Overview

Dataset statistics

Number of variables11
Number of observations53
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory4.8 KiB
Average record size in memory93.5 B

Variable types

Numeric3
Categorical5
Text1
DateTime2

Dataset

Description이 데이터는 2023년 4월 24일 기준으로 남원시 그늘막에 대한 설치장소, 그늘막유형, 설치년월 등의 데이터입니다.
URLhttps://www.data.go.kr/data/15113474/fileData.do

Alerts

시도 has constant value ""Constant
시군구 has constant value ""Constant
데이터기준일자 has constant value ""Constant
그늘막지름 is highly overall correlated with 그늘막유형High correlation
그늘막유형 is highly overall correlated with 그늘막지름High correlation
연번 is highly overall correlated with 위도 and 2 other fieldsHigh correlation
위도 is highly overall correlated with 연번 and 2 other fieldsHigh correlation
경도 is highly overall correlated with 연번 and 2 other fieldsHigh correlation
읍면동 is highly overall correlated with 연번 and 2 other fieldsHigh correlation
그늘막유형 is highly imbalanced (86.5%)Imbalance
연번 has unique valuesUnique

Reproduction

Analysis started2023-12-12 08:56:32.265471
Analysis finished2023-12-12 08:56:34.298433
Duration2.03 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

연번
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct53
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean27
Minimum1
Maximum53
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size609.0 B
2023-12-12T17:56:34.401021image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile3.6
Q114
median27
Q340
95-th percentile50.4
Maximum53
Range52
Interquartile range (IQR)26

Descriptive statistics

Standard deviation15.443445
Coefficient of variation (CV)0.57197945
Kurtosis-1.2
Mean27
Median Absolute Deviation (MAD)13
Skewness0
Sum1431
Variance238.5
MonotonicityStrictly increasing
2023-12-12T17:56:34.603905image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1 1
 
1.9%
41 1
 
1.9%
30 1
 
1.9%
31 1
 
1.9%
32 1
 
1.9%
33 1
 
1.9%
34 1
 
1.9%
35 1
 
1.9%
36 1
 
1.9%
37 1
 
1.9%
Other values (43) 43
81.1%
ValueCountFrequency (%)
1 1
1.9%
2 1
1.9%
3 1
1.9%
4 1
1.9%
5 1
1.9%
6 1
1.9%
7 1
1.9%
8 1
1.9%
9 1
1.9%
10 1
1.9%
ValueCountFrequency (%)
53 1
1.9%
52 1
1.9%
51 1
1.9%
50 1
1.9%
49 1
1.9%
48 1
1.9%
47 1
1.9%
46 1
1.9%
45 1
1.9%
44 1
1.9%

시도
Categorical

CONSTANT 

Distinct1
Distinct (%)1.9%
Missing0
Missing (%)0.0%
Memory size556.0 B
전라북도
53 

Length

Max length4
Median length4
Mean length4
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
전라북도 53
100.0%

Length

2023-12-12T17:56:34.765053image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T17:56:34.881535image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
전라북도 53
100.0%

시군구
Categorical

CONSTANT 

Distinct1
Distinct (%)1.9%
Missing0
Missing (%)0.0%
Memory size556.0 B
남원시
53 

Length

Max length3
Median length3
Mean length3
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
남원시 53
100.0%

Length

2023-12-12T17:56:35.021631image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T17:56:35.139597image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
남원시 53
100.0%

읍면동
Categorical

HIGH CORRELATION 

Distinct6
Distinct (%)11.3%
Missing0
Missing (%)0.0%
Memory size556.0 B
도통동
23 
향교동
13 
금동
9 
왕정동
4 
죽항동
 
2

Length

Max length3
Median length3
Mean length2.8301887
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
도통동 23
43.4%
향교동 13
24.5%
금동 9
 
