Overview

Dataset statistics

Number of variables10
Number of observations72
Missing cells72
Missing cells (%)10.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory6.1 KiB
Average record size in memory86.8 B

Variable types

Numeric4
Text2
Categorical3
Unsupported1

Dataset

Description세종특별자치시 공영자전거 어울링 대여소 정보
Author세종특별자치시
URLhttps://www.data.go.kr/data/15064617/fileData.do

Alerts

STATION_ID is highly overall correlated with Y_POS and 1 other fieldsHigh correlation
Y_POS is highly overall correlated with STATION_ID and 2 other fieldsHigh correlation
X_POS is highly overall correlated with AREA and 1 other fieldsHigh correlation
AREA is highly overall correlated with STATION_ID and 3 other fieldsHigh correlation
GU is highly overall correlated with DONGHigh correlation
DONG is highly overall correlated with Y_POS and 3 other fieldsHigh correlation
GU is highly imbalanced (81.7%)Imbalance
ADDR2 has 72 (100.0%) missing valuesMissing
STATION_ID has unique valuesUnique
STATION_NM has unique valuesUnique
ADDR1 has unique valuesUnique
Y_POS has unique valuesUnique
X_POS has unique valuesUnique
ADDR2 is an unsupported type, check if it needs cleaning or further analysisUnsupported

Reproduction

Analysis started2023-12-12 15:16:33.262689
Analysis finished2023-12-12 15:16:35.791928
Duration2.53 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

STATION_ID
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct72
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean36.5
Minimum1
Maximum72
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size780.0 B
2023-12-13T00:16:36.206334image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile4.55
Q118.75
median36.5
Q354.25
95-th percentile68.45
Maximum72
Range71
Interquartile range (IQR)35.5

Descriptive statistics

Standard deviation20.92845
Coefficient of variation (CV)0.57338218
Kurtosis-1.2
Mean36.5
Median Absolute Deviation (MAD)18
Skewness0
Sum2628
Variance438
MonotonicityStrictly increasing
2023-12-13T00:16:36.339375image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1 1
 
1.4%
38 1
 
1.4%
54 1
 
1.4%
53 1
 
1.4%
52 1
 
1.4%
51 1
 
1.4%
50 1
 
1.4%
49 1
 
1.4%
48 1
 
1.4%
47 1
 
1.4%
Other values (62) 62
86.1%
ValueCountFrequency (%)
1 1
1.4%
2 1
1.4%
3 1
1.4%
4 1
1.4%
5 1
1.4%
6 1
1.4%
7 1
1.4%
8 1
1.4%
9 1
1.4%
10 1
1.4%
ValueCountFrequency (%)
72 1
1.4%
71 1
1.4%
70 1
1.4%
69 1
1.4%
68 1
1.4%
67 1
1.4%
66 1
1.4%
65 1
1.4%
64 1
1.4%
63 1
1.4%

STATION_NM
Text

UNIQUE 

Distinct72
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size708.0 B
2023-12-13T00:16:36.586851image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length17
Median length15
Mean length9.0555556
Min length3

Characters and Unicode

Total characters652
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

Unique72 ?
Unique (%)100.0%

Sample

1st row첫마을 1단지
2nd row첫마을 3단지
3rd row첫마을 4단지
4th rowLH세종특별본부
5th row한솔동 주민센터
ValueCountFrequency (%)
첫마을 7
 
5.6%
가락마을 7
 
5.6%
도램마을 6
 
4.8%
4단지 5
 
4.0%
주민센터 5
 
4.0%
범지기마을 5
 
4.0%
가재마을 4
 
3.2%
새샘마을 3
 
2.4%
1단지 3
 
2.4%
11단지 3
 
2.4%
Other values (65) 78
61.9%
2023-12-13T00:16:37.027306image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
56
 
