Overview

Dataset statistics

Number of variables21
Number of observations500
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory89.0 KiB
Average record size in memory182.3 B

Variable types

Text5
Numeric10
Categorical6

Dataset

Description샘플 데이터
Author서울시(스마트카드사)
URLhttps://bigdata.seoul.go.kr/data/selectSampleData.do?sample_data_seq=13

Alerts

교통카드사용자구분코드3(BILL_USER_GBN3) has constant value ""Constant
승객수2(PASSN_CNT2) has constant value ""Constant
승객수3(PASSN_CNT3) has constant value ""Constant
교통카드사용자구분코드2(BILL_USER_GBN2) is highly imbalanced (97.9%)Imbalance
승객수1(PASSN_CNT1) is highly imbalanced (94.7%)Imbalance
카드번호(CARD_ID) has unique valuesUnique
승차일시(GETON_DATETIME) has unique valuesUnique
하차일시(GETOFF_DATETIME) has unique valuesUnique
이용거리(MOV_DIST) has 15 (3.0%) zerosZeros

Reproduction

Analysis started2024-04-17 19:24:49.172070
Analysis finished2024-04-17 19:24:49.379621
Duration0.21 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

Distinct500
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size4.0 KiB
2024-04-18T04:24:49.516142image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length44
Median length44
Mean length43.92
Min length24

Characters and Unicode

Total characters21960
Distinct characters66
Distinct categories5 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique500 ?
Unique (%)100.0%

Sample

1st rowi*/*L*h*t*4*v*0*c*x*L*A*O*+*I*V*I*u*8*I*Z*0*
2nd row9*D*N*I*Y*A*8*9*c*5*E*u*E*T*C*U*+*G*q*9*J*I*
3rd rowV*C*B*4*X*v*M*S*+*K*Z*w*+*N*5*0*h*0*i*F*E*M*
4th rowi*2*i*q*+*O*A*/*u*e*E*c*i*Q*R*5*O*2*u*T*M*c*
5th rowa*D*v*7*7*M*m*Y*3*I*f*3*G*U*a*/*7*T*b*z*a*k*
ValueCountFrequency (%)
i*/*l*h*t*4*v*0*c*x*l*a*o*+*i*v*i*u*8*i*z*0 1
 
0.2%
p*e*w*j*s*l*s*w*a*j*p*x*j*c*n*3*p*h*6*j*a*8 1
 
0.2%
y*+*m*o*2*e*h*3*w*b*y*q*k*i*u*v*5*g*j*5*a*q 1
 
0.2%
j*j*x*y*l*u*n*b*n*h*d*9*/*p*n*e*a*k*u*0*t*0 1
 
0.2%
y*r*g*j*r*t*3*x*x*k*p*y*8*o*y*r*g*x*8*d*g*i 1
 
0.2%
p*w*m*9*x*k*a*x*e*c*f*w*p*f*s*a*z*y*t*n*u*y 1
 
0.2%
g*v*m*y*i*d*p*4*6*j*1*a*1*a*d*p*e*e*m*r*c*y 1
 
0.2%
h*v*c*y*x*r*q*s*3*d*f*u*k*g*x*2*q*4*w*t*k*m 1
 
0.2%
e*6*g*9*a*d*z*6*v*t*t*3*t*0*i*x*l*d*b*u*x*a 1
 
0.2%
0*k*4*b*t*a*a*j*i*x*j*d*i*l*4*o*y*n*m*e*k*0 1
 
0.2%
Other values (490) 490
98.0%
2024-04-18T04:24:49.811852image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
* 10980
50.0%
8 227
 
1.0%
c 217
 
1.0%
k 207
 
0.9%
A 207
 
0.9%
Q 202
 
0.9%
I 200
 
0.9%
M 194
 
0.9%
E 194
 
0.9%
w 194
 
0.9%
Other values (56) 9138
41.6%

Most occurring categories

ValueCountFrequency (%)
Other Punctuation 11121
50.6%
Uppercase Letter 4472
20.4%
Lowercase Letter 4448
 
