Overview

Dataset statistics

Number of variables31
Number of observations168
Missing cells382
Missing cells (%)7.3%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory42.6 KiB
Average record size in memory259.8 B

Variable types

Text6
Categorical18
Numeric7

Alerts

급지구분 has constant value ""Constant
부제시행구분 has constant value ""Constant
요금정보 has constant value ""Constant
데이터기준일자 has constant value ""Constant
주차장구분 is highly imbalanced (52.7%)Imbalance
주차장유형 is highly imbalanced (65.1%)Imbalance
운영요일 is highly imbalanced (57.9%)Imbalance
공휴일운영시작시각 is highly imbalanced (78.7%)Imbalance
공휴일운영종료시각 is highly imbalanced (74.8%)Imbalance
1일주차권요금적용시간 is highly imbalanced (73.8%)Imbalance
결제방법 is highly imbalanced (88.3%)Imbalance
소재지도로명주소 has 48 (28.6%) missing valuesMissing
추가단위요금 has 48 (28.6%) missing valuesMissing
1일주차권요금 has 141 (83.9%) missing valuesMissing
월정기권요금 has 145 (86.3%) missing valuesMissing
주차장관리번호 has unique valuesUnique
주차기본요금 has 2 (1.2%) zerosZeros

Reproduction

Analysis started2024-04-17 21:49:08.136132
Analysis finished2024-04-17 21:49:08.562125
Duration0.43 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

주차장관리번호
Text

UNIQUE 

Distinct168
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size1.4 KiB
2024-04-18T06:49:08.692182image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length12
Median length12
Mean length12
Min length12

Characters and Unicode

Total characters2016
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

Unique168 ?
Unique (%)100.0%

Sample

1st row150-4-000076
2nd row150-4-000027
3rd row150-4-000028
4th row150-4-000029
5th row150-4-000030
ValueCountFrequency (%)
150-4-000076 1
 
0.6%
150-4-000166 1
 
0.6%
150-1-000001 1
 
0.6%
150-4-000026 1
 
0.6%
150-4-000160 1
 
0.6%
150-4-000161 1
 
0.6%
150-4-000162 1
 
0.6%
150-4-000163 1
 
0.6%
150-4-000164 1
 
0.6%
150-4-000165 1
 
0.6%
Other values (158) 158
94.0%
2024-04-18T06:49:08.992090image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 795
39.4%
- 336
16.7%
1 290
 
14.4%
5 204
 
10.1%
4 188
 
9.3%
2 44
 
2.2%
3 38
 
1.9%
6 36
 
1.8%
7 33
 
1.6%
9 27
 
1.3%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 1680
83.3%
Dash Punctuation 336
 
16.7%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 795
47.3%
1 290
 
17.3%
5 204
 
12.1%
4 188
 
11.2%
2 44
 
2.6%
3 38
 
2.3%
6 36
 
2.1%
7 33
 
2.0%
9 27
 
1.6%
8 25
 
1.5%
Dash Punctuation
ValueCountFrequency (%)
- 336
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 2016
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 795
39.4%
- 336
16.7%
1 290
 
14.4%
5 204
 
10.1%
4 188
 
9.3%
2 44
 
2.2%
3 38
 
1.9%
6 36
 
1.8%
7 33
 
1.6%
9 27
 
1.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 2016
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 795
39.4%
- 336
16.7%
1 290
 
14.4%
5 204
 
10.1%
4 188
 
9.3%
2 44
 
2.2%
3 38
 
1.9%
6 36
 
1.8%
7 33
 
1.6%
9 27
 
1.3%

주차장명
Text

Distinct142
Distinct (%)84.5%
Missing0
Missing (%)0.0%
Memory size1.4 KiB
2024-04-18T06:49:09.195611image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length18
Median length7
Mean length7.9166667
Min length5

Characters and Unicode

Total characters1330
Distinct characters159
Distinct categories4 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique123 ?
Unique (%)73.2%

Sample

1st row동아쇼핑별관유료주차장
2nd row건영유료주차장
3rd row계산문화관유료주차장
4th row계성유료주차장
5th row남산유료주차장
ValueCountFrequency (%)
노상주차장 10
 
5.2%
주변 5
 
2.6%
부근 4
 
2.1%
경북유료주차장 3
 
1.6%
현대유료주차장 3
 
1.6%
대구유료주차장 3
 
1.6%
한일유료주차장 3
 
1.6%
덕영유료주차장 3
 
1.6%
삼덕유료주차장 3
 
1.6%
봉산유료주차장 3
 
1.6%
Other values (140) 152
79.2%
2024-04-18T06:49:09.529278image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
주 177
13.3%
장 170
12.8%
차 168
12.6%
유 148
 