8.6%
지 40
 
6.1%
을 35
 
5.4%
마 35
 
5.4%
단 34
 
5.2%
1 19
 
2.9%
( 18
 
2.8%
) 18
 
2.8%
종 13
 
2.0%
가 12
 
1.8%
Other values (133) 372
57.1%

Most occurring categories

ValueCountFrequency (%)
Other Letter 493
75.6%
Space Separator 56
 
8.6%
Decimal Number 47
 
7.2%
Uppercase Letter 20
 
3.1%
Open Punctuation 18
 
2.8%
Close Punctuation 18
 
2.8%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
지 40
 
8.1%
을 35
 
7.1%
마 35
 
7.1%
단 34
 
6.9%
종 13
 
2.6%
가 12
 
2.4%
세 11
 
2.2%
원 11
 
2.2%
정 10
 
2.0%
터 10
 
2.0%
Other values (112) 282
57.2%
Decimal Number
ValueCountFrequency (%)
1 19
40.4%
4 6
 
12.8%
3 4
 
8.5%
5 4
 
8.5%
9 3
 
6.4%
6 3
 
6.4%
2 3
 
6.4%
0 2
 
4.3%
7 2
 
4.3%
8 1
 
2.1%
Uppercase Letter
ValueCountFrequency (%)
T 5
25.0%
R 5
25.0%
B 5
25.0%
L 1
 
5.0%
I 1
 
5.0%
H 1
 
5.0%
D 1
 
5.0%
K 1
 
5.0%
Space Separator
ValueCountFrequency (%)
56
100.0%
Open Punctuation
ValueCountFrequency (%)
( 18
100.0%
Close Punctuation
ValueCountFrequency (%)
) 18
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 493
75.6%
Common 139
 
21.3%
Latin 20
 
3.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
지 40
 
8.1%
을 35
 
7.1%
마 35
 
7.1%
단 34
 
6.9%
종 13
 
2.6%
가 12
 
2.4%
세 11
 
2.2%
원 11
 
2.2%
정 10
 
2.0%
터 10
 
2.0%
Other values (112) 282
57.2%
Common
ValueCountFrequency (%)
56
40.3%
1 19
 
13.7%
( 18
 
12.9%
) 18
 
12.9%
4 6
 
4.3%
3 4
 
2.9%
5 4
 
2.9%
9 3
 
2.2%
6 3
 
2.2%
2 3
 
2.2%
Other values (3) 5
 
3.6%
Latin
ValueCountFrequency (%)
T 5
25.0%
R 5
25.0%
B 5
25.0%
L 1
 
5.0%
I 1
 
5.0%
H 1
 
5.0%
D 1
 
5.0%
K 1
 
5.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 493
75.6%
ASCII 159
 
24.4%

Most frequent character per block

ASCII
ValueCountFrequency (%)
56
35.2%
1 19
 
11.9%
( 18
 
11.3%
) 18
 
11.3%
4 6
 
3.8%
T 5
 
3.1%
R 5
 
3.1%
B 5
 
3.1%
3 4
 
2.5%
5 4
 
2.5%
Other values (11) 19
 
11.9%
Hangul
ValueCountFrequency (%)
지 40
 
8.1%
을 35
 
7.1%
마 35
 
7.1%
단 34
 
6.9%
종 13
 
2.6%
가 12
 
2.4%
세 11
 
2.2%
원 11
 
2.2%
정 10
 
2.0%
터 10
 
2.0%
Other values (112) 282
57.2%

AREA
Categorical

HIGH CORRELATION 

Distinct5
Distinct (%)6.9%
Missing0
Missing (%)0.0%
Memory size708.0 B
1생활권
38 
2생활권
16 
조치원읍
9 
3생활권
8 
4생활권
 
1

Length

Max length4
Median length4
Mean length4
Min length4

Unique

Unique1 ?
Unique (%)1.4%

Sample

1st row1생활권
2nd row1생활권
3rd row1생활권
4th row2생활권
5th row1생활권

Common Values

ValueCountFrequency (%)
1생활권 38
52.8%
2생활권 16
22.2%
조치원읍 9
 
12.5%
3생활권 8
 
11.1%
4생활권 1
 
1.4%

Length

2023-12-13T00:16:37.163611image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T00:16:37.277864image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
1생활권 38
52.8%
2생활권 16
22.2%
조치원읍 9
 