20.3%
Decimal Number 1764
 
8.0%
Math Symbol 155
 
0.7%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
c 217
 
4.9%
k 207
 
4.7%
w 194
 
4.4%
g 194
 
4.4%
x 190
 
4.3%
q 182
 
4.1%
a 179
 
4.0%
t 178
 
4.0%
m 174
 
3.9%
l 174
 
3.9%
Other values (16) 2559
57.5%
Uppercase Letter
ValueCountFrequency (%)
A 207
 
4.6%
Q 202
 
4.5%
I 200
 
4.5%
M 194
 
4.3%
E 194
 
4.3%
Y 189
 
4.2%
U 187
 
4.2%
N 183
 
4.1%
T 182
 
4.1%
B 173
 
3.9%
Other values (16) 2561
57.3%
Decimal Number
ValueCountFrequency (%)
8 227
12.9%
1 189
10.7%
4 188
10.7%
6 184
10.4%
0 181
10.3%
2 176
10.0%
9 166
9.4%
7 164
9.3%
3 145
8.2%
5 144
8.2%
Other Punctuation
ValueCountFrequency (%)
* 10980
98.7%
/ 141
 
1.3%
Math Symbol
ValueCountFrequency (%)
+ 153
98.7%
= 2
 
1.3%

Most occurring scripts

ValueCountFrequency (%)
Common 13040
59.4%
Latin 8920
40.6%

Most frequent character per script

Latin
ValueCountFrequency (%)
c 217
 
2.4%
k 207
 
2.3%
A 207
 
2.3%
Q 202
 
2.3%
I 200
 
2.2%
M 194
 
2.2%
E 194
 
2.2%
w 194
 
2.2%
g 194
 
2.2%
x 190
 
2.1%
Other values (42) 6921
77.6%
Common
ValueCountFrequency (%)
* 10980
84.2%
8 227
 
1.7%
1 189
 
1.4%
4 188
 
1.4%
6 184
 
1.4%
0 181
 
1.4%
2 176
 
1.3%
9 166
 
1.3%
7 164
 
1.3%
+ 153
 
1.2%
Other values (4) 432
 
3.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 21960
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
* 10980
50.0%
8 227
 
1.0%
c 217
 
1.0%
k 207
 
0.9%
A 207
 
0.9%
Q 202
 
0.9%
I 200
 
0.9%
M 194
 
0.9%
E 194
 
0.9%
w 194
 
0.9%
Other values (56) 9138
41.6%
Distinct299
Distinct (%)59.8%
Missing0
Missing (%)0.0%
Memory size4.0 KiB
2024-04-18T04:24:49.962034image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length14
Median length14
Mean length8.748
Min length1

Characters and Unicode

Total characters4374
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

Unique298 ?
Unique (%)59.6%

Sample

1st row20180224104506
2nd row20170311161320
3rd row~
4th row~
5th row20170311035835
ValueCountFrequency (%)
202
40.4%
20190315084204 1
 
0.2%
20190220110641 1
 
0.2%
20200304112839 1
 
0.2%
20180503092114 1
 
0.2%
20191114103548 1
 
0.2%
20210130052932 1
 
0.2%
20201010075620 1
 
0.2%
20210313195954 1
 
0.2%
20210408040002 1
 
0.2%
Other values (289) 289
57.8%
2024-04-18T04:24:50.206822image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 1061
24.3%
1 843
19.3%
2 778
17.8%
5 248
 
5.7%
3 243
 
5.6%
4 242
 
5.5%
9 228
 
5.2%
~ 202
 
4.6%
7 201
 
4.6%
8 170
 
3.9%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 4172
95.4%
Math Symbol 202
 
4.6%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 1061
25.4%
1 843
20.2%
2 778
18.6%
5 248
 
5.9%
3 243
 
5.8%
4 242
 
5.8%
9 228
 
5.5%
7 201
 
4.8%
8 170
 
4.1%
6 158
 
3.8%
Math Symbol
ValueCountFrequency (%)
~ 202
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 4374
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 1061
24.3%
1 843
19.3%
2 778
17.8%
5 248
 
