Overview

Dataset statistics

Number of variables10
Number of observations2471
Missing cells2491
Missing cells (%)10.1%
Duplicate rows1
Duplicate rows (%)< 0.1%
Total size in memory195.6 KiB
Average record size in memory81.1 B

Variable types

Numeric1
Text2
Categorical2
Unsupported4
DateTime1

Dataset

Description파일 다운로드
Author서울특별시
URLhttps://data.seoul.go.kr/dataList/OA-13252/F/1/datasetView.do

Alerts

Dataset has 1 (< 0.1%) duplicate rowsDuplicates
대여소 번호 is highly overall correlated with 소재지(위치) and 1 other fieldsHigh correlation
소재지(위치) is highly overall correlated with 대여소 번호High correlation
운영 방식 is highly overall correlated with 대여소 번호High correlation
설치형태 has 1015 (41.1%) missing valuesMissing
Unnamed: 8 has 1455 (58.9%) missing valuesMissing
Unnamed: 4 is an unsupported type, check if it needs cleaning or further analysisUnsupported
Unnamed: 5 is an unsupported type, check if it needs cleaning or further analysisUnsupported
설치형태 is an unsupported type, check if it needs cleaning or further analysisUnsupported
Unnamed: 8 is an unsupported type, check if it needs cleaning or further analysisUnsupported

Reproduction

Analysis started2023-12-11 06:35:29.174005
Analysis finished2023-12-11 06:35:30.372678
Duration1.2 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

대여소 번호
Real number (ℝ)

HIGH CORRELATION 

Distinct2467
Distinct (%)100.0%
Missing4
Missing (%)0.2%
Infinite0
Infinite (%)0.0%
Mean1965.0649
Minimum102
Maximum4869
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size21.8 KiB
2023-12-11T15:35:30.443507image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum102
5-th percentile240.3
Q1845.5
median1713
Q32744.5
95-th percentile4556.7
Maximum4869
Range4767
Interquartile range (IQR)1899

Descriptive statistics

Standard deviation1335.0565
Coefficient of variation (CV)0.67939562
Kurtosis-0.75947565
Mean1965.0649
Median Absolute Deviation (MAD)932
Skewness0.56536409
Sum4847815
Variance1782375.7
MonotonicityStrictly increasing
2023-12-11T15:35:30.636034image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
2356 1
 
< 0.1%
2349 1
 
< 0.1%
2350 1
 
< 0.1%
2351 1
 
< 0.1%
2352 1
 
< 0.1%
2353 1
 
< 0.1%
2354 1
 
< 0.1%
2355 1
 
< 0.1%
2357 1
 
< 0.1%
2368 1
 
< 0.1%
Other values (2457) 2457
99.4%
(Missing) 4
 
0.2%
ValueCountFrequency (%)
102 1
< 0.1%
103 1
< 0.1%
104 1
< 0.1%
105 1
< 0.1%
106 1
< 0.1%
107 1
< 0.1%
108 1
< 0.1%
109 1
< 0.1%
111 1
< 0.1%
112 1
< 0.1%
ValueCountFrequency (%)
4869 1
< 0.1%
4868 1
< 0.1%
4867 1
< 0.1%
4865 1
< 0.1%
4864 1
< 0.1%
4863 1
< 0.1%
4862 1
< 0.1%
4861 1
< 0.1%
4860 1
< 0.1%
4859 1
< 0.1%

보관소(대여소)명
Text

Distinct2462
Distinct (%)99.8%
Missing4
Missing (%)0.2%
Memory size19.4 KiB
2023-12-11T15:35:30.934288image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length29
Median length24
Mean length9.9874341
Min length2

Characters and Unicode

Total characters24639
Distinct characters584
Distinct categories13 ?
Distinct scripts3 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique2457 ?
Unique (%)99.6%

Sample

1st row망원역 1번출구 앞
2nd row망원역 2번출구 앞
3rd row합정역 1번출구 앞
4th row합정역 5번출구 앞
5th row합정역 7번출구 앞
ValueCountFrequency (%)
앞 655
 