17.0%
왕정동 4
 
7.5%
죽항동 2
 
3.8%
노암동 2
 
3.8%

Length

2023-12-12T17:56:35.257332image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T17:56:35.383332image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
도통동 23
43.4%
향교동 13
24.5%
금동 9
 
17.0%
왕정동 4
 
7.5%
죽항동 2
 
3.8%
노암동 2
 
3.8%

설치장소명
Text

Distinct48
Distinct (%)90.6%
Missing0
Missing (%)0.0%
Memory size556.0 B
2023-12-12T17:56:35.638659image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length16
Median length12
Mean length9.9811321
Min length5

Characters and Unicode

Total characters529
Distinct characters135
Distinct categories5 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique43 ?
Unique (%)81.1%

Sample

1st row도통동 인도교 모정 앞
2nd row도통동 도통우체국 건너편
3rd row도통동 새마을금고 앞
4th row도통동 영진약국 앞
5th row도통동 홍도막걸리앞
ValueCountFrequency (%)
앞 28
20.3%
사거리 8
 
5.8%
도통동 7
 
5.1%
교통섬 6
 
4.3%
정문 5
 
3.6%
맞은편 4
 
2.9%
건너편 3
 
2.2%
금동 3
 
2.2%
승사교 3
 
2.2%
횡단보도 2
 
1.4%
Other values (54) 69
50.0%
2023-12-12T17:56:36.082143image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
89
 
16.8%
앞 34
 
6.4%
교 22
 
4.2%
리 21
 
4.0%
사 19
 
3.6%
통 17
 
3.2%
거 17
 
3.2%
동 16
 
3.0%
도 16
 
3.0%
원 15
 
2.8%
Other values (125) 263
49.7%

Most occurring categories

ValueCountFrequency (%)
Other Letter 436
82.4%
Space Separator 89
 
16.8%
Uppercase Letter 2
 
0.4%
Open Punctuation 1
 
0.2%
Close Punctuation 1
 
0.2%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
앞 34
 
7.8%
교 22
 
5.0%
리 21
 
4.8%
사 19
 
4.4%
통 17
 
3.9%
거 17
 
3.9%
동 16
 
3.7%
도 16
 
3.7%
원 15
 
3.4%
편 8
 
1.8%
Other values (120) 251
57.6%
Uppercase Letter
ValueCountFrequency (%)
S 1
50.0%
G 1
50.0%
Space Separator
ValueCountFrequency (%)
89
100.0%
Open Punctuation
ValueCountFrequency (%)
( 1
100.0%
Close Punctuation
ValueCountFrequency (%)
) 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 436
82.4%
Common 91
 
17.2%
Latin 2
 
0.4%

Most frequent character per script

Hangul
ValueCountFrequency (%)
앞 34
 
7.8%
교 22
 
5.0%
리 21
 
4.8%
사 19
 
4.4%
통 17
 
3.9%
거 17
 
3.9%
동 16
 
3.7%
도 16
 
3.7%
원 15
 
3.4%
편 8
 
1.8%
Other values (120) 251
57.6%
Common
ValueCountFrequency (%)
89
97.8%
( 1
 
1.1%
) 1
 
1.1%
Latin
ValueCountFrequency (%)
S 1
50.0%
G 1
50.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 436
82.4%
ASCII 93
 
17.6%

Most frequent character per block

ASCII
ValueCountFrequency (%)
89
95.7%
( 1
 
1.1%
) 1
 
1.1%
S 1
 
1.1%
G 1
 
1.1%
Hangul
ValueCountFrequency (%)
앞 34
 
7.8%
교 22
 
5.0%
리 21
 
4.8%
사 19
 
4.4%
통 17
 
3.9%
거 17
 
3.9%
동 16
 
3.7%
도 16
 
3.7%
원 15
 
3.4%
편 8
 
1.8%
Other values (120) 251
57.6%

그늘막유형
Categorical

HIGH CORRELATION  IMBALANCE 

Distinct2
Distinct (%)3.8%
Missing0
Missing (%)0.0%
Memory size556.0 B
고정형
52 
스마트형
 
