Overview

Dataset statistics

Number of variables4
Number of observations52
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory1.9 KiB
Average record size in memory36.5 B

Variable types

Text2
Numeric2

Dataset

Description광주광역시 무인공유자전거 타랑께 정거장 위치에 대한 주소, 위도, 경도 데이터 항목에 대한 정보를 제공하고 있습니다.
Author광주광역시
URLhttps://www.data.go.kr/data/15120326/fileData.do

Alerts

위도 is highly overall correlated with 경도High correlation
경도 is highly overall correlated with 위도High correlation
명칭 has unique valuesUnique

Reproduction

Analysis started2024-03-14 17:27:07.101654
Analysis finished2024-03-14 17:27:08.768363
Duration1.67 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

명칭
Text

UNIQUE 

Distinct52
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size544.0 B
2024-03-15T02:27:09.389498image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length12
Median length10
Mean length7.6923077
Min length4

Characters and Unicode

Total characters400
Distinct characters143
Distinct categories6 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique52 ?
Unique (%)100.0%

Sample

1st row시청 앞
2nd row우체국 건너편
3rd rowKBS 앞
4th row한국주택금융공사 앞
5th row쉐보레 앞
ValueCountFrequency (%)
앞 34
30.9%
동천 3
 
2.7%
공원 3
 
2.7%
동천마을 3
 
2.7%
건너편 3
 
2.7%
버들마을 2
 
1.8%
광천 2
 
1.8%
세상 1
 
0.9%
동남아파트 1
 
0.9%
상무시민공원4 1
 
0.9%
Other values (57) 57
51.8%
2024-03-15T02:27:10.604487image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
58
 
14.5%
앞 34
 
8.5%
원 13
 
3.2%
공 11
 
2.8%
동 9
 
2.2%
천 8
 
2.0%
상 8
 
2.0%
마 7
 
1.8%
시 7
 
1.8%
무 6
 
1.5%
Other values (133) 239
59.8%

Most occurring categories

ValueCountFrequency (%)
Other Letter 324
81.0%
Space Separator 58
 
14.5%
Decimal Number 13
 
3.2%
Uppercase Letter 3
 
0.8%
Dash Punctuation 1
 
0.2%
Lowercase Letter 1
 
0.2%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
앞 34
 
10.5%
원 13
 
4.0%
공 11
 
3.4%
동 9
 
2.8%
천 8
 
2.5%
상 8
 
2.5%
마 7
 
2.2%
시 7
 
2.2%
무 6
 
1.9%
아 6
 
1.9%
Other values (120) 215
66.4%
Decimal Number
ValueCountFrequency (%)
1 3
23.1%
2 3
23.1%
5 2
15.4%
3 2
15.4%
8 1
 
7.7%
4 1
 
7.7%
6 1
 
7.7%
Uppercase Letter
ValueCountFrequency (%)
S 1
33.3%
B 1
33.3%
K 1
33.3%
Space Separator
ValueCountFrequency (%)
58
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 1
100.0%
Lowercase Letter
ValueCountFrequency (%)
e 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 324
81.0%
Common 72
 
18.0%
Latin 4
 
1.0%

Most frequent character per script

Hangul
ValueCountFrequency (%)
앞 34
 
10.5%
원 13
 
4.0%
공 11
 
3.4%
동 9
 
2.8%
천 8
 
2.5%
상 8
 
2.5%
마 7
 
2.2%
시 7
 
2.2%
무 6
 
1.9%
아 6
 
1.9%
Other values (120) 215
66.4%
Common
ValueCountFrequency (%)
58
80.6%
1 3
 
4.2%
2 3
 
4.2%
5 2
 
2.8%
3 2
 
2.8%
- 1
 
1.4%
8 1
 
1.4%
4 1
 
1.4%
6 1
 
1.4%
Latin
ValueCountFrequency (%)
e 1
25.0%
S 1
25.0%
B 1
25.0%
K 1
25.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 324
81.0%
ASCII 76
 
19.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
58
76.3%
1 3
 
3.9%
2 3
 
3.9%
5 2
 
2.6%
3 2
 
2.6%
- 1
 
1.3%
8 1
 
1.3%
4 1
 
1.3%
e 1
 
1.3%
6 1
 
1.3%
Other values (3) 3
 
3.9%
Hangul
ValueCountFrequency (%)
앞 34
 
10.5%
원 13
 
4.0%
공 11
 
3.4%
동 9
 
2.8%
천 8
 
2.5%
상 8
 
2.5%
마 7
 
2.2%
시 7
 
2.2%
무 6
 
1.9%
아 6
 
1.9%
Other values (120) 215
66.4%

주소(지번)
Text

Distinct48
Distinct (%)92.3%
Missing0
Missing (%)0.0%
Memory size544.0 B
2024-03-15T02:27:11.519176image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length20
Median length19
Mean length17.538462
Min length15

