Overview

Dataset statistics

Number of variables8
Number of observations79
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory5.3 KiB
Average record size in memory68.7 B

Variable types

Numeric3
Categorical4
Text1

Dataset

Description성남시 자전거 공기주입기 현황에 대한 데이터로, 도로명, 구, 동, 설치상세위치, 위도, 경도, 공기주입기종류의 항목으로 구성되어 있습니다.
URLhttps://www.data.go.kr/data/3073740/fileData.do

Alerts

연번 is highly overall correlated with 구 and 1 other fieldsHigh correlation
위도 is highly overall correlated with 경도 and 2 other fieldsHigh correlation
경도 is highly overall correlated with 위도 and 1 other fieldsHigh correlation
구 is highly overall correlated with 연번 and 2 other fieldsHigh correlation
동 is highly overall correlated with 연번 and 3 other fieldsHigh correlation
연번 has unique valuesUnique
설치위치 has unique valuesUnique

Reproduction

Analysis started2023-12-12 18:52:09.423958
Analysis finished2023-12-12 18:52:11.933932
Duration2.51 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

연번
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct79
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean40
Minimum1
Maximum79
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size843.0 B
2023-12-13T03:52:12.046128image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile4.9
Q120.5
median40
Q359.5
95-th percentile75.1
Maximum79
Range78
Interquartile range (IQR)39

Descriptive statistics

Standard deviation22.949219
Coefficient of variation (CV)0.57373048
Kurtosis-1.2
Mean40
Median Absolute Deviation (MAD)20
Skewness0
Sum3160
Variance526.66667
MonotonicityStrictly increasing
2023-12-13T03:52:12.253561image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1 1
 
1.3%
2 1
 
1.3%
59 1
 
1.3%
58 1
 
1.3%
57 1
 
1.3%
56 1
 
1.3%
55 1
 
1.3%
54 1
 
1.3%
53 1
 
1.3%
52 1
 
1.3%
Other values (69) 69
87.3%
ValueCountFrequency (%)
1 1
1.3%
2 1
1.3%
3 1
1.3%
4 1
1.3%
5 1
1.3%
6 1
1.3%
7 1
1.3%
8 1
1.3%
9 1
1.3%
10 1
1.3%
ValueCountFrequency (%)
79 1
1.3%
78 1
1.3%
77 1
1.3%
76 1
1.3%
75 1
1.3%
74 1
1.3%
73 1
1.3%
72 1
1.3%
71 1
1.3%
70 1
1.3%

도로명
Categorical

Distinct37
Distinct (%)46.8%
Missing0
Missing (%)0.0%
Memory size764.0 B
성남대로
17 
운중로
6 
수정로
5 
세계로
5 
탄천로
 
4
Other values (32)
42 

Length

Max length7
Median length3
Mean length3.5189873
Min length2

Unique

Unique24 ?
Unique (%)30.4%

Sample

1st row수정로
2nd row수정로
3rd row성남대로
4th row성남대로
5th row탄천중로

Common Values

ValueCountFrequency (%)
성남대로 17
21.5%
운중로 6
 
7.6%
수정로 5
 
6.3%
세계로 5
 
6.3%
탄천로 4
 
5.1%
산성대로 3
 
3.8%
돌마로 3
 
3.8%
분당구 2
 
2.5%
위례동로 2
 
2.5%
탄천중로 2
 
2.5%
Other values (27) 30
38.0%

Length

2023-12-13T03:52:12.468183image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
성남대로 17
21.5%
운중로 6
 
7.6%
수정로 5
 
6.3%
세계로 5
 
6.3%
탄천로 4
 
5.1%
산성대로 3
 
3.8%
돌마로 3
 
3.8%
서현로 2
 
2.5%
판교로 2
 
2.5%
둔촌대로 2
 
2.5%
Other values (27) 30
38.0%

구
Categorical

HIGH CORRELATION 

Distinct4
Distinct (%)5.1%
Missing0
Missing (%)0.0%
Memory size764.0 B
분당구
47 
수정구
19 
중원구
12 
중원구
 
1

Length

Max length4
Median length3
Mean length3.0126582
Min length3

Unique

Unique1 ?
Unique (%)1.3%

Sample

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

Common Values

ValueCountFrequency (%)
분당구 47
59.5%
수정구 19
24.1%
중원구 12
 
15.2%
중원구 1
 
1.3%

Length

2023-12-13T03:52:12.657512image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T03:52:12.815409image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
분당구 47
59.5%
수정구 19
24.1%
중원구 13
 
