Overview

Dataset statistics

Number of variables10
Number of observations6843
Missing cells234
Missing cells (%)0.3%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory574.8 KiB
Average record size in memory86.0 B

Variable types

Categorical2
Text2
Numeric6

Dataset

Description인천광역시에서 운행하고 있는 시내버스의 세부적인 정류소 현황 및 위치 자료입니다.(정류소명, 정류소 번호, 권역, 위-경도, x-y좌표)
Author인천광역시
URLhttps://www.data.go.kr/data/15074309/fileData.do

Alerts

기준일자 has constant value ""Constant
정류소번호 is highly overall correlated with 정류소아이디 and 2 other fieldsHigh correlation
정류소아이디 is highly overall correlated with 정류소번호 and 2 other fieldsHigh correlation
엑스좌표 is highly overall correlated with 위도High correlation
위도 is highly overall correlated with 엑스좌표 and 1 other fieldsHigh correlation
와이좌표 is highly overall correlated with 정류소번호 and 3 other fieldsHigh correlation
경도 is highly overall correlated with 정류소번호 and 3 other fieldsHigh correlation
권역 is highly overall correlated with 위도 and 2 other fieldsHigh correlation
엑스좌표 has 114 (1.7%) missing valuesMissing
와이좌표 has 114 (1.7%) missing valuesMissing
정류소아이디 has unique valuesUnique
위도 has 114 (1.7%) zerosZeros
경도 has 114 (1.7%) zerosZeros

Reproduction

Analysis started2024-03-14 23:07:59.838024
Analysis finished2024-03-14 23:08:13.028475
Duration13.19 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

기준일자
Categorical

CONSTANT 

Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size53.6 KiB
2023-12-31
6843 

Length

Max length10
Median length10
Mean length10
Min length10

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row2023-12-31
2nd row2023-12-31
3rd row2023-12-31
4th row2023-12-31
5th row2023-12-31

Common Values

ValueCountFrequency (%)
2023-12-31 6843
100.0%

Length

2024-03-15T08:08:13.144511image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-15T08:08:13.326621image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2023-12-31 6843
100.0%

정류소명
Text

Distinct4010
Distinct (%)58.6%
Missing0
Missing (%)0.0%
Memory size53.6 KiB
2024-03-15T08:08:14.419005image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length21
Median length18
Mean length6.7181061
Min length2

Characters and Unicode

Total characters45972
Distinct characters636
Distinct categories10 ?
Distinct scripts3 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1670 ?
Unique (%)24.4%

Sample

1st row(구)국제여객터미널
2nd row(구)국제여객터미널
3rd row(구)시민회관사거리
4th row(구)시민회관사거리
5th row(주)경동세라믹스
ValueCountFrequency (%)
대동아파트 13
 
0.2%
현대아파트 12
 
0.2%
입구 12
 
0.2%
부대앞 11
 
0.2%
한국아파트 11
 
0.2%
광명아파트 10
 
0.1%
쌍용아파트 9
 
0.1%
뉴서울아파트 8
 
0.1%
서해그랑블 8
 
0.1%
부평역 8
 
0.1%
Other values (4015) 6790
98.5%
2024-03-15T08:08:16.133919image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
아 1128
 
2.5%
트 1087
 
2.4%
파 970
 
2.1%
리 947
 
2.1%
교 929
 
2.0%
동 870
 
1.9%
지 853
 
1.9%
구 839
 
1.8%
학 702
 
1.5%
) 639
 
1.4%
Other values (626) 37008
80.5%

Most occurring categories

ValueCountFrequency (%)
Other Letter 42420
92.3%
Decimal Number 1333
 
2.9%
Close Punctuation 639
 
1.4%
Open Punctuation 639
 
1.4%
Uppercase Letter 474
 
1.0%
Other Punctuation 366
 
0.8%
Space Separator 50
 
0.1%
Lowercase Letter 37
 
0.1%
Dash Punctuation 12
 
< 0.1%
Connector Punctuation 2
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
아 1128
 
2.7%
트 1087
 
2.6%
파 970
 
2.3%
리 947
 
2.2%
교 929
 
2.2%
동 870
 
2.1%
지 853
 
2.0%
구 839
 
2.0%
학 702
 
1.7%
마 557
 
1.3%
Other values (576) 33538
79.1%
Uppercase Letter
ValueCountFrequency (%)
C 89
18.8%
I 53
11.2%
T 50
10.5%
K 43
9.1%
S 42
8.9%
G 39
8.2%
L 30
 
