Overview

Dataset statistics

Number of variables4
Number of observations299
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory10.1 KiB
Average record size in memory34.4 B

Variable types

Categorical1
Numeric2
Text1

Dataset

Description경기도 광주시 관내 호수 및 저수지 현황에 대한 데이터로 지형지물부호, 지번주소, x좌표, y좌표, 데이터기준일자 등을 제공합니다.
Author경기도 광주시
URLhttps://www.data.go.kr/data/15042226/fileData.do

Alerts

지형지물부호 has constant value ""Constant
경도 has unique valuesUnique
위도 has unique valuesUnique

Reproduction

Analysis started2023-12-16 15:47:34.225924
Analysis finished2023-12-16 15:47:38.700738
Duration4.47 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

지형지물부호
Categorical

CONSTANT 

Distinct1
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Memory size2.5 KiB
호수+저수지
299 

Length

Max length6
Median length6
Mean length6
Min length6

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row호수+저수지
2nd row호수+저수지
3rd row호수+저수지
4th row호수+저수지
5th row호수+저수지

Common Values

ValueCountFrequency (%)
호수+저수지 299
100.0%

Length

2023-12-16T15:47:39.310924image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-16T15:47:40.045860image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
호수+저수지 299
100.0%

경도
Real number (ℝ)

UNIQUE 

Distinct299
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean127.26538
Minimum127.13652
Maximum127.42152
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size2.8 KiB
2023-12-16T15:47:41.132370image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum127.13652
5-th percentile127.15099
Q1127.21894
median127.25626
Q3127.31736
95-th percentile127.35952
Maximum127.42152
Range0.28499668
Interquartile range (IQR)0.098418852

Descriptive statistics

Standard deviation0.065705648
Coefficient of variation (CV)0.00051628846
Kurtosis-0.63961445
Mean127.26538
Median Absolute Deviation (MAD)0.050460917
Skewness0.033736419
Sum38052.349
Variance0.0043172321
MonotonicityNot monotonic
2023-12-16T15:47:41.984464image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
127.234491389 1
 
0.3%
127.26155827 1
 
0.3%
127.217870121 1
 
0.3%
127.179061728 1
 
0.3%
127.319224361 1
 
0.3%
127.314475786 1
 
0.3%
127.355397215 1
 
0.3%
127.242949481 1
 
0.3%
127.220412001 1
 
0.3%
127.244675774 1
 
0.3%
Other values (289) 289
96.7%
ValueCountFrequency (%)
127.136518679 1
0.3%
127.136692495 1
0.3%
127.138538677 1
0.3%
127.138764841 1
0.3%
127.138937738 1
0.3%
127.139232238 1
0.3%
127.139557916 1
0.3%
127.141125878 1
0.3%
127.143752715 1
0.3%
127.144114953 1
0.3%
ValueCountFrequency (%)
127.421515361 1
0.3%
127.420850309 1
0.3%
127.4198435 1
0.3%
127.419760062 1
0.3%
127.417176746 1
0.3%
127.415950127 1
0.3%
127.399792469 1
0.3%
127.399566318 1
0.3%
127.380300634 1
0.3%
127.376135293 1
0.3%

위도
Real number (ℝ)

UNIQUE 

Distinct299
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean37.39154
Minimum37.27096
Maximum37.512283
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size2.8 KiB
2023-12-16T15:47:42.841803image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum37.27096
5-th percentile37.326247
Q137.351508
median37.383196
Q337.421335
95-th percentile37.475921
Maximum37.512283
Range0.2413229
Interquartile range (IQR)0.06982723

Descriptive statistics

Standard deviation0.049211676
Coefficient of variation (CV)0.0013161179
Kurtosis-0.54350389
Mean37.39154
Median Absolute Deviation (MAD)0.032934491
Skewness0.2577101
Sum11180.071
Variance0.002421789
MonotonicityNot monotonic
2023-12-16T15:47:44.119565image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
37.42075874 1
 
0.3%
37.435755522 1
 
0.3%
37.3491849353 1
 
0.3%
37.4097478042 1
 
0.3%
37.4759214228 1
 
0.3%
37.3407151835 1
 
0.3%
37.3392022831 1
 
0.3%
37.4111567941 1
 
0.3%
37.3594238087 1
 
0.3%
37.4025039935 1
 
0.3%
Other values (289) 289
96.7%
ValueCountFrequency (%)
37.2709604658 1
0.3%
37.2812927202 1
0.3%
37.2839744417 1
0.3%
37.2845218866 1
0.3%
37.2874191877 1
0.3%
37.2916604693 1
0.3%
37.2930850546 1
0.3%
37.3089158811 1
0.3%
37.3090970246 1
0.3%
37.3093090438 1
0.3%
ValueCountFrequency (%)
37.512283363 1
0.3%
37.5082139438 1
0.3%
37.5070243578 1
0.3%
37.4991327687 1
0.3%
37.4912084203 1
0.3%
37.484012991 1
0.3%
37.4832125402 1
0.3%
37.4784056729 1
0.3%
37.4782446986 1
0.3%
37.4777638642 1
0.3%

지번주소
Text

Distinct278
Distinct (%)93.0%
Missing0
Missing (%)0.0%
Memory size2.5 KiB
2023-12-16T15:47:45.307006image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length26
Median length24
Mean length20.695652
Min length15

Characters and Unicode

Total characters6188
Distinct characters98
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique262 ?
Unique (%)87.6%

