Overview

Dataset statistics

Number of variables9
Number of observations6857
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory515.7 KiB
Average record size in memory77.0 B

Variable types

Categorical2
Text4
Numeric3

Dataset

Description파일 다운로드
Author서울특별시
URLhttps://data.seoul.go.kr/dataList/OA-12912/S/1/datasetView.do

Alerts

사용일자 has constant value ""Constant
등록일자 has constant value ""Constant
승차총승객수 is highly overall correlated with 하차총승객수High correlation
하차총승객수 is highly overall correlated with 승차총승객수High correlation
승차총승객수 has 553 (8.1%) zerosZeros
하차총승객수 has 374 (5.5%) zerosZeros

Reproduction

Analysis started2024-04-20 21:24:12.444437
Analysis finished2024-04-20 21:24:15.785199
Duration3.34 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

사용일자
Categorical

CONSTANT 

Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size53.7 KiB
20230101
6857 

Length

Max length8
Median length8
Mean length8
Min length8

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row20230101
2nd row20230101
3rd row20230101
4th row20230101
5th row20230101

Common Values

ValueCountFrequency (%)
20230101 6857
100.0%

Length

2024-04-21T06:24:15.901379image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-21T06:24:16.069379image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
20230101 6857
100.0%

노선번호
Text

Distinct78
Distinct (%)1.1%
Missing0
Missing (%)0.0%
Memory size53.7 KiB
2024-04-21T06:24:16.888135image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length4
Median length4
Mean length3.5791162
Min length3

Characters and Unicode

Total characters24542
Distinct characters14
Distinct categories3 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row100
2nd row9401
3rd row9401
4th row9401
5th row9401
ValueCountFrequency (%)
n26 235
 
3.4%
n37 181
 
2.6%
2312 179
 
2.6%
n15 171
 
2.5%
9408 140
 
2.0%
542 138
 
2.0%
9403 135
 
2.0%
9701 127
 
1.9%
661 125
 
1.8%
302 123
 
1.8%
Other values (68) 5303
77.3%
2024-04-21T06:24:17.994038image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
7 3434
14.0%
1 3218
13.1%
5 2803
11.4%
0 2801
11.4%
2 2782
11.3%
3 2650
10.8%
6 2495
10.2%
4 2156
8.8%
9 990
 
4.0%
N 587
 
2.4%
Other values (4) 626
 
2.6%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 23729
96.7%
Uppercase Letter 659
 
2.7%
Other Letter 154
 
0.6%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
7 3434
14.5%
1 3218
13.6%
5 2803
11.8%
0 2801
11.8%
2 2782
11.7%
3 2650
11.2%
6 2495
10.5%
4 2156
9.1%
9 990
 
4.2%
8 400
 
1.7%
Uppercase Letter
ValueCountFrequency (%)
N 587
89.1%
B 72
 
10.9%
Other Letter
ValueCountFrequency (%)
강 77
50.0%
동 77
50.0%

Most occurring scripts

ValueCountFrequency (%)
Common 23729
96.7%
Latin 659
 
2.7%
Hangul 154
 
0.6%

Most frequent character per script

Common
ValueCountFrequency (%)
7 3434
14.5%
1 3218
13.6%
5 2803
11.8%
0 2801
11.8%
2 2782
11.7%
3 2650
11.2%
6 2495
10.5%
4 2156
9.1%
9 990
 
4.2%
8 400
 
1.7%
Latin
ValueCountFrequency (%)
N 587
89.1%
B 72
 
10.9%
Hangul
ValueCountFrequency (%)
강 77
50.0%
동 77
50.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 24388
99.4%
Hangul 154
 
0.6%

Most frequent character per block

ASCII
ValueCountFrequency (%)
7 3434
14.1%
1 3218
13.2%
5 2803
11.5%
0 2801
11.5%
2 2782
11.4%
3 2650
10.9%
6 2495
10.2%
4 2156
8.8%
9 990
 
4.1%
N 587
 
2.4%
Other values (2) 472
 
1.9%
Hangul
ValueCountFrequency (%)
강 77
50.0%
동 77
50.0%

노선명
Text

Distinct82
Distinct (%)1.2%
Missing0
Missing (%)0.0%
Memory size53.7 KiB
2024-04-21T06:24:18.625214image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length23
Median length20
Mean length17.109961
Min length12