6.3%
J 25
 
5.3%
H 24
 
5.1%
A 18
 
3.8%
Other values (12) 61
12.9%
Decimal Number
ValueCountFrequency (%)
1 416
31.2%
2 306
23.0%
3 173
13.0%
0 106
 
8.0%
4 94
 
7.1%
5 77
 
5.8%
6 51
 
3.8%
7 47
 
3.5%
8 32
 
2.4%
9 31
 
2.3%
Lowercase Letter
ValueCountFrequency (%)
e 24
64.9%
s 4
 
10.8%
k 2
 
5.4%
t 1
 
2.7%
i 1
 
2.7%
n 1
 
2.7%
f 1
 
2.7%
y 1
 
2.7%
m 1
 
2.7%
g 1
 
2.7%
Other Punctuation
ValueCountFrequency (%)
. 307
83.9%
· 55
 
15.0%
, 4
 
1.1%
Close Punctuation
ValueCountFrequency (%)
) 639
100.0%
Open Punctuation
ValueCountFrequency (%)
( 639
100.0%
Space Separator
ValueCountFrequency (%)
50
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 12
100.0%
Connector Punctuation
ValueCountFrequency (%)
_ 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 42420
92.3%
Common 3041
 
6.6%
Latin 511
 
1.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
아 1128
 
2.7%
트 1087
 
2.6%
파 970
 
2.3%
리 947
 
2.2%
교 929
 
2.2%
동 870
 
2.1%
지 853
 
2.0%
구 839
 
2.0%
학 702
 
1.7%
마 557
 
1.3%
Other values (576) 33538
79.1%
Latin
ValueCountFrequency (%)
C 89
17.4%
I 53
10.4%
T 50
9.8%
K 43
8.4%
S 42
8.2%
G 39
7.6%
L 30
 
5.9%
J 25
 
4.9%
H 24
 
4.7%
e 24
 
4.7%
Other values (22) 92
18.0%
Common
ValueCountFrequency (%)
) 639
21.0%
( 639
21.0%
1 416
13.7%
. 307
10.1%
2 306
10.1%
3 173
 
5.7%
0 106
 
3.5%
4 94
 
3.1%
5 77
 
2.5%
· 55
 
1.8%
Other values (8) 229
 
7.5%

Most occurring blocks

ValueCountFrequency (%)
Hangul 42420
92.3%
ASCII 3497
 
7.6%
None 55
 
0.1%

Most frequent character per block

Hangul
ValueCountFrequency (%)
아 1128
 
2.7%
트 1087
 
2.6%
파 970
 
2.3%
리 947
 
2.2%
교 929
 
2.2%
동 870
 
2.1%
지 853
 
2.0%
구 839
 
2.0%
학 702
 
1.7%
마 557
 
1.3%
Other values (576) 33538
79.1%
ASCII
ValueCountFrequency (%)
) 639
18.3%
( 639
18.3%
1 416
11.9%
. 307
8.8%
2 306
8.8%
3 173
 
4.9%
0 106
 
3.0%
4 94
 
2.7%
C 89
 
2.5%
5 77
 
2.2%
Other values (39) 651
18.6%
None
ValueCountFrequency (%)
· 55
100.0%

정류소번호
Real number (ℝ)

HIGH CORRELATION 

Distinct6807
Distinct (%)99.5%
Missing3
Missing (%)< 0.1%
Infinite0
Infinite (%)0.0%
Mean47064.629
Minimum0
Maximum92076
Zeros7
Zeros (%)0.1%
Negative0
Negative (%)0.0%
Memory size60.3 KiB
2024-03-15T08:08:16.551653image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile35166.8
Q138292.5
median40898.5
Q343639.25
95-th percentile90109.05
Maximum92076
Range92076
Interquartile range (IQR)5346.75

Descriptive statistics

Standard deviation17822.161
Coefficient of variation (CV)0.37867421
Kurtosis1.5950826
Mean47064.629
Median Absolute Deviation (MAD)2686.5
Skewness1.6915898
Sum3.2192206 × 108
Variance3.1762944 × 108
MonotonicityNot monotonic
2024-03-15T08:08:16.983067image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 7
 