12.5%
3생활권 8
 
11.1%
4생활권 1
 
1.4%

GU
Categorical

HIGH CORRELATION  IMBALANCE 

Distinct2
Distinct (%)2.8%
Missing0
Missing (%)0.0%
Memory size708.0 B
세종
70 
연기
 
2

Length

Max length2
Median length2
Mean length2
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
세종 70
97.2%
연기 2
 
2.8%

Length

2023-12-13T00:16:37.385214image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T00:16:37.497873image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
세종 70
97.2%
연기 2
 
2.8%

DONG
Categorical

HIGH CORRELATION 

Distinct22
Distinct (%)30.6%
Missing0
Missing (%)0.0%
Memory size708.0 B
어진동
10 
고운동
9 
한솔동
9 
도담동
7 
아름동
6 
Other values (17)
31 

Length

Max length3
Median length3
Mean length2.9583333
Min length2

Unique

Unique9 ?
Unique (%)12.5%

Sample

1st row한솔동
2nd row한솔동
3rd row한솔동
4th row어진동
5th row한솔동

Common Values

ValueCountFrequency (%)
어진동 10
13.9%
고운동 9
12.5%
한솔동 9
12.5%
도담동 7
9.7%
아름동 6
 
8.3%
중촌동 3
 
4.2%
종촌동 3
 
4.2%
반곡동 3
 
4.2%
보람동 3
 
4.2%
소담동 3
 
4.2%
Other values (12) 16
22.2%

Length

2023-12-13T00:16:37.639567image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
어진동 10
13.9%
한솔동 9
12.5%
고운동 9
12.5%
도담동 7
9.7%
아름동 6
 
8.3%
중촌동 3
 
4.2%
종촌동 3
 
4.2%
반곡동 3
 
4.2%
보람동 3
 
4.2%
소담동 3
 
4.2%
Other values (12) 16
22.2%

ADDR1
Text

UNIQUE 

Distinct72
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size708.0 B
2023-12-13T00:16:37.965205image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length33
Median length29
Mean length22.166667
Min length14

Characters and Unicode

Total characters1596
Distinct characters94
Distinct categories8 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique72 ?
Unique (%)100.0%

Sample

1st row세종특별자치시 한솔동 168-38
2nd row세종특별자치시 한솔동 168-66
3rd row세종특별자치시 한솔동 산 2
4th row 세종특별자치시 어진동 178-286
5th row세종특별자치시 한솔동 산 6
ValueCountFrequency (%)
세종특별자치시 72
25.5%
어진동 10
 
3.5%
조치원읍 9
 
3.2%
한솔동 9
 
3.2%
앞 7
 
2.5%
고운동 6
 
2.1%
도담동 5
 
1.8%
산 4
 
1.4%
아름동 4
 
1.4%
종촌동 4
 
1.4%
Other values (133) 152
53.9%
2023-12-13T00:16:38.555943image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
229
 
14.3%
1 83
 
5.2%
치 82
 
5.1%
종 81
 
5.1%
세 75
 
4.7%
시 74
 
4.6%
특 72
 
4.5%
별 72
 
4.5%
자 72
 
4.5%
동 67
 
4.2%
Other values (84) 689
43.2%

Most occurring categories

ValueCountFrequency (%)
Other Letter 885
55.5%
Decimal Number 377
23.6%
Space Separator 229
 
14.3%
Dash Punctuation 39
 
2.4%
Open Punctuation 29
 
1.8%
Close Punctuation 29
 
1.8%
Control 7
 
0.4%
Math Symbol 1
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
치 82
 
9.3%
종 81
 
9.2%
세 75
 
8.5%
시 74
 
8.4%
특 72
 
8.1%
별 72
 
8.1%
자 72
 
8.1%
동 67
 
7.6%
로 29
 
3.3%
리 13
 
1.5%
Other values (68) 248
28.0%
Decimal Number
ValueCountFrequency (%)
1 83
22.0%
3 48
12.7%
2 40
10.6%
6 37
9.8%
0 33
 