Characters and Unicode

Total characters117323
Distinct characters158
Distinct categories8 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row100번(하계동~용산구청)
2nd row9401번(구미동~서울역)
3rd row9401번(구미동~서울역)
4th row9401번(구미동~서울역)
5th row9401번(구미동~서울역)
ValueCountFrequency (%)
9408번(성남 140
 
1.9%
분당~영등포 140
 
1.9%
542번(군포버스공영차고지~신사역 138
 
1.9%
9403번(성남분당~을지로5가 135
 
1.9%
n15번(우이동성원아파트~남태령역 134
 
1.8%
9701번(가좌동~서울역 127
 
1.7%
661번(부천상동~영등포역,신세계백화점 125
 
1.7%
302번(성남~동대문 123
 
1.7%
541번(군포공영차고지~강남역 122
 
1.7%
441번(월암공영차고지~신사사거리 122
 
1.7%
Other values (76) 5966
82.0%
2024-04-21T06:24:19.540281image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
( 6941
 
5.9%
) 6941
 
5.9%
~ 6857
 
5.8%
번 6599
 
5.6%
동 4610
 
3.9%
지 4171
 
3.6%
고 4003
 
3.4%
차 3831
 
3.3%
7 3434
 
2.9%
1 3290
 
2.8%
Other values (148) 66646
56.8%

Most occurring categories

ValueCountFrequency (%)
Other Letter 71176
60.7%
Decimal Number 23938
 
20.4%
Open Punctuation 6941
 
5.9%
Close Punctuation 6941
 
5.9%
Math Symbol 6857
 
5.8%
Uppercase Letter 659
 
0.6%
Space Separator 415
 
0.4%
Other Punctuation 396
 
0.3%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
번 6599
 
9.3%
동 4610
 
6.5%
지 4171
 
5.9%
고 4003
 
5.6%
차 3831
 
5.4%
영 3204
 
4.5%
공 2784
 
3.9%
역 2440
 
3.4%
대 1551
 
2.2%
포 1331
 
1.9%
Other values (130) 36652
51.5%
Decimal Number
ValueCountFrequency (%)
7 3434
14.3%
1 3290
13.7%
5 2938
12.3%
0 2801
11.7%
2 2782
11.6%
3 2650
11.1%
6 2495
10.4%
4 2158
9.0%
9 990
 
4.1%
8 400
 
1.7%
Uppercase Letter
ValueCountFrequency (%)
N 587
89.1%
B 72
 
10.9%
Other Punctuation
ValueCountFrequency (%)
, 295
74.5%
. 101
 
25.5%
Open Punctuation
ValueCountFrequency (%)
( 6941
100.0%
Close Punctuation
ValueCountFrequency (%)
) 6941
100.0%
Math Symbol
ValueCountFrequency (%)
~ 6857
100.0%
Space Separator
ValueCountFrequency (%)
415
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 71176
60.7%
Common 45488
38.8%
Latin 659
 
0.6%

Most frequent character per script

Hangul
ValueCountFrequency (%)
번 6599
 
9.3%
동 4610
 
6.5%
지 4171
 
5.9%
고 4003
 
5.6%
차 3831
 
5.4%
영 3204
 
4.5%
공 2784
 
3.9%
역 2440
 
3.4%
대 1551
 
2.2%
포 1331
 
1.9%
Other values (130) 36652
51.5%
Common
ValueCountFrequency (%)
( 6941
15.3%
) 6941
15.3%
~ 6857
15.1%
7 3434
7.5%
1 3290
7.2%
5 2938
6.5%
0 2801
6.2%
2 2782
6.1%
3 2650
 
5.8%
6 2495
 
5.5%
Other values (6) 4359
9.6%
Latin
ValueCountFrequency (%)
N 587
89.1%
B 72
 
10.9%

Most occurring blocks

ValueCountFrequency (%)
Hangul 71176
60.7%
ASCII 46147
39.3%

Most frequent character per block

ASCII
ValueCountFrequency (%)
( 6941
15.0%
) 6941
15.0%
~ 6857
14.9%
7 3434
7.4%
1 3290
7.1%
5 2938
6.4%
0 2801
6.1%
2 2782
6.0%
3 2650
 