16.5%

동
Categorical

HIGH CORRELATION 

Distinct27
Distinct (%)34.2%
Missing0
Missing (%)0.0%
Memory size764.0 B
창곡동
6 
판교동
 
5
성남동
 
5
이매동
 
5
수내동
 
5
Other values (22)
53 

Length

Max length4
Median length3
Mean length3.0632911
Min length3

Unique

Unique5 ?
Unique (%)6.3%

Sample

1st row신흥3동
2nd row신흥2동
3rd row태평1동
4th row태평1동
5th row수진동

Common Values

ValueCountFrequency (%)
창곡동 6
 
7.6%
판교동 5
 
6.3%
성남동 5
 
6.3%
이매동 5
 
6.3%
수내동 5
 
6.3%
백현동 4
 
5.1%
삼평동 4
 
5.1%
야탑동 4
 
5.1%
정자동 4
 
5.1%
분당동 4
 
5.1%
Other values (17) 33
41.8%

Length

2023-12-13T03:52:12.985449image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
창곡동 6
 
7.6%
성남동 5
 
6.3%
이매동 5
 
6.3%
수내동 5
 
6.3%
판교동 5
 
6.3%
백현동 4
 
5.1%
삼평동 4
 
5.1%
야탑동 4
 
5.1%
정자동 4
 
5.1%
분당동 4
 
5.1%
Other values (17) 33
41.8%

설치위치
Text

UNIQUE 

Distinct79
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size764.0 B
2023-12-13T03:52:13.298997image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length24
Median length17
Mean length9.7848101
Min length4

Characters and Unicode

Total characters773
Distinct characters159
Distinct categories7 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique79 ?
Unique (%)100.0%

Sample

1st row신흥역 4번 출구
2nd row산성역 3번 출구
3rd row태평역 6번 출구
4th row태평1동 주민센터
5th row단대천교
ValueCountFrequency (%)
출구 16
 
9.9%
앞 8
 
5.0%
주민센터 5
 
3.1%
3번 5
 
3.1%
2번 3
 
1.9%
자전거보관소 3
 
1.9%
위 3
 
1.9%
1번 3
 
1.9%
신흥역 2
 
1.2%
주변 2
 
1.2%
Other values (109) 111
68.9%
2023-12-13T03:52:13.951241image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
83
 
10.7%
구 30
 
3.9%
교 28
 
3.6%
출 22
 
2.8%
역 21
 
2.7%
번 21
 
2.7%
동 17
 
2.2%
원 16
 
2.1%
( 15
 
1.9%
공 15
 
1.9%
Other values (149) 505
65.3%

Most occurring categories

ValueCountFrequency (%)
Other Letter 624
80.7%
Space Separator 83
 
10.7%
Decimal Number 33
 
4.3%
Open Punctuation 15
 
1.9%
Close Punctuation 15
 
1.9%
Lowercase Letter 2
 
0.3%
Other Punctuation 1
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
구 30
 
4.8%
교 28
 
4.5%
출 22
 
3.5%
역 21
 
3.4%
번 21
 
3.4%
동 17
 
2.7%
원 16
 
2.6%
공 15
 
2.4%
정 13
 
2.1%
중 12
 
1.9%
Other values (134) 429
68.8%
Decimal Number
ValueCountFrequency (%)
1 11
33.3%
3 7
21.2%
2 6
18.2%
4 3
 
9.1%
6 2
 
6.1%
7 1
 
3.0%
8 1
 
3.0%
9 1
 
3.0%
5 1
 
3.0%
Lowercase Letter
ValueCountFrequency (%)
g 1
50.0%
s 1
50.0%
Space Separator
ValueCountFrequency (%)
83
100.0%
Open Punctuation
ValueCountFrequency (%)
( 15
100.0%
Close Punctuation
ValueCountFrequency (%)
) 15
100.0%
Other Punctuation
ValueCountFrequency (%)
, 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 624
80.7%
Common 147
 
19.0%
Latin 2
 
0.3%

Most frequent character per script

Hangul
ValueCountFrequency (%)
구 30
 
4.8%
교 28
 
4.5%
출 22
 
3.5%
역 21
 
3.4%
번 21
 
3.4%
동 17
 
2.7%
원 16
 
2.6%
공 15
 
2.4%
정 13
 
2.1%
중 12
 
1.9%
Other values (134) 429
68.8%
Common
ValueCountFrequency (%)
83
56.5%
( 15
 
10.2%
) 15
 
10.2%
1 11
 
7.5%
3 7
 
4.8%
2 6
 
4.1%
4 3
 
2.0%
6 2
 
1.4%
7 1
 
0.7%
, 1
 
0.7%
Other values (3) 3
 
2.0%
Latin
ValueCountFrequency (%)
g 1
50.0%
s 1
50.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 624
80.7%
ASCII 149
 