11.1%
료 148
 
11.1%
대 27
 
2.0%
24
 
1.8%
동 23
 
1.7%
성 20
 
1.5%
영 15
 
1.1%
Other values (149) 410
30.8%

Most occurring categories

ValueCountFrequency (%)
Other Letter 1296
97.4%
Space Separator 24
 
1.8%
Decimal Number 6
 
0.5%
Uppercase Letter 4
 
0.3%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
주 177
13.7%
장 170
13.1%
차 168
13.0%
유 148
 
11.4%
료 148
 
11.4%
대 27
 
2.1%
동 23
 
1.8%
성 20
 
1.5%
영 15
 
1.2%
산 14
 
1.1%
Other values (141) 386
29.8%
Uppercase Letter
ValueCountFrequency (%)
Z 1
25.0%
D 1
25.0%
S 1
25.0%
G 1
25.0%
Decimal Number
ValueCountFrequency (%)
2 3
50.0%
1 2
33.3%
4 1
 
16.7%
Space Separator
ValueCountFrequency (%)
24
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 1296
97.4%
Common 30
 
2.3%
Latin 4
 
0.3%

Most frequent character per script

Hangul
ValueCountFrequency (%)
주 177
13.7%
장 170
13.1%
차 168
13.0%
유 148
 
11.4%
료 148
 
11.4%
대 27
 
2.1%
동 23
 
1.8%
성 20
 
1.5%
영 15
 
1.2%
산 14
 
1.1%
Other values (141) 386
29.8%
Common
ValueCountFrequency (%)
24
80.0%
2 3
 
10.0%
1 2
 
6.7%
4 1
 
3.3%
Latin
ValueCountFrequency (%)
Z 1
25.0%
D 1
25.0%
S 1
25.0%
G 1
25.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 1296
97.4%
ASCII 34
 
2.6%

Most frequent character per block

Hangul
ValueCountFrequency (%)
주 177
13.7%
장 170
13.1%
차 168
13.0%
유 148
 
11.4%
료 148
 
11.4%
대 27
 
2.1%
동 23
 
1.8%
성 20
 
1.5%
영 15
 
1.2%
산 14
 
1.1%
Other values (141) 386
29.8%
ASCII
ValueCountFrequency (%)
24
70.6%
2 3
 
8.8%
1 2
 
5.9%
Z 1
 
2.9%
D 1
 
2.9%
S 1
 
2.9%
G 1
 
2.9%
4 1
 
2.9%

주차장구분
Categorical

IMBALANCE 

Distinct2
Distinct (%)1.2%
Missing0
Missing (%)0.0%
Memory size1.4 KiB
민영
151 
공영
17 

Length

Max length2
Median length2
Mean length2
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
민영 151
89.9%
공영 17
 
10.1%

Length

2024-04-18T06:49:09.641238image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-18T06:49:09.733704image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
민영 151
89.9%
공영 17
 
10.1%

주차장유형
Categorical

IMBALANCE 

Distinct2
Distinct (%)1.2%
Missing0
Missing (%)0.0%
Memory size1.4 KiB
노외
157 
노상
 
11

Length

Max length2
Median length2
Mean length2
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
노외 157
93.5%
노상 11
 
6.5%

Length

2024-04-18T06:49:09.829529image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-18T06:49:09.916600image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
노외 157
93.5%
노상 11
 
6.5%

소재지도로명주소
Text

MISSING 

Distinct120
Distinct (%)100.0%
Missing48
Missing (%)28.6%
Memory size1.4 KiB
2024-04-18T06:49:10.139436image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length29
Median length24
Mean length20.108333
Min length14

Characters and Unicode

Total characters2413
Distinct characters66
Distinct categories6 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique120 ?
Unique (%)100.0%

Sample

1st row대구광역시 중구 달성공원로 14
2nd row대구광역시 중구 서성로 10
3rd row대구광역시 중구 명륜로 19
4th row대구광역시 중구 국채보상로142길 33-29
5th row대구광역시 중구 중앙대로 354-42(남산동)
ValueCountFrequency (%)
대구광역시 120
24.3%
중구 120
24.3%
공평로 7
 