5.7%
6 2495
 
5.4%
Other values (8) 5018
10.9%
Hangul
ValueCountFrequency (%)
번 6599
 
9.3%
동 4610
 
6.5%
지 4171
 
5.9%
고 4003
 
5.6%
차 3831
 
5.4%
영 3204
 
4.5%
공 2784
 
3.9%
역 2440
 
3.4%
대 1551
 
2.2%
포 1331
 
1.9%
Other values (130) 36652
51.5%

표준버스정류장ID
Real number (ℝ)

Distinct3712
Distinct (%)54.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1.5131594 × 108
Minimum1 × 108
Maximum9.998 × 108
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size60.4 KiB
2024-04-21T06:24:19.821259image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1 × 108
5-th percentile1.0180007 × 108
Q11.1200013 × 108
median1.2000007 × 108
Q32.0900001 × 108
95-th percentile2.2100005 × 108
Maximum9.998 × 108
Range8.998 × 108
Interquartile range (IQR)96999884

Descriptive statistics

Standard deviation61985520
Coefficient of variation (CV)0.40964302
Kurtosis68.555351
Mean1.5131594 × 108
Median Absolute Deviation (MAD)13999841
Skewness5.4267301
Sum1.0375734 × 1012
Variance3.8422047 × 1015
MonotonicityNot monotonic
2024-04-21T06:24:20.165045image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
121000007 12
 
0.2%
121000005 12
 
0.2%
121000009 11
 
0.2%
121000008 11
 
0.2%
121000006 11
 
0.2%
121000014 10
 
0.1%
121000013 10
 
0.1%
121000010 10
 
0.1%
121000003 10
 
0.1%
121000012 9
 
0.1%
Other values (3702) 6751
98.5%
ValueCountFrequency (%)
100000001 2
< 0.1%
100000002 2
< 0.1%
100000003 2
< 0.1%
100000004 2
< 0.1%
100000005 1
< 0.1%
100000006 1
< 0.1%
100000007 1
< 0.1%
100000008 1
< 0.1%
100000015 1
< 0.1%
100000016 1
< 0.1%
ValueCountFrequency (%)
999800005 2
< 0.1%
999800004 1
 
< 0.1%
999033574 3
< 0.1%
998502907 1
 
< 0.1%
998501980 1
 
< 0.1%
998501973 1
 
< 0.1%
998501932 1
 
< 0.1%
998501931 1
 
< 0.1%
998001700 1
 
< 0.1%
990070001 1
 
< 0.1%

버스정류장ARS번호
Text

Distinct3679
Distinct (%)53.7%
Missing0
Missing (%)0.0%
Memory size53.7 KiB
2024-04-21T06:24:21.554803image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length5
Median length5
Mean length4.9918332
Min length1

Characters and Unicode

Total characters34229
Distinct characters11
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique2113 ?
Unique (%)30.8%

Sample

1st row01002
2nd row47024
3rd row47022
4th row47054
5th row47065
ValueCountFrequency (%)
14
 
0.2%
22005 12
 
0.2%
22007 12
 
0.2%
22009 11
 
0.2%
22006 11
 
0.2%
22008 11
 
0.2%
22003 10
 
0.1%
22010 10
 
0.1%
22013 10
 
0.1%
22014 10
 
0.1%
Other values (3669) 6746
98.4%
2024-04-21T06:24:23.498818image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 6504
19.0%
0 6240
18.2%
2 4643
13.6%
3 3521
10.3%
4 2800
8.2%
6 2689
7.9%
5 2459
 
7.2%
7 2117
 
6.2%
8 1817
 
5.3%
9 1425
 
4.2%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 34215
> 99.9%
Math Symbol 14
 
< 0.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 6504
19.0%
0 6240
18.2%
2 4643
13.6%
3 3521
10.3%
4 2800
8.2%
6 2689
7.9%
5 2459
 
7.2%
7 2117
 
6.2%
8 1817
 
5.3%
9 1425
 
4.2%
Math Symbol
ValueCountFrequency (%)
~ 14
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 34229
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
1 6504
19.0%
0 6240
18.2%
2 4643
13.6%
3 3521
10.3%
4 2800
8.2%
6 2689
7.9%
5 2459
 