12.6%
옆 96
 
1.8%
출구 90
 
1.7%
입구 67
 
1.3%
1번출구 63
 
1.2%
교차로 57
 
1.1%
사거리 51
 
1.0%
2번출구 46
 
0.9%
뒤 44
 
0.8%
3번출구 41
 
0.8%
Other values (2836) 4002
76.8%
2023-12-11T15:35:31.420340image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
2775
 
11.3%
앞 802
 
3.3%
구 742
 
3.0%
역 545
 
2.2%
동 540
 
2.2%
번 476
 
1.9%
출 466
 
1.9%
교 400
 
1.6%
1 366
 
1.5%
파 362
 
1.5%
Other values (574) 17165
69.7%

Most occurring categories

ValueCountFrequency (%)
Other Letter 19687
79.9%
Space Separator 2775
 
11.3%
Decimal Number 1278
 
5.2%
Uppercase Letter 346
 
1.4%
Open Punctuation 224
 
0.9%
Close Punctuation 222
 
0.9%
Lowercase Letter 47
 
0.2%
Other Punctuation 32
 
0.1%
Dash Punctuation 16
 
0.1%
Math Symbol 5
 
< 0.1%
Other values (3) 7
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
앞 802
 
4.1%
구 742
 
3.8%
역 545
 
2.8%
동 540
 
2.7%
번 476
 
2.4%
출 466
 
2.4%
교 400
 
2.0%
파 362
 
1.8%
아 343
 
1.7%
트 336
 
1.7%
Other values (511) 14675
74.5%
Uppercase Letter
ValueCountFrequency (%)
K 43
12.4%
S 40
11.6%
T 33
9.5%
C 30
 
8.7%
G 24
 
6.9%
A 23
 
6.6%
L 21
 
6.1%
D 18
 
5.2%
P 17
 
4.9%
M 17
 
4.9%
Other values (14) 80
23.1%
Lowercase Letter
ValueCountFrequency (%)
e 15
31.9%
k 8
17.0%
s 6
 
12.8%
t 4
 
8.5%
l 2
 
4.3%
n 2
 
4.3%
d 2
 
4.3%
a 1
 
2.1%
g 1
 
2.1%
v 1
 
2.1%
Other values (5) 5
 
10.6%
Decimal Number
ValueCountFrequency (%)
1 366
28.6%
2 223
17.4%
3 164
12.8%
4 127
 
9.9%
0 106
 
8.3%
5 89
 
7.0%
6 58
 
4.5%
7 53
 
4.1%
8 50
 
3.9%
9 42
 
3.3%
Other Punctuation
ValueCountFrequency (%)
, 12
37.5%
. 10
31.2%
& 6
18.8%
· 2
 
6.2%
? 2
 
6.2%
Math Symbol
ValueCountFrequency (%)
~ 4
80.0%
+ 1
 
20.0%
Space Separator
ValueCountFrequency (%)
2775
100.0%
Open Punctuation
ValueCountFrequency (%)
( 224
100.0%
Close Punctuation
ValueCountFrequency (%)
) 222
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 16
100.0%
Control
ValueCountFrequency (%)
4
100.0%
Connector Punctuation
ValueCountFrequency (%)
_ 2
100.0%
Other Symbol
ValueCountFrequency (%)
㈜ 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 19688
79.9%
Common 4558
 
18.5%
Latin 393
 
1.6%

Most frequent character per script

Hangul
ValueCountFrequency (%)
앞 802
 
4.1%
구 742
 
3.8%
역 545
 
2.8%
동 540
 
2.7%
번 476
 
2.4%
출 466
 
2.4%
교 400
 
2.0%
파 362
 
1.8%
아 343
 
1.7%
트 336
 
1.7%
Other values (512) 14676
74.5%
Latin
ValueCountFrequency (%)
K 43
 
10.9%
S 40
 
10.2%
T 33
 
8.4%
C 30
 
7.6%
G 24
 
6.1%
A 23
 
5.9%
L 21
 
5.3%
D 18
 
4.6%
P 17
 
4.3%
M 17
 
4.3%
Other values (29) 127
32.3%
Common
ValueCountFrequency (%)
2775
60.9%
1 366
 
8.0%
( 224
 
4.9%
2 223
 
4.9%
) 222
 
4.9%
3 164
 
3.6%
4 127
 
2.8%
0 106
 
2.3%
5 89
 
2.0%
6 58
 
1.3%
Other values (13) 204
 
4.5%

Most occurring blocks

ValueCountFrequency (%)
Hangul 19687
79.9%
ASCII 4949
 
20.1%
None 3
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
2775
56.1%
1 366
 