1.4%
국채보상로 6
 
1.2%
경상감영길 6
 
1.2%
동덕로 6
 
1.2%
중앙대로81길 4
 
0.8%
달성공원로 4
 
0.8%
태평로 4
 
0.8%
중앙대로 4
 
0.8%
Other values (168) 212
43.0%
2024-04-18T06:49:10.509689image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
373
15.5%
구 244
 
10.1%
대 141
 
5.8%
중 132
 
5.5%
시 122
 
5.1%
광 120
 
5.0%
역 120
 
5.0%
로 113
 
4.7%
1 98
 
4.1%
길 72
 
3.0%
Other values (56) 878
36.4%

Most occurring categories

ValueCountFrequency (%)
Other Letter 1502
62.2%
Decimal Number 440
 
18.2%
Space Separator 373
 
15.5%
Open Punctuation 35
 
1.5%
Close Punctuation 35
 
1.5%
Dash Punctuation 28
 
1.2%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
구 244
16.2%
대 141
9.4%
중 132
 
8.8%
시 122
 
8.1%
광 120
 
8.0%
역 120
 
8.0%
로 113
 
7.5%
길 72
 
4.8%
동 67
 
4.5%
성 41
 
2.7%
Other values (42) 330
22.0%
Decimal Number
ValueCountFrequency (%)
1 98
22.3%
2 67
15.2%
3 52
11.8%
4 50
11.4%
0 33
 
7.5%
6 30
 
6.8%
5 30
 
6.8%
9 29
 
6.6%
8 28
 
6.4%
7 23
 
5.2%
Space Separator
ValueCountFrequency (%)
373
100.0%
Open Punctuation
ValueCountFrequency (%)
( 35
100.0%
Close Punctuation
ValueCountFrequency (%)
) 35
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 28
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 1502
62.2%
Common 911
37.8%

Most frequent character per script

Hangul
ValueCountFrequency (%)
구 244
16.2%
대 141
9.4%
중 132
 
8.8%
시 122
 
8.1%
광 120
 
8.0%
역 120
 
8.0%
로 113
 
7.5%
길 72
 
4.8%
동 67
 
4.5%
성 41
 
2.7%
Other values (42) 330
22.0%
Common
ValueCountFrequency (%)
373
40.9%
1 98
 
10.8%
2 67
 
7.4%
3 52
 
5.7%
4 50
 
5.5%
( 35
 
3.8%
) 35
 
3.8%
0 33
 
3.6%
6 30
 
3.3%
5 30
 
3.3%
Other values (4) 108
 
11.9%

Most occurring blocks

ValueCountFrequency (%)
Hangul 1502
62.2%
ASCII 911
37.8%

Most frequent character per block

ASCII
ValueCountFrequency (%)
373
40.9%
1 98
 
10.8%
2 67
 
7.4%
3 52
 
5.7%
4 50
 
5.5%
( 35
 
3.8%
) 35
 
3.8%
0 33
 
3.6%
6 30
 
3.3%
5 30
 
3.3%
Other values (4) 108
 
11.9%
Hangul
ValueCountFrequency (%)
구 244
16.2%
대 141
9.4%
중 132
 
8.8%
시 122
 
8.1%
광 120
 
8.0%
역 120
 
8.0%
로 113
 
7.5%
길 72
 
4.8%
동 67
 
4.5%
성 41
 
2.7%
Other values (42) 330
22.0%

소재지지번주소
Text

Distinct164
Distinct (%)97.6%
Missing0
Missing (%)0.0%
Memory size1.4 KiB
2024-04-18T06:49:10.841082image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length21
Median length19
Mean length17.791667
Min length14

Characters and Unicode

Total characters2989
Distinct characters57
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

Unique160 ?
Unique (%)95.2%

Sample

1st row대구광역시 중구 남성로 84-1
2nd row대구광역시 중구 대신동 69-13
3rd row대구광역시 중구 계산동2가 70-3
4th row대구광역시 중구 대신동 259-5
5th row대구광역시 중구 남산동 437-1
ValueCountFrequency (%)
대구광역시 168
25.0%
중구 168
25.0%
삼덕동2가 15
 
2.2%
남산동 11
 
1.6%
봉산동 11
 
1.6%
대신동 10
 
1.5%
삼덕동1가 8
 
1.2%
동문동 6
 
0.9%
수창동 6
 
0.9%
대봉동 6
 
0.9%
Other values (192) 263
39.1%
2024-04-18T06:49:11.297951image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
504
16.9%
구 336
11.2%
대 187
 