8.8%
7 30
 
8.0%
5 30
 
8.0%
4 28
 
7.4%
8 28
 
7.4%
9 20
 
5.3%
Space Separator
ValueCountFrequency (%)
229
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 39
100.0%
Open Punctuation
ValueCountFrequency (%)
( 29
100.0%
Close Punctuation
ValueCountFrequency (%)
) 29
100.0%
Control
ValueCountFrequency (%)
7
100.0%
Math Symbol
ValueCountFrequency (%)
| 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 885
55.5%
Common 711
44.5%

Most frequent character per script

Hangul
ValueCountFrequency (%)
치 82
 
9.3%
종 81
 
9.2%
세 75
 
8.5%
시 74
 
8.4%
특 72
 
8.1%
별 72
 
8.1%
자 72
 
8.1%
동 67
 
7.6%
로 29
 
3.3%
리 13
 
1.5%
Other values (68) 248
28.0%
Common
ValueCountFrequency (%)
229
32.2%
1 83
 
11.7%
3 48
 
6.8%
2 40
 
5.6%
- 39
 
5.5%
6 37
 
5.2%
0 33
 
4.6%
7 30
 
4.2%
5 30
 
4.2%
( 29
 
4.1%
Other values (6) 113
15.9%

Most occurring blocks

ValueCountFrequency (%)
Hangul 885
55.5%
ASCII 711
44.5%

Most frequent character per block

ASCII
ValueCountFrequency (%)
229
32.2%
1 83
 
11.7%
3 48
 
6.8%
2 40
 
5.6%
- 39
 
5.5%
6 37
 
5.2%
0 33
 
4.6%
7 30
 
4.2%
5 30
 
4.2%
( 29
 
4.1%
Other values (6) 113
15.9%
Hangul
ValueCountFrequency (%)
치 82
 
9.3%
종 81
 
9.2%
세 75
 
8.5%
시 74
 
8.4%
특 72
 
8.1%
별 72
 
8.1%
자 72
 
8.1%
동 67
 
7.6%
로 29
 
3.3%
리 13
 
1.5%
Other values (68) 248
28.0%

ADDR2
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing72
Missing (%)100.0%
Memory size780.0 B

LOCKER
Real number (ℝ)

Distinct9
Distinct (%)12.5%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean14.652778
Minimum10
Maximum30
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size780.0 B
2023-12-13T00:16:38.703328image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum10
5-th percentile10
Q112
median15
Q315
95-th percentile20
Maximum30
Range20
Interquartile range (IQR)3

Descriptive statistics

Standard deviation3.4073645
Coefficient of variation (CV)0.23254052
Kurtosis7.6484991
Mean14.652778
Median Absolute Deviation (MAD)0
Skewness2.1915998
Sum1055
Variance11.610133
MonotonicityNot monotonic
2023-12-13T00:16:38.844856image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=9)
ValueCountFrequency (%)
15 37
51.4%
12 18
25.0%
10 5
 
6.9%
20 5
 
6.9%
13 2
 
2.8%
18 2
 
2.8%
14 1
 
1.4%
30 1
 
1.4%
28 1
 
1.4%
ValueCountFrequency (%)
10 5
 
6.9%
12 18
25.0%
13 2
 
2.8%
14 1
 
1.4%
15 37
51.4%
18 2
 
2.8%
20 5
 
6.9%
28 1
 
1.4%
30 1
 
1.4%
ValueCountFrequency (%)
30 1
 
1.4%
28 1
 
1.4%
20 5
 
6.9%
18 2
 
2.8%
15 37
51.4%
14 1
 
1.4%
13 2
 
2.8%
12 18
25.0%
10 5
 
6.9%

Y_POS
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct72
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean36.510463
Minimum36.469003
Maximum36.620912
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size780.0 B
2023-12-13T00:16:39.020548image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum36.469003
5-th percentile36.476005
Q136.484159
median36.50456
Q336.5131
95-th percentile36.601044
Maximum36.620912
Range0.151909
Interquartile range (IQR)0.028941

Descriptive statistics

Standard deviation0.036821717
Coefficient of variation (CV)0.0010085251
Kurtosis2.2665671
Mean36.510463
Median Absolute Deviation (MAD)0.0115395
Skewness1.7521703
Sum2628.7533
Variance0.0013558388
MonotonicityNot monotonic
2023-12-13T00:16:39.191282image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
36.482114 1
 