7.4%
( 224
 
4.5%
2 223
 
4.5%
) 222
 
4.5%
3 164
 
3.3%
4 127
 
2.6%
0 106
 
2.1%
5 89
 
1.8%
6 58
 
1.2%
Other values (51) 595
 
12.0%
Hangul
ValueCountFrequency (%)
앞 802
 
4.1%
구 742
 
3.8%
역 545
 
2.8%
동 540
 
2.7%
번 476
 
2.4%
출 466
 
2.4%
교 400
 
2.0%
파 362
 
1.8%
아 343
 
1.7%
트 336
 
1.7%
Other values (511) 14675
74.5%
None
ValueCountFrequency (%)
· 2
66.7%
㈜ 1
33.3%

소재지(위치)
Categorical

HIGH CORRELATION 

Distinct27
Distinct (%)1.1%
Missing0
Missing (%)0.0%
Memory size19.4 KiB
송파구
184 
강서구
 
162
강남구
 
145
서초구
 
136
영등포구
 
136
Other values (22)
1708 

Length

Max length4
Median length3
Mean length3.0845811
Min length2

Unique

Unique1 ?
Unique (%)< 0.1%

Sample

1st row<NA>
2nd row자치구
3rd row<NA>
4th row<NA>
5th row마포구

Common Values

ValueCountFrequency (%)
송파구 184
 
7.4%
강서구 162
 
6.6%
강남구 145
 
5.9%
서초구 136
 
5.5%
영등포구 136
 
5.5%
노원구 119
 
4.8%
강동구 111
 
4.5%
종로구 106
 
4.3%
마포구 105
 
4.2%
양천구 100
 
4.0%
Other values (17) 1167
47.2%

Length

2023-12-11T15:35:31.641842image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
송파구 184
 
7.4%
강서구 162
 
6.6%
강남구 145
 
5.9%
서초구 136
 
5.5%
영등포구 136
 
5.5%
노원구 119
 
4.8%
강동구 111
 
4.5%
종로구 106
 
4.3%
마포구 105
 
4.2%
양천구 100
 
4.0%
Other values (17) 1167
47.2%

Unnamed: 3
Text

Distinct2373
Distinct (%)96.2%
Missing3
Missing (%)0.1%
Memory size19.4 KiB
2023-12-11T15:35:31.994235image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length42
Median length35
Mean length14.838736
Min length3

Characters and Unicode

Total characters36622
Distinct characters346
Distinct categories10 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique2292 ?
Unique (%)92.9%

Sample

1st row상세주소
2nd row서울특별시 마포구 월드컵로 72
3rd row서울특별시 마포구 월드컵로 79
4th row서울특별시 마포구 양화로 59
5th row서울특별시 마포구 양화로 48
ValueCountFrequency (%)
서울특별시 1240
 
15.4%
강서구 131
 
1.6%
노원구 121
 
1.5%
영등포구 116
 
1.4%
송파구 109
 
1.3%
지하 106
 
1.3%
강남구 105
 
1.3%
마포구 103
 
1.3%
구로구 96
 
1.2%
서초구 96
 
1.2%
Other values (2496) 5854
72.5%
2023-12-11T15:35:32.467989image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
5789
 
15.8%
구 1953
 
5.3%
로 1736
 
4.7%
서 1669
 
4.6%
1 1636
 
4.5%
동 1329
 
3.6%
울 1311
 
3.6%
시 1291
 
3.5%
별 1242
 
3.4%
특 1241
 
3.4%
Other values (336) 17425
47.6%

Most occurring categories

ValueCountFrequency (%)
Other Letter 21467
58.6%
Decimal Number 8403
 
22.9%
Space Separator 5789
 
15.8%
Dash Punctuation 805
 
2.2%
Open Punctuation 61
 
0.2%
Close Punctuation 61
 
0.2%
Control 19
 
0.1%
Other Punctuation 8
 
< 0.1%
Uppercase Letter 8
 
< 0.1%
Math Symbol 1
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
구 1953
 