0.1%
35214 2
 
< 0.1%
35735 2
 
< 0.1%
25204 2
 
< 0.1%
35591 2
 
< 0.1%
35220 2
 
< 0.1%
35219 2
 
< 0.1%
35097 2
 
< 0.1%
35701 2
 
< 0.1%
35494 2
 
< 0.1%
Other values (6797) 6815
99.6%
(Missing) 3
 
< 0.1%
ValueCountFrequency (%)
0 7
0.1%
2099 1
 
< 0.1%
5499 1
 
< 0.1%
11002 1
 
< 0.1%
11013 1
 
< 0.1%
11014 1
 
< 0.1%
11015 1
 
< 0.1%
11020 1
 
< 0.1%
11021 1
 
< 0.1%
11047 1
 
< 0.1%
ValueCountFrequency (%)
92076 1
< 0.1%
92075 1
< 0.1%
92074 1
< 0.1%
92073 1
< 0.1%
92072 1
< 0.1%
92071 1
< 0.1%
92070 1
< 0.1%
92069 1
< 0.1%
92068 1
< 0.1%
92067 1
< 0.1%

정류소아이디
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct6843
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1.6858008 × 108
Minimum1.0100002 × 108
Maximum2.8280706 × 108
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size60.3 KiB
2024-03-15T08:08:17.401356image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1.0100002 × 108
5-th percentile1.6100026 × 108
Q11.6400045 × 108
median1.6700001 × 108
Q31.6900026 × 108
95-th percentile2.1000042 × 108
Maximum2.8280706 × 108
Range1.8180704 × 108
Interquartile range (IQR)4999813

Descriptive statistics

Standard deviation17824772
Coefficient of variation (CV)0.10573474
Kurtosis13.94755
Mean1.6858008 × 108
Median Absolute Deviation (MAD)2000493
Skewness2.5950166
Sum1.1535935 × 1012
Variance3.177225 × 1014
MonotonicityNot monotonic
2024-03-15T08:08:18.054125image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
161000052 1
 
< 0.1%
164000170 1
 
< 0.1%
164000330 1
 
< 0.1%
164000212 1
 
< 0.1%
164000219 1
 
< 0.1%
164000451 1
 
< 0.1%
164000450 1
 
< 0.1%
164000217 1
 
< 0.1%
169000953 1
 
< 0.1%
169000952 1
 
< 0.1%
Other values (6833) 6833
99.9%
ValueCountFrequency (%)
101000015 1
< 0.1%
101000250 1
< 0.1%
101000329 1
< 0.1%
104000304 1
< 0.1%
111001130 1
< 0.1%
112000013 1
< 0.1%
112000031 1
< 0.1%
112000057 1
< 0.1%
112000067 1
< 0.1%
112000170 1
< 0.1%
ValueCountFrequency (%)
282807060 1
< 0.1%
282807059 1
< 0.1%
282803498 1
< 0.1%
277103846 1
< 0.1%
277103845 1
< 0.1%
277103844 1
< 0.1%
277103843 1
< 0.1%
277103820 1
< 0.1%
277103819 1
< 0.1%
277103812 1
< 0.1%

권역
Categorical

HIGH CORRELATION 

Distinct12
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size53.6 KiB
강화군
1352 
서구
1033 
남동구
744 
부평구
665 
중구
643 
Other values (7)
2406 

Length

Max length7
Median length3
Mean length3.0406255
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row중구
2nd row중구
3rd row미추홀구
4th row미추홀구
5th row서구

Common Values

ValueCountFrequency (%)
강화군 1352
19.8%
서구 1033
15.1%
남동구 744
10.9%
부평구 665
9.7%
중구 643
9.4%
연수구 573
8.4%
미추홀구 490
 
7.2%
계양구 440
 
6.4%
코드정보 없음 434
 
6.3%
옹진군 197
 
2.9%
Other values (2) 272
 
4.0%

Length

2024-03-15T08:08:18.500896image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
강화군 1352
18.6%
서구 1033
14.2%
남동구 744
10.2%
부평구 665
9.1%
중구 643
8.8%
연수구 573
7.9%
미추홀구 490
 