6.3%
시 170
 
5.7%
동 170
 
5.7%
광 168
 
5.6%
역 168
 
5.6%
중 168
 
5.6%
1 159
 
5.3%
- 127
 
4.2%
Other values (47) 832
27.8%

Most occurring categories

ValueCountFrequency (%)
Other Letter 1738
58.1%
Decimal Number 620
 
20.7%
Space Separator 504
 
16.9%
Dash Punctuation 127
 
4.2%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
구 336
19.3%
대 187
10.8%
시 170
9.8%
동 170
9.8%
광 168
9.7%
역 168
9.7%
중 168
9.7%
가 67
 
3.9%
산 30
 
1.7%
로 28
 
1.6%
Other values (35) 246
14.2%
Decimal Number
ValueCountFrequency (%)
1 159
25.6%
2 119
19.2%
3 55
 
8.9%
5 51
 
8.2%
4 50
 
8.1%
6 43
 
6.9%
8 39
 
6.3%
9 39
 
6.3%
0 35
 
5.6%
7 30
 
4.8%
Space Separator
ValueCountFrequency (%)
504
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 127
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 1738
58.1%
Common 1251
41.9%

Most frequent character per script

Hangul
ValueCountFrequency (%)
구 336
19.3%
대 187
10.8%
시 170
9.8%
동 170
9.8%
광 168
9.7%
역 168
9.7%
중 168
9.7%
가 67
 
3.9%
산 30
 
1.7%
로 28
 
1.6%
Other values (35) 246
14.2%
Common
ValueCountFrequency (%)
504
40.3%
1 159
 
12.7%
- 127
 
10.2%
2 119
 
9.5%
3 55
 
4.4%
5 51
 
4.1%
4 50
 
4.0%
6 43
 
3.4%
8 39
 
3.1%
9 39
 
3.1%
Other values (2) 65
 
5.2%

Most occurring blocks

ValueCountFrequency (%)
Hangul 1738
58.1%
ASCII 1251
41.9%

Most frequent character per block

ASCII
ValueCountFrequency (%)
504
40.3%
1 159
 
12.7%
- 127
 
10.2%
2 119
 
9.5%
3 55
 
4.4%
5 51
 
4.1%
4 50
 
4.0%
6 43
 
3.4%
8 39
 
3.1%
9 39
 
3.1%
Other values (2) 65
 
5.2%
Hangul
ValueCountFrequency (%)
구 336
19.3%
대 187
10.8%
시 170
9.8%
동 170
9.8%
광 168
9.7%
역 168
9.7%
중 168
9.7%
가 67
 
3.9%
산 30
 
1.7%
로 28
 
1.6%
Other values (35) 246
14.2%

주차구획수
Real number (ℝ)

Distinct62
Distinct (%)36.9%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean43.583333
Minimum5
Maximum305
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.6 KiB
2024-04-18T06:49:11.416526image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum5
5-th percentile10
Q116
median26
Q343.5
95-th percentile157.4
Maximum305
Range300
Interquartile range (IQR)27.5

Descriptive statistics

Standard deviation55.871797
Coefficient of variation (CV)1.2819533
Kurtosis11.602669
Mean43.583333
Median Absolute Deviation (MAD)11.5
Skewness3.3240198
Sum7322
Variance3121.6577
MonotonicityNot monotonic
2024-04-18T06:49:11.527511image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
20 15
 
8.9%
30 14
 
8.3%
10 10
 
6.0%
15 9
 
5.4%
50 8
 
4.8%
25 6
 
3.6%
35 6
 
3.6%
18 6
 
3.6%
11 5
 
3.0%
17 5
 
3.0%
Other values (52) 84
50.0%
ValueCountFrequency (%)
5 1
 
0.6%
7 2
 
1.2%
8 3
 
1.8%
10 10
6.0%
11 5
3.0%
12 4
 
2.4%
13 3
 
1.8%
14 3
 
1.8%
15 9
5.4%
16 3
 
1.8%
ValueCountFrequency (%)
305 1
0.6%
300 2
1.2%
297 1
0.6%
282 1
0.6%
208 1
0.6%
200 1
0.6%
194 1
0.6%
170 1
0.6%
134 1
0.6%
129 1
0.6%

급지구분
Categorical

CONSTANT 

Distinct1
Distinct (%)0.6%
Missing0
Missing (%)0.0%
Memory size1.4 KiB
1
168 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
1 168
100.0%

Length

2024-04-18T06:49:11.675962image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-18T06:49:11.767280image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
1 168
100.0%