Sample

1st row경기도 광주시 탄벌동 591번지
2nd row경기도 광주시 곤지암읍 삼리 550-2번지
3rd row경기도 광주시 곤지암읍 곤지암리 367번지
4th row경기도 광주시 역동 77-3번지
5th row경기도 광주시 양벌동 949-9번지
ValueCountFrequency (%)
경기도 299
22.2%
광주시 299
22.2%
곤지암읍 39
 
2.9%
도척면 34
 
2.5%
퇴촌면 26
 
1.9%
초월읍 25
 
1.9%
신현동 24
 
1.8%
남한산성면 18
 
1.3%
도수리 16
 
1.2%
양벌동 15
 
1.1%
Other values (331) 554
41.1%
2023-12-16T15:47:47.897457image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1050
17.0%
지 372
 
6.0%
도 355
 
5.7%
경 304
 
4.9%
광 301
 
4.9%
번 301
 
4.9%
주 299
 
4.8%
시 299
 
4.8%
기 299
 
4.8%
- 207
 
3.3%
Other values (88) 2401
38.8%

Most occurring categories

ValueCountFrequency (%)
Other Letter 3822
61.8%
Decimal Number 1109
 
17.9%
Space Separator 1050
 
17.0%
Dash Punctuation 207
 
3.3%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
지 372
 
9.7%
도 355
 
9.3%
경 304
 
8.0%
광 301
 
7.9%
번 301
 
7.9%
주 299
 
7.8%
시 299
 
7.8%
기 299
 
7.8%
리 153
 
4.0%
동 152
 
4.0%
Other values (76) 987
25.8%
Decimal Number
ValueCountFrequency (%)
1 204
18.4%
2 153
13.8%
3 129
11.6%
4 120
10.8%
5 117
10.6%
9 88
7.9%
8 83
7.5%
7 80
 
7.2%
6 79
 
7.1%
0 56
 
5.0%
Space Separator
ValueCountFrequency (%)
1050
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 207
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 3822
61.8%
Common 2366
38.2%

Most frequent character per script

Hangul
ValueCountFrequency (%)
지 372
 
9.7%
도 355
 
9.3%
경 304
 
8.0%
광 301
 
7.9%
번 301
 
7.9%
주 299
 
7.8%
시 299
 
7.8%
기 299
 
7.8%
리 153
 
4.0%
동 152
 
4.0%
Other values (76) 987
25.8%
Common
ValueCountFrequency (%)
1050
44.4%
- 207
 
8.7%
1 204
 
8.6%
2 153
 
6.5%
3 129
 
5.5%
4 120
 
5.1%
5 117
 
4.9%
9 88
 
3.7%
8 83
 
3.5%
7 80
 
3.4%
Other values (2) 135
 
5.7%

Most occurring blocks

ValueCountFrequency (%)
Hangul 3822
61.8%
ASCII 2366
38.2%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1050
44.4%
- 207
 
8.7%
1 204
 
8.6%
2 153
 
6.5%
3 129
 
5.5%
4 120
 
5.1%
5 117
 
4.9%
9 88
 
3.7%
8 83
 
3.5%
7 80
 
3.4%
Other values (2) 135
 
5.7%
Hangul
ValueCountFrequency (%)
지 372
 
9.7%
도 355
 
9.3%
경 304
 
8.0%
광 301
 
7.9%
번 301
 
7.9%
주 299
 
7.8%
시 299
 
7.8%
기 299
 
7.8%
리 153
 
4.0%
동 152
 
4.0%
Other values (76) 987
25.8%

Interactions

2023-12-16T15:47:35.865933image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-16T15:47:34.855338image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-16T15:47:36.578381image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-16T15:47:35.300349image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-16T15:47:48.762368image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
경도위도
경도1.0000.740
위도0.7401.000
2023-12-16T15:47:49.488539image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
경도위도
경도1.000-0.104
위도-0.1041.000

Missing values

2023-12-16T15:47:37.381348image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-16T15:47:38.390837image/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

지형지물부호경도위도지번주소
0호수+저수지127.23449137.420759경기도 광주시 탄벌동 591번지
1호수+저수지127.31182237.351583경기도 광주시 곤지암읍 삼리 550-2번지
2호수+저수지127.34447937.351285경기도 광주시 곤지암읍 곤지암리 367번지
3호수+저수지127.25064537.403027경기도 광주시 역동 77-3번지
4호수+저수지127.24644737.368469경기도 광주시 양벌동 949-9번지
5호수+저수지127.33514237.364804경기도 광주시 곤지암읍 신대리 252-17번지
6호수+저수지127.26480337.411442경기도 광주시 쌍령동 19-10번지
7호수+저수지127.25437.43154경기도 광주시 송정동 산63-11번지
8호수+저수지127.19620937.414512경기도 광주시 삼동 488번지
9호수+저수지127.2856137.420573경기도 광주시 초월읍 지월리 729-30번지
지형지물부호경도위도지번주소
289호수+저수지127.18867337.403717경기도 광주시 직동 207-3번지
290호수+저수지127.13893837.350495경기도 광주시 신현동 1038번지
291호수+저수지127.23858237.387396경기도 광주시 태전동 688번지
292호수+저수지127.34069737.328407경기도 광주시 도척면 진우리 140-2번지
293호수+저수지127.29166337.415171경기도 광주시 초월읍 지월리 592-5번지
294호수+저수지127.34835737.318228경기도 광주시 도척면 진우리 929번지
295호수+저수지127.14112637.35842경기도 광주시 신현동 888-2번지
296호수+저수지127.28675937.484013경기도 광주시 남종면 삼성리 166-2번지
297호수+저수지127.22220437.436093경기도 광주시 목현동 248-7번지
298호수+저수지127.16751837.378822경기도 광주시 신현동 523-15번지