Characters and Unicode

Total characters912
Distinct characters27
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

Unique46 ?
Unique (%)88.5%

Sample

1st row광주광역시 서구 치평동 1200
2nd row광주광역시 서구 치평동 1200-3
3rd row광주광역시 서구 치평동 1206-2
4th row광주광역시 서구 치평동 1208-3
5th row광주광역시 서구 치평동 1241-4
ValueCountFrequency (%)
광주광역시 52
25.0%
서구 51
24.5%
치평동 33
15.9%
동천동 10
 
4.8%
1162 4
 
1.9%
유촌동 4
 
1.9%
쌍촌동 2
 
1.0%
광천동 2
 
1.0%
1200 2
 
1.0%
648 1
 
0.5%
Other values (47) 47
22.6%
2024-03-15T02:27:12.700157image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
156
17.1%
광 106
11.6%
1 63
 
6.9%
동 62
 
6.8%
역 52
 
5.7%
시 52
 
5.7%
구 52
 
5.7%
주 52
 
5.7%
서 51
 
5.6%
2 35
 
3.8%
Other values (17) 231
25.3%

Most occurring categories

ValueCountFrequency (%)
Other Letter 519
56.9%
Decimal Number 213
23.4%
Space Separator 156
 
17.1%
Dash Punctuation 24
 
2.6%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
광 106
20.4%
동 62
11.9%
역 52
10.0%
시 52
10.0%
구 52
10.0%
주 52
10.0%
서 51
9.8%
치 33
 
6.4%
평 33
 
6.4%
천 12
 
2.3%
Other values (5) 14
 
2.7%
Decimal Number
ValueCountFrequency (%)
1 63
29.6%
2 35
16.4%
6 25
 
11.7%
3 19
 
8.9%
0 16
 
7.5%
7 13
 
6.1%
8 12
 
5.6%
5 11
 
5.2%
9 10
 
4.7%
4 9
 
4.2%
Space Separator
ValueCountFrequency (%)
156
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 24
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 519
56.9%
Common 393
43.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
광 106
20.4%
동 62
11.9%
역 52
10.0%
시 52
10.0%
구 52
10.0%
주 52
10.0%
서 51
9.8%
치 33
 
6.4%
평 33
 
6.4%
천 12
 
2.3%
Other values (5) 14
 
2.7%
Common
ValueCountFrequency (%)
156
39.7%
1 63
16.0%
2 35
 
8.9%
6 25
 
6.4%
- 24
 
6.1%
3 19
 
4.8%
0 16
 
4.1%
7 13
 
3.3%
8 12
 
3.1%
5 11
 
2.8%
Other values (2) 19
 
4.8%

Most occurring blocks

ValueCountFrequency (%)
Hangul 519
56.9%
ASCII 393
43.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
156
39.7%
1 63
16.0%
2 35
 
8.9%
6 25
 
6.4%
- 24
 
6.1%
3 19
 
4.8%
0 16
 
4.1%
7 13
 
3.3%
8 12
 
3.1%
5 11
 
2.8%
Other values (2) 19
 
4.8%
Hangul
ValueCountFrequency (%)
광 106
20.4%
동 62
11.9%
역 52
10.0%
시 52
10.0%
구 52
10.0%
주 52
10.0%
서 51
9.8%
치 33
 
6.4%
평 33
 
6.4%
천 12
 
2.3%
Other values (5) 14
 
2.7%

위도
Real number (ℝ)

HIGH CORRELATION 

Distinct51
Distinct (%)98.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean35.158062
Minimum35.143238
Maximum35.17105
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size596.0 B
2024-03-15T02:27:12.937362image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum35.143238
5-th percentile35.147399
Q135.151868
median35.156872
Q335.165987
95-th percentile35.170166
Maximum35.17105
Range0.027812
Interquartile range (IQR)0.0141185

Descriptive statistics

Standard deviation0.0079830799
Coefficient of variation (CV)0.00022706257
Kurtosis-1.2299076
Mean35.158062
Median Absolute Deviation (MAD)0.0061165
Skewness0.18006461
Sum1828.2192
Variance6.3729565 × 10-5
MonotonicityNot monotonic
2024-03-15T02:27:13.180253image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
35.170166 2
 
