29.9
5-th percentile32.7
Q134.6
median35.7
Q336.8
95-th percentile38.9
Maximum41
Range11.1
Interquartile range (IQR)2.2

Descriptive statistics

Standard deviation1.8492086
Coefficient of variation (CV)0.05177118
Kurtosis0.3900054
Mean35.718881
Median Absolute Deviation (MAD)1.1
Skewness-0.033520827
Sum15323.4
Variance3.4195726
MonotonicityNot monotonic
2023-12-11T09:04:31.773940image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
35.8 18
 
4.2%
35.1 15
 
3.5%
34.5 15
 
3.5%
34.9 14
 
3.3%
36.6 13
 
3.0%
36.5 12
 
2.8%
36.4 12
 
2.8%
36.2 12
 
2.8%
35.5 12
 
2.8%
35.7 11
 
2.6%
Other values (82) 295
68.8%
ValueCountFrequency (%)
29.9 1
0.2%
30.2 1
0.2%
30.5 1
0.2%
30.6 1
0.2%
31.1 1
0.2%
31.2 2
0.5%
31.3 1
0.2%
31.6 1
0.2%
31.7 1
0.2%
31.8 1
0.2%
ValueCountFrequency (%)
41.0 1
0.2%
40.6 1
0.2%
40.4 1
0.2%
40.1 1
0.2%
40.0 1
0.2%
39.9 2
0.5%
39.8 1
0.2%
39.7 1
0.2%
39.6 1
0.2%
39.5 2
0.5%

최저기온(섭씨)
Real number (ℝ)

HIGH CORRELATION 

Distinct178
Distinct (%)41.5%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean12.920047
Minimum0.7
Maximum25.2
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size3.9 KiB
2023-12-11T09:04:31.958417image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0.7
5-th percentile4.14
Q19.6
median13.1
Q316.6
95-th percentile21.16
Maximum25.2
Range24.5
Interquartile range (IQR)7

Descriptive statistics

Standard deviation5.0093528
Coefficient of variation (CV)0.38771941
Kurtosis-0.42353904
Mean12.920047
Median Absolute Deviation (MAD)3.5
Skewness-0.096857566
Sum5542.7
Variance25.093616
MonotonicityNot monotonic
2023-12-11T09:04:32.137408image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
12.6 9
 
2.1%
10.9 8
 
1.9%
14.6 8
 
1.9%
15.9 7
 
1.6%
17.4 7
 
1.6%
16.3 6
 
1.4%
11.3 6
 
1.4%
8.3 5
 
1.2%
10.0 5
 
1.2%
10.2 5
 
1.2%
Other values (168) 363
84.6%
ValueCountFrequency (%)
0.7 1
0.2%
1.1 1
0.2%
1.2 1
0.2%
1.3 1
0.2%
1.4 2
0.5%
1.6 1
0.2%
2.0 1
0.2%
2.1 1
0.2%
2.7 2
0.5%
2.8 2
0.5%
ValueCountFrequency (%)
25.2 1
0.2%
24.4 1
0.2%
24.3 1
0.2%
24.1 1
0.2%
24.0 1
0.2%
23.5 1
0.2%
22.8 1
0.2%
22.5 1
0.2%
22.4 1
0.2%
21.9 1
0.2%

Interactions

2023-12-11T09:04:28.211712image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T09:04:25.594615image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T09:04:26.132308image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T09:04:26.583036image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T09:04:27.587311image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/