부제시행구분
Categorical

CONSTANT 

Distinct1
Distinct (%)0.6%
Missing0
Missing (%)0.0%
Memory size1.4 KiB
미시행
168 

Length

Max length3
Median length3
Mean length3
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
미시행 168
100.0%

Length

2024-04-18T06:49:11.849217image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-18T06:49:11.951307image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
미시행 168
100.0%

운영요일
Categorical

IMBALANCE 

Distinct3
Distinct (%)1.8%
Missing0
Missing (%)0.0%
Memory size1.4 KiB
평일+토요일
145 
평일+토요일+공휴일
19 
평일
 
4

Length

Max length10
Median length6
Mean length6.3571429
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row평일+토요일+공휴일
2nd row평일+토요일
3rd row평일+토요일+공휴일
4th row평일+토요일
5th row평일+토요일

Common Values

ValueCountFrequency (%)
평일+토요일 145
86.3%
평일+토요일+공휴일 19
 
11.3%
평일 4
 
2.4%

Length

2024-04-18T06:49:12.067931image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-18T06:49:12.171368image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
평일+토요일 145
86.3%
평일+토요일+공휴일 19
 
11.3%
평일 4
 
2.4%

평일운영시작시각
Categorical

Distinct15
Distinct (%)8.9%
Missing0
Missing (%)0.0%
Memory size1.4 KiB
08:00
64 
09:00
39 
07:00
13 
10:00
12 
00:00
10 
Other values (10)
30 

Length

Max length5
Median length5
Mean length5
Min length5

Unique

Unique5 ?
Unique (%)3.0%

Sample

1st row10:00
2nd row08:00
3rd row00:00
4th row08:00
5th row08:00

Common Values

ValueCountFrequency (%)
08:00 64
38.1%
09:00 39
23.2%
07:00 13
 
7.7%
10:00 12
 
7.1%
00:00 10
 
6.0%
07:30 9
 
5.4%
08:30 8
 
4.8%
09:30 3
 
1.8%
06:00 3
 
1.8%
11:00 2
 
1.2%
Other values (5) 5
 
3.0%

Length

2024-04-18T06:49:12.261558image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
08:00 64
38.1%
09:00 39
23.2%
07:00 13
 
7.7%
10:00 12
 
7.1%
00:00 10
 
6.0%
07:30 9
 
5.4%
08:30 8
 
4.8%
09:30 3
 
1.8%
06:00 3
 
1.8%
11:00 2
 
1.2%
Other values (5) 5
 
3.0%

평일운영종료시각
Categorical

Distinct18
Distinct (%)10.7%
Missing0
Missing (%)0.0%
Memory size1.4 KiB
20:00
34 
18:00
28 
23:59
19 
22:00
19 
19:00
17 
Other values (13)
51 

Length

Max length5
Median length5
Mean length5
Min length5

Unique

Unique4 ?
Unique (%)2.4%

Sample

1st row21:30
2nd row19:00
3rd row23:59
4th row20:00
5th row19:00

Common Values

ValueCountFrequency (%)
20:00 34
20.2%
18:00 28
16.7%
23:59 19
11.3%
22:00 19
11.3%
19:00 17
10.1%
21:00 16
9.5%
23:00 14
8.3%
20:30 4
 
2.4%
19:30 3
 
1.8%
01:00 2
 
1.2%
Other values (8) 12
 
7.1%

Length

2024-04-18T06:49:12.360193image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
20:00 34
20.2%
18:00 28
16.7%
23:59 19
11.3%
22:00 19
11.3%
19:00 17
10.1%
21:00 16
9.5%
23:00 14
8.3%
20:30 4
 
2.4%
19:30 3
 
1.8%
00:00 2
 
1.2%
Other values (8) 12
 
7.1%

토요일운영시작시각
Categorical

Distinct14
Distinct (%)8.3%
Missing0
Missing (%)0.0%
Memory size1.4 KiB
08:00
61 
09:00
37 
00:00
15 
07:00
13 
10:00
12 
Other values (9)
30 

Length

Max length5
Median length5
Mean length5
Min length5

Unique

Unique4 ?
Unique (%)2.4%

Sample

1st row10:00
2nd row08:00
3rd row00:00
4th row08:00
5th row08:00

Common Values

ValueCountFrequency (%)
08:00 61
36.3%
09:00 37
22.0%
00:00 15
 
8.9%
07:00 13
 
7.7%
10:00 12
 
7.1%
07:30 9
 
5.4%
08:30 9
 
5.4%
09:30 3
 
1.8%
06:00 3
 
1.8%
11:00 2
 
1.2%
Other values (4) 4
 
2.4%

Length

2024-04-18T06:49:12.463315image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
08:00 61
36.3%
09:00 37
22.0%
00:00 15
 