1

Length

Max length4
Median length3
Mean length3.0188679
Min length3

Unique

Unique1 ?
Unique (%)1.9%

Sample

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

Common Values

ValueCountFrequency (%)
고정형 52
98.1%
스마트형 1
 
1.9%

Length

2023-12-12T17:56:36.280811image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T17:56:36.403702image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
고정형 52
98.1%
스마트형 1
 
1.9%

그늘막지름
Categorical

HIGH CORRELATION 

Distinct5
Distinct (%)9.4%
Missing0
Missing (%)0.0%
Memory size556.0 B
5M
41 
3M
6 
3.5M
 
3
4M
 
2
5.4M
 
1

Length

Max length4
Median length2
Mean length2.1509434
Min length2

Unique

Unique1 ?
Unique (%)1.9%

Sample

1st row5M
2nd row5M
3rd row5M
4th row5M
5th row5M

Common Values

ValueCountFrequency (%)
5M 41
77.4%
3M 6
 
11.3%
3.5M 3
 
5.7%
4M 2
 
3.8%
5.4M 1
 
1.9%

Length

2023-12-12T17:56:36.572549image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T17:56:36.743418image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
5m 41
77.4%
3m 6
 
11.3%
3.5m 3
 
5.7%
4m 2
 
3.8%
5.4m 1
 
1.9%

위도
Real number (ℝ)

HIGH CORRELATION 

Distinct45
Distinct (%)84.9%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean35.413206
Minimum35.3992
Maximum35.4228
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size609.0 B
2023-12-12T17:56:36.926251image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum35.3992
5-th percentile35.40086
Q135.4083
median35.4153
Q335.4174
95-th percentile35.42236
Maximum35.4228
Range0.0236
Interquartile range (IQR)0.0091

Descriptive statistics

Standard deviation0.0071374261
Coefficient of variation (CV)0.00020154702
Kurtosis-0.69230817
Mean35.413206
Median Absolute Deviation (MAD)0.0031
Skewness-0.68070473
Sum1876.8999
Variance5.0942852 × 10-5
MonotonicityNot monotonic
2023-12-12T17:56:37.155739image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=45)
ValueCountFrequency (%)
35.4132 2
 
3.8%
35.3992 2
 
3.8%
35.4164 2
 
3.8%
35.4009 2
 
3.8%
35.4153 2
 
3.8%
35.4013 2
 
3.8%
35.4148 2
 
3.8%
35.4168 2
 
3.8%
35.4075 1
 
1.9%
35.4151 1
 
1.9%
Other values (35) 35
66.0%
ValueCountFrequency (%)
35.3992 2
3.8%
35.4008 1
1.9%
35.4009 2
3.8%
35.401 1
1.9%
35.4013 2
3.8%
35.4028 1
1.9%
35.4031 1
1.9%
35.405 1
1.9%
35.4066 1
1.9%
35.4075 1
1.9%
ValueCountFrequency (%)
35.4228 1
1.9%
35.4227 1
1.9%
35.4226 1
1.9%
35.4222 1
1.9%
35.422 1
1.9%
35.4219 1
1.9%
35.4215 1
1.9%
35.4212 1
1.9%
35.421 1
1.9%
35.419 1
1.9%

경도
Real number (ℝ)

HIGH CORRELATION 

Distinct49
Distinct (%)92.5%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean127.38645
Minimum127.3583
Maximum127.4048
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size609.0 B
2023-12-12T17:56:37.347614image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum127.3583
5-th percentile127.3719
Q1127.378
median127.3886
Q3127.3942
95-th percentile127.40114
Maximum127.4048
Range0.0465
Interquartile range (IQR)0.0162

Descriptive statistics

Standard deviation0.010354627
Coefficient of variation (CV)8.1285154 × 10-5
Kurtosis-0.53003654
Mean127.38645
Median Absolute Deviation (MAD)0.0091
Skewness-0.36743933
Sum6751.482
Variance0.00010721831
MonotonicityNot monotonic
2023-12-12T17:56:37.555366image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=49)
ValueCountFrequency (%)
127.398 2
 