7.2%
7 2117
 
6.2%
8 1817
 
5.3%
9 1425
 
4.2%

Most occurring blocks

ValueCountFrequency (%)
ASCII 34229
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 6504
19.0%
0 6240
18.2%
2 4643
13.6%
3 3521
10.3%
4 2800
8.2%
6 2689
7.9%
5 2459
 
7.2%
7 2117
 
6.2%
8 1817
 
5.3%
9 1425
 
4.2%

역명
Text

Distinct6476
Distinct (%)94.4%
Missing0
Missing (%)0.0%
Memory size53.7 KiB
2024-04-21T06:24:24.384654image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length37
Median length30
Mean length15.102231
Min length9

Characters and Unicode

Total characters103556
Distinct characters531
Distinct categories9 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique6184 ?
Unique (%)90.2%

Sample

1st row창경궁.서울대학교병원(00031)
2nd row샛별마을.우방아파트(00015)
3rd row중앙공원.샛별마을.라이프아파트(00016)
4th row효자촌(00017)
5th row서현중학교(00018)
ValueCountFrequency (%)
군포공영차고지(00001 6
 
0.1%
등촌중학교 6
 
0.1%
군포보건소(00002 5
 
0.1%
광명차고지(00001 5
 
0.1%
하안버스공영차고지(00002 5
 
0.1%
동해운수(00001 4
 
0.1%
오리초등학교(00006 4
 
0.1%
덕은교.은평차고지앞(00002 4
 
0.1%
대우.롯데아파트상가(00008 4
 
0.1%
헬스케어혁신파크.(구)가스공사(00010 4
 
0.1%
Other values (6468) 6817
99.3%
2024-04-21T06:24:25.831404image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 21592
 
20.9%
( 7139
 
6.9%
) 7139
 
6.9%
1 2669
 
2.6%
. 2282
 
2.2%
2 1810
 
1.7%
3 1651
 
1.6%
4 1521
 
1.5%
5 1456
 
1.4%
6 1394
 
1.3%
Other values (521) 54903
53.0%

Most occurring categories

ValueCountFrequency (%)
Other Letter 50696
49.0%
Decimal Number 35696
34.5%
Open Punctuation 7139
 
6.9%
Close Punctuation 7139
 
6.9%
Other Punctuation 2295
 
2.2%
Uppercase Letter 561
 
0.5%
Lowercase Letter 21
 
< 0.1%
Space Separator 7
 
< 0.1%
Dash Punctuation 2
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
동 1373
 
2.7%
역 1347
 
2.7%
교 1258
 
2.5%
지 1096
 
2.2%
구 1027
 
2.0%
파 1023
 
2.0%
아 989
 
2.0%
트 952
 
1.9%
학 868
 
1.7%
리 822
 
1.6%
Other values (480) 39941
78.8%
Uppercase Letter
ValueCountFrequency (%)
T 86
15.3%
C 82
14.6%
K 78
13.9%
M 66
11.8%
D 61
10.9%
G 40
7.1%
L 33
 
5.9%
S 28
 
5.0%
B 19
 
3.4%
N 13
 
2.3%
Other values (11) 55
9.8%
Decimal Number
ValueCountFrequency (%)
0 21592
60.5%
1 2669
 
7.5%
2 1810
 
5.1%
3 1651
 
4.6%
4 1521
 
4.3%
5 1456
 
4.1%
6 1394
 
3.9%
7 1295
 
3.6%
8 1192
 
3.3%
9 1116
 
3.1%
Other Punctuation
ValueCountFrequency (%)
. 2282
99.4%
& 11
 
0.5%
? 2
 
0.1%
Lowercase Letter
ValueCountFrequency (%)
e 19
90.5%
t 1
 
4.8%
k 1
 
4.8%
Open Punctuation
ValueCountFrequency (%)
( 7139
100.0%
Close Punctuation
ValueCountFrequency (%)
) 7139
100.0%
Space Separator
ValueCountFrequency (%)
7
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 52278
50.5%
Hangul 50696
49.0%
Latin 582
 
0.6%

Most frequent character per script

Hangul
ValueCountFrequency (%)
동 1373
 
2.7%
역 1347
 
2.7%
교 1258
 
2.5%
지 1096
 
2.2%
구 1027
 
2.0%
파 1023
 
2.0%
아 989
 
2.0%
트 952
 
1.9%
학 868
 
1.7%
리 822
 
1.6%
Other values (480) 39941
78.8%
Latin
ValueCountFrequency (%)
T 86
14.8%
C 82
14.1%
K 78
13.4%
M 66
11.3%
D 61
10.5%
G 40
6.9%
L 33
 