8.9%
07:00 13
 
7.7%
10:00 12
 
7.1%
07:30 9
 
5.4%
08:30 9
 
5.4%
09:30 3
 
1.8%
06:00 3
 
1.8%
11:00 2
 
1.2%
Other values (4) 4
 
2.4%

토요일운영종료시각
Categorical

Distinct18
Distinct (%)10.7%
Missing0
Missing (%)0.0%
Memory size1.4 KiB
20:00
30 
18:00
28 
22:00
20 
23:59
19 
19:00
17 
Other values (13)
54 

Length

Max length5
Median length5
Mean length5
Min length5

Unique

Unique4 ?
Unique (%)2.4%

Sample

1st row21:30
2nd row19:00
3rd row23:59
4th row20:00
5th row19:00

Common Values

ValueCountFrequency (%)
20:00 30
17.9%
18:00 28
16.7%
22:00 20
11.9%
23:59 19
11.3%
19:00 17
10.1%
21:00 15
8.9%
23:00 13
7.7%
00:00 7
 
4.2%
20:30 4
 
2.4%
19:30 3
 
1.8%
Other values (8) 12
 
7.1%

Length

2024-04-18T06:49:12.584060image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
20:00 30
17.9%
18:00 28
16.7%
22:00 20
11.9%
23:59 19
11.3%
19:00 17
10.1%
21:00 15
8.9%
23:00 13
7.7%
00:00 7
 
4.2%
20:30 4
 
2.4%
19:30 3
 
1.8%
Other values (8) 12
 
7.1%

공휴일운영시작시각
Categorical

IMBALANCE 

Distinct7
Distinct (%)4.2%
Missing0
Missing (%)0.0%
Memory size1.4 KiB
00:00
154 
08:00
 
6
10:00
 
3
09:00
 
2
07:00
 
1
Other values (2)
 
2

Length

Max length5
Median length5
Mean length5
Min length5

Unique

Unique3 ?
Unique (%)1.8%

Sample

1st row10:00
2nd row00:00
3rd row00:00
4th row00:00
5th row00:00

Common Values

ValueCountFrequency (%)
00:00 154
91.7%
08:00 6
 
3.6%
10:00 3
 
1.8%
09:00 2
 
1.2%
07:00 1
 
0.6%
11:00 1
 
0.6%
06:00 1
 
0.6%

Length

2024-04-18T06:49:12.691981image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-18T06:49:12.791574image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
00:00 154
91.7%
08:00 6
 
3.6%
10:00 3
 
1.8%
09:00 2
 
1.2%
07:00 1
 
0.6%
11:00 1
 
0.6%
06:00 1
 
0.6%

공휴일운영종료시각
Categorical

IMBALANCE 

Distinct8
Distinct (%)4.8%
Missing0
Missing (%)0.0%
Memory size1.4 KiB
00:00
150 
23:59
 
7
20:00
 
3
23:00
 
2
01:00
 
2
Other values (3)
 
4

Length

Max length5
Median length5
Mean length5
Min length5

Unique

Unique2 ?
Unique (%)1.2%

Sample

1st row21:30
2nd row00:00
3rd row23:59
4th row00:00
5th row00:00

Common Values

ValueCountFrequency (%)
00:00 150
89.3%
23:59 7
 
4.2%
20:00 3
 
1.8%
23:00 2
 
1.2%
01:00 2
 
1.2%
22:00 2
 
1.2%
21:30 1
 
0.6%
18:00 1
 
0.6%

Length

2024-04-18T06:49:12.905337image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-18T06:49:13.423587image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
00:00 150
89.3%
23:59 7
 
4.2%
20:00 3
 
1.8%
23:00 2
 
1.2%
01:00 2
 
1.2%
22:00 2
 
1.2%
21:30 1
 
0.6%
18:00 1
 
0.6%

요금정보
Categorical

CONSTANT 

Distinct1
Distinct (%)0.6%
Missing0
Missing (%)0.0%
Memory size1.4 KiB
유료
168 

Length

Max length2
Median length2
Mean length2
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
유료 168
100.0%

Length

2024-04-18T06:49:13.521875image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-18T06:49:13.599645image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
유료 168
100.0%