3.8%
127.3859 2
 
3.8%
127.3921 2
 
3.8%
127.3728 2
 
3.8%
127.3992 1
 
1.9%
127.3713 1
 
1.9%
127.3887 1
 
1.9%
127.3797 1
 
1.9%
127.3885 1
 
1.9%
127.3886 1
 
1.9%
Other values (39) 39
73.6%
ValueCountFrequency (%)
127.3583 1
1.9%
127.3711 1
1.9%
127.3713 1
1.9%
127.3723 1
1.9%
127.3725 1
1.9%
127.3727 1
1.9%
127.3728 2
3.8%
127.3742 1
1.9%
127.3761 1
1.9%
127.3763 1
1.9%
ValueCountFrequency (%)
127.4048 1
1.9%
127.4014 1
1.9%
127.4012 1
1.9%
127.4011 1
1.9%
127.3992 1
1.9%
127.3989 1
1.9%
127.3981 1
1.9%
127.398 2
3.8%
127.3974 1
1.9%
127.3971 1
1.9%

설치년월
Date

Distinct7
Distinct (%)13.2%
Missing0
Missing (%)0.0%
Memory size556.0 B
Minimum2018-05-01 00:00:00
Maximum2021-08-01 00:00:00
2023-12-12T17:56:37.712589image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T17:56:37.849349image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=7)

데이터기준일자
Date

CONSTANT 

Distinct1
Distinct (%)1.9%
Missing0
Missing (%)0.0%
Memory size556.0 B
Minimum2023-04-24 00:00:00
Maximum2023-04-24 00:00:00
2023-12-12T17:56:37.997834image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T17:56:38.137442image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=1)

Interactions

2023-12-12T17:56:33.529386image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T17:56:32.803647image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T17:56:33.166020image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T17:56:33.663307image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T17:56:32.925729image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T17:56:33.283682image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T17:56:33.786093image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T17:56:33.048495image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T17:56:33.418954image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-12T17:56:38.253328image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
연번읍면동설치장소명그늘막유형그늘막지름위도경도설치년월
연번1.0000.8790.9900.1740.2890.8610.8450.688
읍면동0.8791.0001.0000.0000.4140.8220.8180.596
설치장소명0.9901.0001.0001.0000.8861.0001.0001.000
그늘막유형0.1740.0001.0001.0001.0000.0000.0000.606
그늘막지름0.2890.4140.8861.0001.0000.6290.4190.716
위도0.8610.8221.0000.0000.6291.0000.7120.584
경도0.8450.8181.0000.0000.4190.7121.0000.555
설치년월0.6880.5961.0000.6060.7160.5840.5551.000
2023-12-12T17:56:38.423167image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
그늘막지름읍면동그늘막유형
그늘막지름1.0000.2900.970
읍면동0.2901.0000.000
그늘막유형0.9700.0001.000
2023-12-12T17:56:38.546610image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
연번위도경도읍면동그늘막유형그늘막지름
연번1.000-0.724-0.8050.6810.1080.131
위도-0.7241.0000.6940.5910.0000.288
경도-0.8050.6941.0000.5560.0000.241
읍면동0.6810.5910.5561.0000.0000.290
그늘막유형0.1080.0000.0000.0001.0000.970
그늘막지름0.1310.2880.2410.2900.9701.000

Missing values

2023-12-12T17:56:33.982599image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-12T17:56:34.203660image/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

연번시도시군구읍면동설치장소명그늘막유형그늘막지름위도경도설치년월데이터기준일자
01전라북도남원시도통동도통동 인도교 모정 앞고정형5M35.4163127.39922018-05-012023-04-24
12전라북도남원시도통동도통동 도통우체국 건너편고정형5M35.4173127.39812018-05-012023-04-24
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