6.7%
계양구 440
 
6.0%
코드정보 434
 
6.0%
없음 434
 
6.0%
Other values (3) 469
 
6.4%

행정동명
Text

Distinct334
Distinct (%)4.9%
Missing3
Missing (%)< 0.1%
Memory size53.6 KiB
2024-03-15T08:08:19.661991image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length8
Median length7
Mean length3.6726608
Min length2

Characters and Unicode

Total characters25121
Distinct characters162
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

Unique69 ?
Unique (%)1.0%

Sample

1st row연안동
2nd row연안동
3rd row주안2동
4th row주안4동
5th row오류왕길동
ValueCountFrequency (%)
영종동 238
 
3.5%
길상면 176
 
2.6%
논현고잔동 159
 
2.3%
강화읍 137
 
2.0%
영흥면 134
 
2.0%
불은면 123
 
1.8%
화도면 119
 
1.7%
계양1동 113
 
1.7%
하점면 111
 
1.6%
삼산면 109
 
1.6%
Other values (324) 5422
79.3%
2024-03-15T08:08:21.669861image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
동 5419
21.6%
면 1463
 
5.8%
1 1061
 
4.2%
2 1007
 
4.0%
도 708
 
2.8%
3 684
 
2.7%
송 485
 
1.9%
산 443
 
1.8%
현 425
 
1.7%
양 395
 
1.6%
Other values (152) 13031
51.9%

Most occurring categories

ValueCountFrequency (%)
Other Letter 21834
86.9%
Decimal Number 3283
 
13.1%
Other Punctuation 3
 
< 0.1%
Space Separator 1
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
동 5419
24.8%
면 1463
 
6.7%
도 708
 
3.2%
송 485
 
2.2%
산 443
 
2.0%
현 425
 
1.9%
양 395
 
1.8%
화 391
 
1.8%
영 389
 
1.8%
서 351
 
1.6%
Other values (142) 11365
52.1%
Decimal Number
ValueCountFrequency (%)
1 1061
32.3%
2 1007
30.7%
3 684
20.8%
4 279
 
8.5%
5 152
 
4.6%
6 60
 
1.8%
8 23
 
0.7%
7 17
 
0.5%
Other Punctuation
ValueCountFrequency (%)
. 3
100.0%
Space Separator
ValueCountFrequency (%)
1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 21834
86.9%
Common 3287
 
13.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
동 5419
24.8%
면 1463
 
6.7%
도 708
 
3.2%
송 485
 
2.2%
산 443
 
2.0%
현 425
 
1.9%
양 395
 
1.8%
화 391
 
1.8%
영 389
 
1.8%
서 351
 
1.6%
Other values (142) 11365
52.1%
Common
ValueCountFrequency (%)
1 1061
32.3%
2 1007
30.6%
3 684
20.8%
4 279
 
8.5%
5 152
 
4.6%
6 60
 
1.8%
8 23
 
0.7%
7 17
 
0.5%
. 3
 
0.1%
1
 
< 0.1%

Most occurring blocks

ValueCountFrequency (%)
Hangul 21834
86.9%
ASCII 3287
 
13.1%

Most frequent character per block

Hangul
ValueCountFrequency (%)
동 5419
24.8%
면 1463
 
6.7%
도 708
 
3.2%
송 485
 
2.2%
산 443
 
2.0%
현 425
 
1.9%
양 395
 
1.8%
화 391
 
1.8%
영 389
 
1.8%
서 351
 
1.6%
Other values (142) 11365
52.1%
ASCII
ValueCountFrequency (%)
1 1061
32.3%
2 1007
30.6%
3 684
20.8%
4 279
 
8.5%
5 152
 
4.6%
6 60
 
1.8%
8 23
 
0.7%
7 17
 
0.5%
. 3
 
0.1%
1
 
< 0.1%

엑스좌표
Real number (ℝ)

HIGH CORRELATION  MISSING 

Distinct6724
Distinct (%)99.9%
Missing114
Missing (%)1.7%
Infinite0
Infinite (%)0.0%
Mean166880.66
Minimum131125.16
Maximum211184.08
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size60.3 KiB
2024-03-15T08:08:22.376415image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum131125.16
5-th percentile145821.49
Q1157254.29
median170003.11
Q3174616.26
95-th percentile178778.62
Maximum211184.08
Range80058.925
Interquartile range (IQR)17361.978