1.4%
36.516182 1
 
1.4%
36.520034 1
 
1.4%
36.48985 1
 
1.4%
36.507983 1
 
1.4%
36.511969 1
 
1.4%
36.512775 1
 
1.4%
36.506402 1
 
1.4%
36.508934 1
 
1.4%
36.511452 1
 
1.4%
Other values (62) 62
86.1%
ValueCountFrequency (%)
36.469003 1
1.4%
36.474186 1
1.4%
36.474876 1
1.4%
36.475618 1
1.4%
36.476322 1
1.4%
36.476774 1
1.4%
36.477852 1
1.4%
36.477965 1
1.4%
36.478848 1
1.4%
36.4789789 1
1.4%
ValueCountFrequency (%)
36.620912 1
1.4%
36.6099 1
1.4%
36.602542 1
1.4%
36.602002 1
1.4%
36.60026 1
1.4%
36.5945 1
1.4%
36.5926 1
1.4%
36.591192 1
1.4%
36.5868 1
1.4%
36.520034 1
1.4%

X_POS
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct72
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean127.26478
Minimum127.22969
Maximum127.31061
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size780.0 B
2023-12-13T00:16:39.387175image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum127.22969
5-th percentile127.23695
Q1127.25034
median127.2599
Q3127.27771
95-th percentile127.30146
Maximum127.31061
Range0.08092
Interquartile range (IQR)0.0273625

Descriptive statistics

Standard deviation0.021095882
Coefficient of variation (CV)0.00016576371
Kurtosis-0.72908714
Mean127.26478
Median Absolute Deviation (MAD)0.01036
Skewness0.54836395
Sum9163.0641
Variance0.00044503625
MonotonicityNot monotonic
2023-12-13T00:16:39.607346image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
127.259628 1
 
1.4%
127.245477 1
 
1.4%
127.236768 1
 
1.4%
127.270374 1
 
1.4%
127.261488 1
 
1.4%
127.255813 1
 
1.4%
127.261354 1
 
1.4%
127.249654 1
 
1.4%
127.242006 1
 
1.4%
127.252059 1
 
1.4%
Other values (62) 62
86.1%
ValueCountFrequency (%)
127.229691 1
1.4%
127.229927 1
1.4%
127.23607 1
1.4%
127.236768 1
1.4%
127.237095 1
1.4%
127.237483 1
1.4%
127.237826 1
1.4%
127.239403 1
1.4%
127.240872 1
1.4%
127.242006 1
1.4%
ValueCountFrequency (%)
127.310611 1
1.4%
127.3057 1
1.4%
127.303916 1
1.4%
127.302521 1
1.4%
127.300585 1
1.4%
127.299128 1
1.4%
127.297745 1
1.4%
127.2975 1
1.4%
127.2974 1
1.4%
127.295668 1
1.4%

Interactions

2023-12-13T00:16:35.204966image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T00:16:33.723243image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T00:16:34.318892image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T00:16:34.807429image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T00:16:35.307471image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T00:16:33.895150image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T00:16:34.446013image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T00:16:34.911002image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T00:16:35.404147image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T00:16:34.041149image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T00:16:34.565571image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T00:16:35.010688image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T00:16:35.501431image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T00:16:34.191828image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T00:16:34.689809image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T00:16:35.106592image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-13T00:16:39.757731image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
STATION_IDSTATION_NMAREAGUDONGADDR1LOCKERY_POSX_POS
STATION_ID1.0001.0000.9310.0000.7981.0000.4350.6740.645
STATION_NM1.0001.0001.0001.0001.0001.0001.0001.0001.000
AREA0.9311.0001.0000.1770.9391.0000.5760.7540.733
GU0.0001.0000.1771.0000.8591.0000.0000.0000.000
DONG0.7981.0000.9390.8591.0001.0000.8110.9520.889
ADDR11.0001.0001.0001.0001.0001.0001.0001.0001.000
LOCKER0.4351.0000.5760.0000.8111.0001.0000.4300.328
Y_POS0.6741.0000.7540.0000.9521.0000.4301.0000.541
X_POS0.6451.0000.7330.0000.8891.0000.3280.5411.000
2023-12-13T00:16:39.902723image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
GUAREADONG
GU1.0000.2100.605
AREA0.2101.0000.695
DONG0.6050.6951.000
2023-12-13T00:16:40.009530image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
STATION_IDLOCKERY_POSX_POSAREAGUDONG
STATION_ID1.0000.1100.5620.3060.6230.0000.398
LOCKER0.1101.000-0.004-0.0090.4110.0000.416
Y_POS0.562-0.0041.000-0.0650.6060.0000.701
X_POS0.306-0.009-0.0651.0000.5210.0000.546
AREA0.6230.4110.6060.5211.0000.2100.695
GU0.0000.0000.0000.0000.2101.0000.605
DONG0.3980.4160.7010.5460.6950.6051.000