9.1%
로 1736
 
8.1%
서 1669
 
7.8%
동 1329
 
6.2%
울 1311
 
6.1%
시 1291
 
6.0%
별 1242
 
5.8%
특 1241
 
5.8%
강 392
 
1.8%
대 365
 
1.7%
Other values (310) 8938
41.6%
Decimal Number
ValueCountFrequency (%)
1 1636
19.5%
2 1214
14.4%
3 946
11.3%
4 770
9.2%
5 722
8.6%
7 697
8.3%
6 691
8.2%
0 644
 
7.7%
8 546
 
6.5%
9 537
 
6.4%
Uppercase Letter
ValueCountFrequency (%)
S 1
12.5%
G 1
12.5%
C 1
12.5%
J 1
12.5%
A 1
12.5%
I 1
12.5%
B 1
12.5%
K 1
12.5%
Other Punctuation
ValueCountFrequency (%)
, 4
50.0%
? 4
50.0%
Space Separator
ValueCountFrequency (%)
5789
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 805
100.0%
Open Punctuation
ValueCountFrequency (%)
( 61
100.0%
Close Punctuation
ValueCountFrequency (%)
) 61
100.0%
Control
ValueCountFrequency (%)
19
100.0%
Math Symbol
ValueCountFrequency (%)
~ 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 21467
58.6%
Common 15147
41.4%
Latin 8
 
< 0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
구 1953
 
9.1%
로 1736
 
8.1%
서 1669
 
7.8%
동 1329
 
6.2%
울 1311
 
6.1%
시 1291
 
6.0%
별 1242
 
5.8%
특 1241
 
5.8%
강 392
 
1.8%
대 365
 
1.7%
Other values (310) 8938
41.6%
Common
ValueCountFrequency (%)
5789
38.2%
1 1636
 
10.8%
2 1214
 
8.0%
3 946
 
6.2%
- 805
 
5.3%
4 770
 
5.1%
5 722
 
4.8%
7 697
 
4.6%
6 691
 
4.6%
0 644
 
4.3%
Other values (8) 1233
 
8.1%
Latin
ValueCountFrequency (%)
S 1
12.5%
G 1
12.5%
C 1
12.5%
J 1
12.5%
A 1
12.5%
I 1
12.5%
B 1
12.5%
K 1
12.5%

Most occurring blocks

ValueCountFrequency (%)
Hangul 21467
58.6%
ASCII 15155
41.4%

Most frequent character per block

ASCII
ValueCountFrequency (%)
5789
38.2%
1 1636
 
10.8%
2 1214
 
8.0%
3 946
 
6.2%
- 805
 
5.3%
4 770
 
5.1%
5 722
 
4.8%
7 697
 
4.6%
6 691
 
4.6%
0 644
 
4.2%
Other values (16) 1241
 
8.2%
Hangul
ValueCountFrequency (%)
구 1953
 
9.1%
로 1736
 
8.1%
서 1669
 
7.8%
동 1329
 
6.2%
울 1311
 
6.1%
시 1291
 
6.0%
별 1242
 
5.8%
특 1241
 
5.8%
강 392
 
1.8%
대 365
 
1.7%
Other values (310) 8938
41.6%

Unnamed: 4
Unsupported

REJECTED  UNSUPPORTED 

Missing3
Missing (%)0.1%
Memory size19.4 KiB

Unnamed: 5
Unsupported

REJECTED  UNSUPPORTED 

Missing3
Missing (%)0.1%
Memory size19.4 KiB

설치 시기
Date

Distinct356
Distinct (%)14.4%
Missing4
Missing (%)0.2%
Memory size19.4 KiB
Minimum2015-09-06 00:00:00
Maximum2021-06-21 00:00:00
2023-12-11T15:35:32.617977image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T15:35:32.775681image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

설치형태
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing1015
Missing (%)41.1%
Memory size19.4 KiB

Unnamed: 8
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing1455
Missing (%)58.9%
Memory size19.4 KiB

운영 방식
Categorical

HIGH CORRELATION 

Distinct3
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size19.4 KiB
LCD
1454 
QR
1013 
<NA>
 