5.7%
3 243
 
5.6%
4 242
 
5.5%
9 228
 
5.2%
~ 202
 
4.6%
7 201
 
4.6%
8 170
 
3.9%

Most occurring blocks

ValueCountFrequency (%)
ASCII 4374
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 1061
24.3%
1 843
19.3%
2 778
17.8%
5 248
 
5.7%
3 243
 
5.6%
4 242
 
5.5%
9 228
 
5.2%
~ 202
 
4.6%
7 201
 
4.6%
8 170
 
3.9%
Distinct135
Distinct (%)27.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean58.718
Minimum1
Maximum196
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size4.5 KiB
2024-04-18T04:24:50.319411image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile4
Q125
median52
Q383
95-th percentile151
Maximum196
Range195
Interquartile range (IQR)58

Descriptive statistics

Standard deviation42.760395
Coefficient of variation (CV)0.72823316
Kurtosis1.4056075
Mean58.718
Median Absolute Deviation (MAD)28
Skewness1.1281174
Sum29359
Variance1828.4514
MonotonicityNot monotonic
2024-04-18T04:24:50.427259image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
89 13
 
2.6%
2 11
 
2.2%
28 11
 
2.2%
22 10
 
2.0%
72 9
 
1.8%
56 8
 
1.6%
24 8
 
1.6%
52 8
 
1.6%
70 8
 
1.6%
79 8
 
1.6%
Other values (125) 406
81.2%
ValueCountFrequency (%)
1 7
1.4%
2 11
2.2%
3 4
 
0.8%
4 6
1.2%
5 5
1.0%
6 2
 
0.4%
7 4
 
0.8%
8 2
 
0.4%
9 5
1.0%
10 2
 
0.4%
ValueCountFrequency (%)
196 2
0.4%
195 1
 
0.2%
194 1
 
0.2%
193 1
 
0.2%
190 4
0.8%
188 1
 
0.2%
184 2
0.4%
182 2
0.4%
181 1
 
0.2%
179 1
 
0.2%

교통수단CD(SUDAN_CD)
Real number (ℝ)

Distinct8
Distinct (%)1.6%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean152.952
Minimum105
Maximum205
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size4.5 KiB
2024-04-18T04:24:50.521488image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum105
5-th percentile105
Q1115
median120
Q3201
95-th percentile203
Maximum205
Range100
Interquartile range (IQR)86

Descriptive statistics

Standard deviation43.405642
Coefficient of variation (CV)0.28378604
Kurtosis-1.9111735
Mean152.952
Median Absolute Deviation (MAD)15
Skewness0.23042666
Sum76476
Variance1884.0498
MonotonicityNot monotonic
2024-04-18T04:24:50.596778image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=8)
ValueCountFrequency (%)
201 121
24.2%
115 110
22.0%
120 109
21.8%
203 82
16.4%
105 58
11.6%
205 15
 
3.0%
121 4
 
0.8%
130 1
 
0.2%
ValueCountFrequency (%)
105 58
11.6%
115 110
22.0%
120 109
21.8%
121 4
 
0.8%
130 1
 
0.2%
201 121
24.2%
203 82
16.4%
205 15
 
3.0%
ValueCountFrequency (%)
205 15
 
3.0%
203 82
16.4%
201 121
24.2%
130 1
 
0.2%
121 4
 
0.8%
120 109
21.8%
115 110
22.0%
105 58
11.6%
Distinct4
Distinct (%)0.8%
Missing0
Missing (%)0.0%
Memory size4.0 KiB
0
357 
1
120 
2
 
18
3
 
5

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row2
3rd row0
4th row1
5th row0

Common Values

ValueCountFrequency (%)
0 357
71.4%
1 120
 
24.0%
2 18
 
3.6%
3 5
 
1.0%

Length

2024-04-18T04:24:50.681784image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-18T04:24:50.753609image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 357
71.4%
1 120
 
24.0%
2 18
 
3.6%
3 5
 
1.0%
Distinct195
Distinct (%)39.0%
Missing0
Missing (%)0.0%
Memory size4.0 KiB
2024-04-18T04:24:50.971494image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/