주차기본시간
Categorical

Distinct3
Distinct (%)1.8%
Missing0
Missing (%)0.0%
Memory size1.4 KiB
30
133 
60
33 
0
 
2

Length

Max length2
Median length2
Mean length1.9880952
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row30
2nd row30
3rd row30
4th row30
5th row30

Common Values

ValueCountFrequency (%)
30 133
79.2%
60 33
 
19.6%
0 2
 
1.2%

Length

2024-04-18T06:49:13.688408image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-18T06:49:13.777533image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
30 133
79.2%
60 33
 
19.6%
0 2
 
1.2%

주차기본요금
Real number (ℝ)

ZEROS 

Distinct8
Distinct (%)4.8%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1040.4762
Minimum0
Maximum2000
Zeros2
Zeros (%)1.2%
Negative0
Negative (%)0.0%
Memory size1.6 KiB
2024-04-18T06:49:13.855442image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile600
Q11000
median1000
Q31000
95-th percentile1500
Maximum2000
Range2000
Interquartile range (IQR)0

Descriptive statistics

Standard deviation282.04516
Coefficient of variation (CV)0.27107315
Kurtosis5.436305
Mean1040.4762
Median Absolute Deviation (MAD)0
Skewness0.87289321
Sum174800
Variance79549.472
MonotonicityNot monotonic
2024-04-18T06:49:13.964784image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=8)
ValueCountFrequency (%)
1000 132
78.6%
1500 14
 
8.3%
2000 6
 
3.6%
500 6
 
3.6%
800 4
 
2.4%
600 2
 
1.2%
1200 2
 
1.2%
0 2
 
1.2%
ValueCountFrequency (%)
0 2
 
1.2%
500 6
 
3.6%
600 2
 
1.2%
800 4
 
2.4%
1000 132
78.6%
1200 2
 
1.2%
1500 14
 
8.3%
2000 6
 
3.6%
ValueCountFrequency (%)
2000 6
 
3.6%
1500 14
 
8.3%
1200 2
 
1.2%
1000 132
78.6%
800 4
 
2.4%
600 2
 
1.2%
500 6
 
3.6%
0 2
 
1.2%

추가단위시간
Categorical

Distinct5
Distinct (%)3.0%
Missing0
Missing (%)0.0%
Memory size1.4 KiB
30
65 
<NA>
48 
60
28 
10
24 
15
 
3

Length

Max length4
Median length2
Mean length2.5714286
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row<NA>
2nd row30
3rd row<NA>
4th row30
5th row30

Common Values

ValueCountFrequency (%)
30 65
38.7%
<NA> 48
28.6%
60 28
16.7%
10 24
 
14.3%
15 3
 
1.8%

Length

2024-04-18T06:49:14.080495image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-18T06:49:14.195005image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
30 65
38.7%
na 48
28.6%
60 28
16.7%
10 24
 
14.3%
15 3
 
1.8%

추가단위요금
Real number (ℝ)

MISSING 

Distinct9
Distinct (%)7.5%
Missing48
Missing (%)28.6%
Infinite0
Infinite (%)0.0%
Mean917.5
Minimum200
Maximum2000
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.6 KiB
2024-04-18T06:49:14.285182image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum200
5-th percentile250
Q1600
median1000
Q31000
95-th percentile1500
Maximum2000
Range1800
Interquartile range (IQR)400

Descriptive statistics

Standard deviation352.40172
Coefficient of variation (CV)0.38408907
Kurtosis0.71728623
Mean917.5
Median Absolute Deviation (MAD)0
Skewness0.12531505
Sum110100
Variance124186.97
MonotonicityNot monotonic
2024-04-18T06:49:14.377927image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=9)
ValueCountFrequency (%)
1000 74
44.0%
500 19
 
11.3%
1500 12
 
7.1%
250 6
 
3.6%
300 3
 
1.8%
600 2
 
1.2%
2000 2
 
1.2%
200 1
 
0.6%
800 1
 
0.6%
(Missing) 48
28.6%
ValueCountFrequency (%)
200 1
 
0.6%
250 6
 
3.6%
300 3
 
1.8%
500 19
 
11.3%
600 2
 
1.2%
800 1
 
0.6%
1000 74
44.0%
1500 12
 
7.1%
2000 2
 
1.2%
ValueCountFrequency (%)
2000 2
 
1.2%
1500 12
 
7.1%
1000 74
44.0%
800 1
 
0.6%
600 2
 
1.2%
500 19
 
11.3%
300 3
 
1.8%
250 6
 
3.6%
200 1
 
0.6%

1일주차권요금적용시간
Categorical

IMBALANCE 

Distinct5
Distinct (%)3.0%
Missing0
Missing (%)0.0%
Memory size1.4 KiB
<NA>
150 
3.5
 