Descriptive statistics

Standard deviation11734.451
Coefficient of variation (CV)0.070316421
Kurtosis0.61982329
Mean166880.66
Median Absolute Deviation (MAD)5438.5876
Skewness-0.382529
Sum1.1229399 × 109
Variance1.3769733 × 108
MonotonicityNot monotonic
2024-03-15T08:08:23.236684image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
156648.6601 2
 
< 0.1%
148589.6429 2
 
< 0.1%
153526.8102 2
 
< 0.1%
169277.8426 2
 
< 0.1%
155843.3009 2
 
< 0.1%
155100.5895 1
 
< 0.1%
155108.7948 1
 
< 0.1%
153238.8939 1
 
< 0.1%
174251.1223 1
 
< 0.1%
153248.2997 1
 
< 0.1%
Other values (6714) 6714
98.1%
(Missing) 114
 
1.7%
ValueCountFrequency (%)
131125.1577 1
< 0.1%
131259.9991 1
< 0.1%
131267.6408 1
< 0.1%
131408.8359 1
< 0.1%
131408.9834 1
< 0.1%
131791.1137 1
< 0.1%
131802.9246 1
< 0.1%
132116.7032 1
< 0.1%
132247.7218 1
< 0.1%
132302.435 1
< 0.1%
ValueCountFrequency (%)
211184.0829 1
< 0.1%
211114.7357 1
< 0.1%
211089.8274 1
< 0.1%
211020.6353 1
< 0.1%
210865.8059 1
< 0.1%
210675.9072 1
< 0.1%
210602.6176 1
< 0.1%
210302.7201 1
< 0.1%
210270.7086 1
< 0.1%
209293.6303 1
< 0.1%

위도
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct6724
Distinct (%)98.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean124.5165
Minimum0
Maximum127.12722
Zeros114
Zeros (%)1.7%
Negative0
Negative (%)0.0%
Memory size60.3 KiB
2024-03-15T08:08:23.865328image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile126.36557
Q1126.50987
median126.65968
Q3126.71269
95-th percentile126.75962
Maximum127.12722
Range127.12722
Interquartile range (IQR)0.202822

Descriptive statistics

Standard deviation16.208775
Coefficient of variation (CV)0.13017372
Kurtosis55.076668
Mean124.5165
Median Absolute Deviation (MAD)0.0644538
Skewness-7.5535767
Sum852066.38
Variance262.7244
MonotonicityNot monotonic
2024-03-15T08:08:24.717915image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.0 114
 
1.7%
126.7221379 2
 
< 0.1%
126.6684156 2
 
< 0.1%
126.649138 2
 
< 0.1%
126.6985575 2
 
< 0.1%
126.7161664 2
 
< 0.1%
126.699019 2
 
< 0.1%
126.597932 1
 
< 0.1%
126.6484213 1
 
< 0.1%
126.6485399 1
 
< 0.1%
Other values (6714) 6714
98.1%
ValueCountFrequency (%)
0.0 114
1.7%
126.2191277 1
 
< 0.1%
126.2206182 1
 
< 0.1%
126.2207056 1
 
< 0.1%
126.2222946 1
 
< 0.1%
126.2222971 1
 
< 0.1%
126.226645 1
 
< 0.1%
126.2267778 1
 
< 0.1%
126.2303954 1
 
< 0.1%
126.2319089 1
 
< 0.1%
ValueCountFrequency (%)
127.1272223 1
< 0.1%
127.1264326 1
< 0.1%
127.1261674 1
< 0.1%
127.1253869 1
< 0.1%
127.1235467 1
< 0.1%
127.1215025 1
< 0.1%
127.1206755 1
< 0.1%
127.1172922 1
< 0.1%
127.1169304 1
< 0.1%
127.1058988 1
< 0.1%

와이좌표
Real number (ℝ)

HIGH CORRELATION  MISSING 

Distinct6722
Distinct (%)99.9%
Missing114
Missing (%)1.7%
Infinite0
Infinite (%)0.0%
Mean447238.46
Minimum413721.41
Maximum480297.46
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size60.3 KiB
2024-03-15T08:08:25.232877image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum413721.41
5-th percentile431594.82
Q1438737.4
median444506.67
Q3454453.47
95-th percentile473796.26
Maximum480297.46
Range66576.056
Interquartile range (IQR)15716.072