4

Length

Max length4
Median length3
Mean length2.5916633
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row<NA>
2nd row<NA>
3rd row<NA>
4th row<NA>
5th rowLCD

Common Values

ValueCountFrequency (%)
LCD 1454
58.8%
QR 1013
41.0%
<NA> 4
 
0.2%

Length

2023-12-11T15:35:32.943197image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T15:35:33.049684image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
lcd 1454
58.8%
qr 1013
41.0%
na 4
 
0.2%

Interactions

2023-12-11T15:35:29.833912image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-11T15:35:33.121588image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
대여소 번호소재지(위치)운영 방식
대여소\n번호1.0000.9190.832
소재지(위치)0.9191.0000.155
운영\n방식0.8320.1551.000
2023-12-11T15:35:33.214456image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
소재지(위치)운영 방식
소재지(위치)1.0000.134
운영\n방식0.1341.000
2023-12-11T15:35:33.301561image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
대여소 번호소재지(위치)운영 방식
대여소\n번호1.0000.6360.663
소재지(위치)0.6361.0000.134
운영\n방식0.6630.1341.000

Missing values

2023-12-11T15:35:29.963453image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-11T15:35:30.104206image/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.
2023-12-11T15:35:30.261676image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
The correlation heatmap measures nullity correlation: how strongly the presence or absence of one variable affects the presence of another.

Sample

대여소 번호보관소(대여소)명소재지(위치)Unnamed: 3Unnamed: 4Unnamed: 5설치 시기설치형태Unnamed: 8운영 방식
0<NA><NA><NA><NA>NaNNaNNaTLCDQR<NA>
1<NA><NA>자치구상세주소위도경도NaTNaNNaN<NA>
2<NA><NA><NA><NA>NaNNaNNaT거치\n대수거치\n대수<NA>
3<NA><NA><NA><NA>NaNNaNNaTNaNNaN<NA>
4102망원역 1번출구 앞마포구서울특별시 마포구 월드컵로 7237.555649126.9106292015-09-0620NaNLCD
5103망원역 2번출구 앞마포구서울특별시 마포구 월드컵로 7937.554951126.9108352015-09-0614NaNLCD
6104합정역 1번출구 앞마포구서울특별시 마포구 양화로 5937.550629126.9149862015-09-0613NaNLCD
7105합정역 5번출구 앞마포구서울특별시 마포구 양화로 4837.550007126.9148252015-09-065NaNLCD
8106합정역 7번출구 앞마포구서울특별시 마포구 독막로 437.548645126.9128272015-09-0610NaNLCD
9107신한은행 서교동금융센터점 앞마포구서울특별시 마포구 월드컵북로 3537.55751126.9185032015-09-065NaNLCD
대여소 번호보관소(대여소)명소재지(위치)Unnamed: 3Unnamed: 4Unnamed: 5설치 시기설치형태Unnamed: 8운영 방식
24614859잠실나루 나들목송파구신천동 637.521484127.1002812021-01-05NaN15QR
24624860가락쌍용2차아파트 103동송파구가락동22-737.50227127.1219562021-04-13NaN8QR
24634861거여삼거리송파구거여동 20-1437.493084127.1520392021-04-07NaN7QR
24644862올림픽파크텔 맞은편송파구마천동 307-137.523018127.1158832021-04-07NaN10QR
24654863잠실나들목5송파구송파구 잠실동 19-437.516403127.0776142021-03-30NaN7QR
24664864송파사거리송파구송파구 송파동 97-237.502056127.110552021-04-27NaN6QR
24674865한성백제역 1번출구 뒤송파구송파구 방이동 45-437.516479127.1149832021-04-28NaN5QR
24684867가락대림아파트 앞송파구송파구 가락동 94-937.500027127.1184312021-04-28NaN10QR
24694868레이크 호텔 앞송파구송파구 석촌동 15837.507172127.1012422021-05-18NaN7QR
24704869잠실나들목6송파구잠실동 2437.516296127.084612021-06-21NaN9QR

Duplicate rows

Most frequently occurring

대여소 번호보관소(대여소)명소재지(위치)Unnamed: 3설치 시기운영 방식# duplicates
0<NA><NA><NA><NA>NaT<NA>3