5.7%
S 28
 
4.8%
e 19
 
3.3%
B 19
 
3.3%
Other values (14) 70
12.0%
Common
ValueCountFrequency (%)
0 21592
41.3%
( 7139
 
13.7%
) 7139
 
13.7%
1 2669
 
5.1%
. 2282
 
4.4%
2 1810
 
3.5%
3 1651
 
3.2%
4 1521
 
2.9%
5 1456
 
2.8%
6 1394
 
2.7%
Other values (7) 3625
 
6.9%

Most occurring blocks

ValueCountFrequency (%)
ASCII 52860
51.0%
Hangul 50696
49.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 21592
40.8%
( 7139
 
13.5%
) 7139
 
13.5%
1 2669
 
5.0%
. 2282
 
4.3%
2 1810
 
3.4%
3 1651
 
3.1%
4 1521
 
2.9%
5 1456
 
2.8%
6 1394
 
2.6%
Other values (31) 4207
 
8.0%
Hangul
ValueCountFrequency (%)
동 1373
 
2.7%
역 1347
 
2.7%
교 1258
 
2.5%
지 1096
 
2.2%
구 1027
 
2.0%
파 1023
 
2.0%
아 989
 
2.0%
트 952
 
1.9%
학 868
 
1.7%
리 822
 
1.6%
Other values (480) 39941
78.8%

승차총승객수
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct339
Distinct (%)4.9%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean47.877643
Minimum0
Maximum916
Zeros553
Zeros (%)8.1%
Negative0
Negative (%)0.0%
Memory size60.4 KiB
2024-04-21T06:24:26.239420image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q15
median25
Q364
95-th percentile171.2
Maximum916
Range916
Interquartile range (IQR)59

Descriptive statistics

Standard deviation67.875635
Coefficient of variation (CV)1.4176896
Kurtosis21.017112
Mean47.877643
Median Absolute Deviation (MAD)23
Skewness3.542853
Sum328297
Variance4607.1019
MonotonicityNot monotonic
2024-04-21T06:24:26.660382image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 553
 
8.1%
1 369
 
5.4%
2 260
 
3.8%
3 198
 
2.9%
4 194
 
2.8%
5 146
 
2.1%
6 144
 
2.1%
7 125
 
1.8%
9 120
 
1.8%
8 112
 
1.6%
Other values (329) 4636
67.6%
ValueCountFrequency (%)
0 553
8.1%
1 369
5.4%
2 260
3.8%
3 198
 
2.9%
4 194
 
2.8%
5 146
 
2.1%
6 144
 
2.1%
7 125
 
1.8%
8 112
 
1.6%
9 120
 
1.8%
ValueCountFrequency (%)
916 1
< 0.1%
822 1
< 0.1%
813 1
< 0.1%
670 1
< 0.1%
630 1
< 0.1%
593 1
< 0.1%
586 1
< 0.1%
562 1
< 0.1%
560 1
< 0.1%
558 1
< 0.1%

하차총승객수
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct327
Distinct (%)4.8%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean46.998979
Minimum0
Maximum813
Zeros374
Zeros (%)5.5%
Negative0
Negative (%)0.0%
Memory size60.4 KiB
2024-04-21T06:24:27.068049image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q16
median27
Q364
95-th percentile160
Maximum813
Range813
Interquartile range (IQR)58

Descriptive statistics

Standard deviation62.717332
Coefficient of variation (CV)1.3344403
Kurtosis19.158572
Mean46.998979
Median Absolute Deviation (MAD)23
Skewness3.3727484
Sum322272
Variance3933.4637
MonotonicityNot monotonic
2024-04-21T06:24:27.423826image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 374
 
5.5%
1 334
 
4.9%
2 275
 
4.0%
3 237
 
3.5%
4 192
 
2.8%
5 167
 
2.4%
6 152
 
2.2%
7 128
 
1.9%
8 125
 
1.8%
11 116
 
1.7%
Other values (317) 4757
69.4%
ValueCountFrequency (%)
0 374
5.5%
1 334
4.9%
2 275
4.0%
3 237
3.5%
4 192
2.8%
5 167
2.4%
6 152
2.2%
7 128
 