Descriptive statistics

Standard deviation12884.945
Coefficient of variation (CV)0.028810011
Kurtosis0.13982807
Mean447238.46
Median Absolute Deviation (MAD)6530.2455
Skewness0.57722528
Sum3.0094676 × 109
Variance1.660218 × 108
MonotonicityNot monotonic
2024-03-15T08:08:25.694540image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
456100.5576 2
 
< 0.1%
420096.7028 2
 
< 0.1%
441489.9708 2
 
< 0.1%
447557.5939 2
 
< 0.1%
469635.9387 2
 
< 0.1%
431361.6324 2
 
< 0.1%
477075.8787 2
 
< 0.1%
428926.2911 1
 
< 0.1%
441391.2635 1
 
< 0.1%
436383.5215 1
 
< 0.1%
Other values (6712) 6712
98.1%
(Missing) 114
 
1.7%
ValueCountFrequency (%)
413721.4082 1
< 0.1%
413736.3934 1
< 0.1%
413833.952 1
< 0.1%
413859.8791 1
< 0.1%
413868.2322 1
< 0.1%
414377.1818 1
< 0.1%
414685.334 1
< 0.1%
414693.3367 1
< 0.1%
414701.6184 1
< 0.1%
414718.9099 1
< 0.1%
ValueCountFrequency (%)
480297.4644 1
< 0.1%
480294.9055 1
< 0.1%
480286.6187 1
< 0.1%
480284.3814 1
< 0.1%
480137.6263 1
< 0.1%
480117.7598 1
< 0.1%
480023.1736 1
< 0.1%
480017.0885 1
< 0.1%
479777.5026 1
< 0.1%
479768.2907 1
< 0.1%

경도
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct6730
Distinct (%)98.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean36.901543
Minimum0
Maximum37.823827
Zeros114
Zeros (%)1.7%
Negative0
Negative (%)0.0%
Memory size60.3 KiB
2024-03-15T08:08:25.971338image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile37.374458
Q137.448214
median37.500629
Q337.589493
95-th percentile37.76441
Maximum37.823827
Range37.823827
Interquartile range (IQR)0.14127939

Descriptive statistics

Standard deviation4.8048245
Coefficient of variation (CV)0.1302066
Kurtosis55.018083
Mean36.901543
Median Absolute Deviation (MAD)0.05917812
Skewness-7.5476505
Sum252517.26
Variance23.086338
MonotonicityNot monotonic
2024-03-15T08:08:26.235696image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.0 114
 
1.7%
37.45241451 1
 
< 0.1%
37.72802849 1
 
< 0.1%
37.42656611 1
 
< 0.1%
37.4279407 1
 
< 0.1%
37.71577326 1
 
< 0.1%
37.71561996 1
 
< 0.1%
37.43190693 1
 
< 0.1%
37.43199399 1
 
< 0.1%
37.67598455 1
 
< 0.1%
Other values (6720) 6720
98.2%
ValueCountFrequency (%)
0.0 114
1.7%
37.22458696 1
 
< 0.1%
37.22472201 1
 
< 0.1%
37.22557003 1
 
< 0.1%
37.22584795 1
 
< 0.1%
37.22587254 1
 
< 0.1%
37.2305196 1
 
< 0.1%
37.23315467 1
 
< 0.1%
37.23322686 1
 
< 0.1%
37.2333121 1
 
< 0.1%
ValueCountFrequency (%)
37.82382708 1
< 0.1%
37.82380528 1
< 0.1%
37.82378501 1
< 0.1%
37.8237658 1
< 0.1%
37.82237425 1
< 0.1%
37.82219712 1
< 0.1%
37.82142014 1
< 0.1%
37.82136469 1
< 0.1%
37.8191223 1
< 0.1%
37.81903974 1
< 0.1%