19.3%

Most frequent character per block

ASCII
ValueCountFrequency (%)
83
55.7%
( 15
 
10.1%
) 15
 
10.1%
1 11
 
7.4%
3 7
 
4.7%
2 6
 
4.0%
4 3
 
2.0%
6 2
 
1.3%
7 1
 
0.7%
, 1
 
0.7%
Other values (5) 5
 
3.4%
Hangul
ValueCountFrequency (%)
구 30
 
4.8%
교 28
 
4.5%
출 22
 
3.5%
역 21
 
3.4%
번 21
 
3.4%
동 17
 
2.7%
원 16
 
2.6%
공 15
 
2.4%
정 13
 
2.1%
중 12
 
1.9%
Other values (134) 429
68.8%

위도
Real number (ℝ)

HIGH CORRELATION 

Distinct78
Distinct (%)98.7%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean37.407592
Minimum37.3406
Maximum37.4731
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size843.0 B
2023-12-13T03:52:14.229597image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum37.3406
5-th percentile37.35038
Q137.38255
median37.400729
Q337.43515
95-th percentile37.468986
Maximum37.4731
Range0.1325
Interquartile range (IQR)0.0526

Descriptive statistics

Standard deviation0.034880637
Coefficient of variation (CV)0.00093244808
Kurtosis-0.82002601
Mean37.407592
Median Absolute Deviation (MAD)0.0279294
Skewness0.18396653
Sum2955.1998
Variance0.0012166589
MonotonicityNot monotonic
2023-12-13T03:52:14.539842image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
37.4401 2
 
2.5%
37.4412 1
 
1.3%
37.3894 1
 
1.3%
37.3611 1
 
1.3%
37.3886 1
 
1.3%
37.3914 1
 
1.3%
37.3931 1
 
1.3%
37.39526205 1
 
1.3%
37.3885 1
 
1.3%
37.3882 1
 
1.3%
Other values (68) 68
86.1%
ValueCountFrequency (%)
37.3406 1
1.3%
37.3412 1
1.3%
37.3499 1
1.3%
37.3502 1
1.3%
37.3504 1
1.3%
37.3611 1
1.3%
37.3612 1
1.3%
37.3664 1
1.3%
37.3679 1
1.3%
37.369 1
1.3%
ValueCountFrequency (%)
37.4731 1
1.3%
37.4724 1
1.3%
37.4721 1
1.3%
37.4698 1
1.3%
37.46889506 1
1.3%
37.4678 1
1.3%
37.4642 1
1.3%
37.4639 1
1.3%
37.4553 1
1.3%
37.4514 1
1.3%

경도
Real number (ℝ)

HIGH CORRELATION 

Distinct76
Distinct (%)96.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean127.12415
Minimum127.0703
Maximum127.1707
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size843.0 B
2023-12-13T03:52:14.850733image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum127.0703
5-th percentile127.08648
Q1127.11137
median127.12337
Q3127.13845
95-th percentile127.15878
Maximum127.1707
Range0.1004
Interquartile range (IQR)0.0270792

Descriptive statistics

Standard deviation0.021052195
Coefficient of variation (CV)0.00016560343
Kurtosis0.37014688
Mean127.12415
Median Absolute Deviation (MAD)0.0122703
Skewness-0.26888057
Sum10042.808
Variance0.0004431949
MonotonicityNot monotonic
2023-12-13T03:52:15.128348image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
127.1092 2
 
2.5%
127.1111 2
 
2.5%
127.1259 2
 
2.5%
127.1474 1
 
1.3%
127.117 1
 
1.3%
127.0703 1
 
1.3%
127.1114413 1
 
1.3%
127.0973 1
 
1.3%
127.1113 1
 
1.3%
127.1132 1
 
1.3%
Other values (66) 66
83.5%
ValueCountFrequency (%)
127.0703 1
1.3%
127.0708 1
1.3%
127.0755 1
1.3%
127.0782 1
1.3%
127.0874 1
1.3%
127.091 1
1.3%
127.095539 1
1.3%
127.0973 1
1.3%
127.1015 1
1.3%
127.1059 1
1.3%
ValueCountFrequency (%)
127.1707 1
1.3%
127.1644 1
1.3%
127.1628 1
1.3%
127.1595 1
1.3%
127.1587 1
1.3%
127.157 1
1.3%
127.1567056 1
1.3%
127.15 1
1.3%
127.1497 1
1.3%
127.1494 1
1.3%