3.8%
35.158997 1
 
1.9%
35.160225 1
 
1.9%
35.15379 1
 
1.9%
35.151863 1
 
1.9%
35.148182 1
 
1.9%
35.143238 1
 
1.9%
35.168144 1
 
1.9%
35.162544 1
 
1.9%
35.164253 1
 
1.9%
Other values (41) 41
78.8%
ValueCountFrequency (%)
35.143238 1
1.9%
35.146217 1
1.9%
35.14695 1
1.9%
35.147766 1
1.9%
35.14814 1
1.9%
35.148182 1
1.9%
35.148197 1
1.9%
35.1488 1
1.9%
35.150143 1
1.9%
35.150646 1
1.9%
ValueCountFrequency (%)
35.17105 1
1.9%
35.170643 1
1.9%
35.170166 2
3.8%
35.16989 1
1.9%
35.1696 1
1.9%
35.16925 1
1.9%
35.168312 1
1.9%
35.168224 1
1.9%
35.168144 1
1.9%
35.16747 1
1.9%

경도
Real number (ℝ)

HIGH CORRELATION 

Distinct50
Distinct (%)96.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean126.85485
Minimum126.83861
Maximum126.88606
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size596.0 B
2024-03-15T02:27:13.493498image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum126.83861
5-th percentile126.84015
Q1126.84719
median126.85208
Q3126.86266
95-th percentile126.87555
Maximum126.88606
Range0.04745
Interquartile range (IQR)0.01546525

Descriptive statistics

Standard deviation0.011381879
Coefficient of variation (CV)8.9723639 × 10-5
Kurtosis-0.090015696
Mean126.85485
Median Absolute Deviation (MAD)0.008705
Skewness0.7128314
Sum6596.4521
Variance0.00012954716
MonotonicityNot monotonic
2024-03-15T02:27:14.023443image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
126.87851 2
 
3.8%
126.8487 2
 
3.8%
126.85207 1
 
1.9%
126.86394 1
 
1.9%
126.83909 1
 
1.9%
126.84107 1
 
1.9%
126.84101 1
 
1.9%
126.85815 1
 
1.9%
126.86284 1
 
1.9%
126.85908 1
 
1.9%
Other values (40) 40
76.9%
ValueCountFrequency (%)
126.83861 1
1.9%
126.839066 1
1.9%
126.83909 1
1.9%
126.84101 1
1.9%
126.84107 1
1.9%
126.842804 1
1.9%
126.842834 1
1.9%
126.84284 1
1.9%
126.843185 1
1.9%
126.84321 1
1.9%
ValueCountFrequency (%)
126.88606 1
1.9%
126.87851 2
3.8%
126.87312 1
1.9%
126.87026 1
1.9%
126.87018 1
1.9%
126.86988 1
1.9%
126.867584 1
1.9%
126.86701 1
1.9%
126.86681 1
1.9%
126.86394 1
1.9%

Interactions

2024-03-15T02:27:07.978017image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T02:27:07.396859image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T02:27:08.241020image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T02:27:07.708007image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-03-15T02:27:14.302010image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
명칭주소(지번)위도경도
명칭1.0001.0001.0001.000
주소(지번)1.0001.0000.9851.000
위도1.0000.9851.0000.745
경도1.0001.0000.7451.000
2024-03-15T02:27:14.566792image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
위도경도
위도1.0000.797
경도0.7971.000

Missing values

2024-03-15T02:27:08.550125image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-03-15T02:27:08.704360image/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

명칭주소(지번)위도경도
0시청 앞광주광역시 서구 치평동 120035.158997126.85207
1우체국 건너편광주광역시 서구 치평동 1200-335.160225126.855545
2KBS 앞광주광역시 서구 치평동 1206-235.15751126.85521
3한국주택금융공사 앞광주광역시 서구 치평동 1208-335.156643126.85485
4쉐보레 앞광주광역시 서구 치평동 1241-435.152634126.854675
5자생한방병원광주광역시 서구 치평동 1243-235.150864126.85516
6코앤영의원 앞광주광역시 서구 치평동 279-1335.1488126.851685
7롯데마트 앞광주광역시 서구 치평동 123935.151897126.85209
8현대해상 앞광주광역시 서구 치평동 122035.155037126.85211
9센트럴시티 앞광주광역시 서구 치평동 1210-335.155415126.851105
명칭주소(지번)위도경도
42대자중학교 앞광주광역시 서구 동천동 35335.168312126.86701
43동천 호반베르디움 앞광주광역시 서구 동천동 61535.170166126.86681
44동천마을 6단지 앞광주광역시 서구 동천동 65835.170643126.87026
45동천 우미린 앞광주광역시 서구 동천동 64835.16989126.86988
46동천 유적 근린 공원광주광역시 서구 동천동 66035.168224126.87018
47강나루 공원 건너편광주광역시 서구 동천동 36935.16925126.87312
48광천 e-편한 세상 앞광주광역시 서구 광천동 89535.165733126.87851
49유스퀘어 건너편광주광역시 서구 광천동 895-335.161934126.87851
50광주사회복지회관광주광역시 북구 임동 61835.166748126.88606
51라붐웨딩광주광역시 서구 치평동 115735.148197126.83861