Interactions

2024-03-15T08:08:10.361594image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T08:08:02.665536image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T08:08:04.125856image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T08:08:05.519903image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T08:08:07.445111image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T08:08:08.974551image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T08:08:10.616617image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T08:08:02.828278image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T08:08:04.390583image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T08:08:05.977158image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T08:08:07.679729image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T08:08:09.136026image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T08:08:10.871690image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T08:08:03.053091image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T08:08:04.677790image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T08:08:06.272759image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T08:08:07.990073image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T08:08:09.326546image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T08:08:11.203392image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T08:08:03.332718image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T08:08:04.871767image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T08:08:06.596439image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T08:08:08.224114image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T08:08:09.522292image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T08:08:11.478426image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T08:08:03.594308image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T08:08:05.046569image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T08:08:06.868310image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T08:08:08.425079image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T08:08:09.720115image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T08:08:11.754605image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T08:08:03.858139image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T08:08:05.235963image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T08:08:07.151037image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T08:08:08.696234image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T08:08:10.050891image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-03-15T08:08:26.436573image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
정류소번호정류소아이디권역엑스좌표위도와이좌표경도
정류소번호1.0000.8790.7900.7590.1820.6440.182
정류소아이디0.8791.0000.6850.7580.1360.4050.136
권역0.7900.6851.0000.7810.6660.8580.666
엑스좌표0.7590.7580.7811.000NaN0.734NaN
위도0.1820.1360.666NaN1.000NaN1.000
와이좌표0.6440.4050.8580.734NaN1.000NaN
경도0.1820.1360.666NaN1.000NaN1.000
2024-03-15T08:08:26.691993image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
정류소번호정류소아이디엑스좌표위도와이좌표경도권역
정류소번호1.0000.887-0.242-0.2420.5830.5510.486
정류소아이디0.8871.000-0.244-0.2700.5940.5290.422
엑스좌표-0.242-0.2441.0001.000-0.366-0.3640.474
위도-0.242-0.2701.0001.000-0.370-0.3010.524
와이좌표0.5830.594-0.366-0.3701.0001.0000.589
경도0.5510.529-0.364-0.3011.0001.0000.524
권역0.4860.4220.4740.5240.5890.5241.000

Missing values

2024-03-15T08:08:12.134527image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-03-15T08:08:12.638185image/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.
2024-03-15T08:08:12.921649image/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

기준일자정류소명정류소번호정류소아이디권역행정동명엑스좌표위도와이좌표경도
02023-12-31(구)국제여객터미널35052161000052중구연안동164354.2097126.597932438993.844137.452415
12023-12-31(구)국제여객터미널35051161000051중구연안동164336.1312126.597726439026.360137.452707
22023-12-31(구)시민회관사거리37326163000326미추홀구주안2동171611.976126.679935439524.678437.457449
32023-12-31(구)시민회관사거리37319163000319미추홀구주안4동171634.3433126.680188439514.77937.45736
42023-12-31(주)경동세라믹스89146168001146서구오류왕길동166087.8384126.616978450837.172437.559186
52023-12-31(주)경인양행앞42096168000096서구가좌1동170343.637126.665414444145.873737.499045
62023-12-31(주)경인양행앞42097168000097서구석남2동170465.3876126.666789444178.413137.499342
72023-12-31(주)대한특수금속39050165000050남동구논현고잔동172879.0446126.694491433147.566637.400029
82023-12-31(주)두남39135165000135남동구남촌도림동173648.1398126.703106435119.479437.417819
92023-12-31(주)세모입구(린나이코리아)37585163000585미추홀구주안5동172037.8604126.684685441205.144937.472603
기준일자정류소명정류소번호정류소아이디권역행정동명엑스좌표위도와이좌표경도
68332023-12-31힐스테이트푸르지오주안37293163000293미추홀구주안4동171617.4849126.680016439043.680937.453115
68342023-12-31힐스테이트푸르지오주안아파트37680163000680미추홀구주안2동171592.7648126.679738439017.861437.452882
68352023-12-31힐스테이트학익37023163000023미추홀구학익1동168987.6645126.650338438014.795737.443761
68362023-12-31힐스테이트학익37022163000022미추홀구학익1동168966.3558126.650097438014.983137.443762
68372023-12-31힐스테이트학익104동앞37670163000670미추홀구학익1동168675.989126.646812438098.620737.444505
68382023-12-31힐스테이트학익104동앞37669163000669미추홀구용현5동168741.3734126.64755438140.779237.444887
68392023-12-31힐캐슬프라자39329165000329남동구구월2동174634.8498126.714105439385.919637.456287
68402023-12-31힐캐슬프라자39331165000331남동구구월2동174638.781126.714149439413.581937.456536
68412023-12-31힘찬병원40891166000891부평구부평5동176052.8411126.730001443392.607237.492425
68422023-12-31힘찬병원40892166000892부평구부평5동176029.5694126.729737443418.217737.492655