공기주입기 종류
Categorical

Distinct3
Distinct (%)3.8%
Missing0
Missing (%)0.0%
Memory size764.0 B
전기식
48 
태양광
28 
수동식
 
3

Length

Max length3
Median length3
Mean length3
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
전기식 48
60.8%
태양광 28
35.4%
수동식 3
 
3.8%

Length

2023-12-13T03:52:15.372247image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T03:52:15.572724image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
전기식 48
60.8%
태양광 28
35.4%
수동식 3
 
3.8%

Interactions

2023-12-13T03:52:11.274668image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T03:52:10.511085image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T03:52:10.881903image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T03:52:11.414925image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T03:52:10.647496image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T03:52:11.015602image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T03:52:11.551448image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T03:52:10.780507image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T03:52:11.138323image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-13T03:52:15.721223image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
연번도로명구동설치위치위도경도공기주입기 종류
연번1.0000.8400.8300.9181.0000.8850.6980.000
도로명0.8401.0000.7960.8671.0000.8180.8490.000
구0.8300.7961.0000.9601.0000.8240.4600.000
동0.9180.8670.9601.0001.0000.9600.8950.000
설치위치1.0001.0001.0001.0001.0001.0001.0001.000
위도0.8850.8180.8240.9601.0001.0000.6240.329
경도0.6980.8490.4600.8951.0000.6241.0000.131
공기주입기 종류0.0000.0000.0000.0001.0000.3290.1311.000
2023-12-13T03:52:15.936793image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
도로명구동공기주입기 종류
도로명1.0000.4020.3230.000
구0.4021.0000.7110.000
동0.3230.7111.0000.000
공기주입기 종류0.0000.0000.0001.000
2023-12-13T03:52:16.116124image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
연번위도경도도로명구동공기주입기 종류
연번1.000-0.171-0.2970.3720.6390.5660.000
위도-0.1711.0000.6400.3460.6310.6830.195
경도-0.2970.6401.0000.3830.2780.5180.064
도로명0.3720.3460.3831.0000.4020.3230.000
구0.6390.6310.2780.4021.0000.7110.000
동0.5660.6830.5180.3230.7111.0000.000
공기주입기 종류0.0000.1950.0640.0000.0000.0001.000

Missing values

2023-12-13T03:52:11.705541image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-13T03:52:11.876534image/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

연번도로명구동설치위치위도경도공기주입기 종류
01수정로수정구신흥3동신흥역 4번 출구37.4412127.1474전기식
12수정로수정구신흥2동산성역 3번 출구37.4553127.1497전기식
23성남대로수정구태평1동태평역 6번 출구37.4401127.1275전기식
34성남대로수정구태평1동태평1동 주민센터37.4409127.126전기식
45탄천중로수정구수진동단대천교37.4325127.1188전기식
56중앙로수정구단대동단대오거리 7번 출구37.4459127.157태양광
67수정로수정구단대동남한산성입구역 3번 출구37.4514127.1595전기식
78성남대로수정구양지동남한산성유원지입구37.4642127.1707전기식
89성남대로수정구복정동가천대역 1번 출구37.4494127.1269전기식
910대왕판교로수정구시흥동시흥동주민센터37.4219127.107929태양광
연번도로명구동설치위치위도경도공기주입기 종류
6970탄천로분당구이매동매송중학교37.397307127.12337전기식
7071둔촌대로중원구성남동모란공영주차장37.429049127.126397태양광
7172복정로수정구복정동복정도서관37.4639127.1279전기식
7273위례서로수정구창곡동위례중앙중학교(후문, 고가교위)37.4724127.1376태양광
7374위례광장로수정구창곡동위례중앙광장37.4731127.1421태양광
7475위례대로수정구창곡동위례역사수변공원 북측 정자 아래37.4698127.1423태양광
7576위례동로수정구창곡동성남위례파출소 앞37.4721127.15태양광
7677위례동로수정구창곡동위례한빛중학교(정문)37.4678127.1494태양광
7778성남대로분당구구미동미금역 3번 출구 앞37.3499127.1092전기식
7879산성대로중원구중앙동신흥역 3번 출구37.441156127.147571태양광