1.9%
8 125
 
1.8%
9 108
 
1.6%
ValueCountFrequency (%)
813 1
< 0.1%
745 1
< 0.1%
683 1
< 0.1%
595 1
< 0.1%
590 1
< 0.1%
558 1
< 0.1%
533 1
< 0.1%
526 1
< 0.1%
523 1
< 0.1%
520 1
< 0.1%

등록일자
Categorical

CONSTANT 

Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size53.7 KiB
20230104
6857 

Length

Max length8
Median length8
Mean length8
Min length8

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row20230104
2nd row20230104
3rd row20230104
4th row20230104
5th row20230104

Common Values

ValueCountFrequency (%)
20230104 6857
100.0%

Length

2024-04-21T06:24:27.791393image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-21T06:24:28.100322image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
20230104 6857
100.0%

Interactions

2024-04-21T06:24:14.543216image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T06:24:13.525094image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T06:24:14.023798image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T06:24:14.714419image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T06:24:13.688738image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T06:24:14.219293image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T06:24:14.876123image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T06:24:13.840928image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T06:24:14.373003image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-04-21T06:24:28.279030image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
노선번호노선명표준버스정류장ID승차총승객수하차총승객수
노선번호1.0001.0000.6940.4630.453
노선명1.0001.0000.6800.4610.450
표준버스정류장ID0.6940.6801.0000.1250.141
승차총승객수0.4630.4610.1251.0000.598
하차총승객수0.4530.4500.1410.5981.000
2024-04-21T06:24:28.545436image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
표준버스정류장ID승차총승객수하차총승객수
표준버스정류장ID1.000-0.120-0.113
승차총승객수-0.1201.0000.571
하차총승객수-0.1130.5711.000

Missing values

2024-04-21T06:24:15.205685image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-04-21T06:24:15.668079image/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

사용일자노선번호노선명표준버스정류장ID버스정류장ARS번호역명승차총승객수하차총승객수등록일자
020230101100100번(하계동~용산구청)10000000201002창경궁.서울대학교병원(00031)334720230104
12023010194019401번(구미동~서울역)20600032147024샛별마을.우방아파트(00015)76120230104
22023010194019401번(구미동~서울역)20600032047022중앙공원.샛별마을.라이프아파트(00016)55820230104
32023010194019401번(구미동~서울역)20600031947054효자촌(00017)3632120230104
42023010194019401번(구미동~서울역)20600031847065서현중학교(00018)1332520230104
52023010194019401번(구미동~서울역)20600031747059새마을연수원입구(00019)1262420230104
62023010194019401번(구미동~서울역)20600024847041정자3동주민센터(00011)123620230104
72023010194019401번(구미동~서울역)20600024747043정든마을.우성아파트(00012)58920230104
82023010194019401번(구미동~서울역)20600024647029한솔마을.LG아파트(00013)62220230104
92023010194019401번(구미동~서울역)20600024547017푸른마을(00014)2292520230104
사용일자노선번호노선명표준버스정류장ID버스정류장ARS번호역명승차총승객수하차총승객수등록일자
684720230101303303번(성남~신설동)20500023349089상대원차고지(00001)4020230104
684820230101603603번(신월동~시청)10100000802008숭례문(00043)217720230104
68492023010123112311번(중랑차고지~문정동)10600031907418중랑공영차고지.신내역(00002)8020230104
68502023010123122312번(중랑공영차고지~강동공영차고지)12400019025302중앙보훈병원1번출구(00071)44920230104
685120230101303303번(성남~신설동)20500023449090상대원차고지(00106)0320230104
685220230101500500번(석수역~을지로입구)10100000402004서울역버스환승센터(00047)2072920230104
68532023010123122312번(중랑공영차고지~강동공영차고지)12400019125303중앙보훈병원1번출구(00034)145020230104
685420230101500500번(석수역~을지로입구)10100000702007서울역버스환승센터.강우규의거터(00040)107720230104
685520230101500500번(석수역~을지로입구)10100000802008숭례문(00046)28420230104
68562023010123112311번(중랑차고지~문정동)10600043607434신내데시앙아파트후문(00116)0520230104