Missing values

2023-12-13T00:16:35.621127image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-13T00:16:35.740645image/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

STATION_IDSTATION_NMAREAGUDONGADDR1ADDR2LOCKERY_POSX_POS
01첫마을 1단지1생활권세종한솔동세종특별자치시 한솔동 168-38<NA>1336.482114127.259628
12첫마을 3단지1생활권세종한솔동세종특별자치시 한솔동 168-66<NA>1536.47985127.260513
23첫마을 4단지1생활권세종한솔동세종특별자치시 한솔동 산 2<NA>1536.480436127.253314
34LH세종특별본부2생활권세종어진동세종특별자치시 어진동 178-286<NA>1536.495484127.266063
45한솔동 주민센터1생활권세종한솔동세종특별자치시 한솔동 산 6<NA>1436.478979127.255523
56한솔중학교1생활권세종한솔동세종특별자치시 한솔동 산16<NA>1236.474876127.255207
67첫마을 5단지1생활권세종한솔동세종특별자치시 한솔동 316-6|<NA>1536.477852127.249886
78첫마을 6단지1생활권세종한솔동세종특별자치시 한솔동 203-6<NA>1536.475618127.252225
89첫마을 7단지1생활권세종한솔동세종특별자치시 한솔동 102<NA>1536.474186127.255057
910세종보 홍보관2생활권연기세종리세종특별자치시 연기면 세종리 551-174<NA>1536.476774127.25951
STATION_IDSTATION_NMAREAGUDONGADDR1ADDR2LOCKERY_POSX_POS
6263호려울마을 4단지3생활권세종보람동세종특별자치시 보람동 700-77 401동 앞<NA>1236.476322127.288507
6364자이아파트조치원읍세종죽림리세종특별자치시 조치원읍 죽림리 376-1 119동 앞<NA>1236.591192127.291513
6465신흥주공아파트조치원읍세종신흥리세종특별자치시 조치원읍 이화로 5(신흥리393) 201동앞<NA>1536.5945127.288621
6566세종시청(조치원청사)조치원읍세종신흥리세종특별자치시 조치원읍 군청로 87-16(신흥리123)<NA>1236.5926127.2935
6667전통시장(주차타워)조치원읍세종정리세종특별자치시 조치원읍 새내로 89(정리 102-9)<NA>1036.60026127.297745
6768홈플러스 조치원점조치원읍세종원리세종특별자치시 조치원읍 번암리 53-2<NA>1536.5868127.2974
6869조치원역(서측)조치원읍세종침산리세종특별자치시 조치원읍 충현로157(침산리 131-2)<NA>2836.602542127.29476
6970공영버스터미널(조치원)조치원읍세종상리세종특별자치시 조치원읍 조치원로52-1(상리 151-1)<NA>1036.602002127.302521
7071고려대학교(세종캠퍼스)조치원읍세종서창리세종특별자치시 조치원읍 서창리 54-8 테니스장 앞<NA>2036.6099127.29325
7172홍익대학교(세종캠퍼스)조치원읍세종신안리세종특별자치시 조치원읍 신안리 314-1<NA>2036.620912127.290678