14
4.5
 
2
8.0
 
1
10.0
 
1

Length

Max length4
Median length4
Mean length3.8988095
Min length3

Unique

Unique2 ?
Unique (%)1.2%

Sample

1st row<NA>
2nd row<NA>
3rd row<NA>
4th row<NA>
5th row<NA>

Common Values

ValueCountFrequency (%)
<NA> 150
89.3%
3.5 14
 
8.3%
4.5 2
 
1.2%
8.0 1
 
0.6%
10.0 1
 
0.6%

Length

2024-04-18T06:49:14.488235image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-18T06:49:14.591352image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 150
89.3%
3.5 14
 
8.3%
4.5 2
 
1.2%
8.0 1
 
0.6%
10.0 1
 
0.6%

1일주차권요금
Real number (ℝ)

MISSING 

Distinct7
Distinct (%)25.9%
Missing141
Missing (%)83.9%
Infinite0
Infinite (%)0.0%
Mean10037.037
Minimum3000
Maximum50000
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.6 KiB
2024-04-18T06:49:14.694595image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum3000
5-th percentile5000
Q16000
median10000
Q310000
95-th percentile13500
Maximum50000
Range47000
Interquartile range (IQR)4000

Descriptive statistics

Standard deviation8414.646
Coefficient of variation (CV)0.83835957
Kurtosis21.341894
Mean10037.037
Median Absolute Deviation (MAD)0
Skewness4.3771853
Sum271000
Variance70806268
MonotonicityNot monotonic
2024-04-18T06:49:14.808846image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=7)
ValueCountFrequency (%)
10000 15
 
8.9%
5000 6
 
3.6%
8000 2
 
1.2%
50000 1
 
0.6%
15000 1
 
0.6%
7000 1
 
0.6%
3000 1
 
0.6%
(Missing) 141
83.9%
ValueCountFrequency (%)
3000 1
 
0.6%
5000 6
 
3.6%
7000 1
 
0.6%
8000 2
 
1.2%
10000 15
8.9%
15000 1
 
0.6%
50000 1
 
0.6%
ValueCountFrequency (%)
50000 1
 
0.6%
15000 1
 
0.6%
10000 15
8.9%
8000 2
 
1.2%
7000 1
 
0.6%
5000 6
 
3.6%
3000 1
 
0.6%

월정기권요금
Real number (ℝ)

MISSING 

Distinct6
Distinct (%)26.1%
Missing145
Missing (%)86.3%
Infinite0
Infinite (%)0.0%
Mean86086.957
Minimum50000
Maximum120000
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.6 KiB
2024-04-18T06:49:14.896138image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum50000
5-th percentile50000
Q165000
median100000
Q3100000
95-th percentile100000
Maximum120000
Range70000
Interquartile range (IQR)35000

Descriptive statistics

Standard deviation22711.457
Coefficient of variation (CV)0.26381995
Kurtosis-1.0190608
Mean86086.957
Median Absolute Deviation (MAD)0
Skewness-0.76666817
Sum1980000
Variance5.1581028 × 108
MonotonicityNot monotonic
2024-04-18T06:49:14.997085image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=6)
ValueCountFrequency (%)
100000 14
 
8.3%
50000 5
 
3.0%
70000 1
 
0.6%
80000 1
 
0.6%
60000 1
 
0.6%
120000 1
 
0.6%
(Missing) 145
86.3%
ValueCountFrequency (%)
50000 5
 
3.0%
60000 1
 
0.6%
70000 1
 
0.6%
80000 1
 
0.6%
100000 14
8.3%
120000 1
 
0.6%
ValueCountFrequency (%)
120000 1
 
0.6%
100000 14
8.3%
80000 1
 
0.6%
70000 1
 
0.6%
60000 1
 
0.6%
50000 5
 
3.0%

결제방법
Categorical

IMBALANCE 

Distinct3
Distinct (%)1.8%
Missing0
Missing (%)0.0%
Memory size1.4 KiB
현금
164 
현금+신용카드
 
2
신용카드
 
2

Length

Max length7
Median length2
Mean length2.0833333
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
현금 164
97.6%
현금+신용카드 2
 
1.2%
신용카드 2
 
1.2%

Length

2024-04-18T06:49:15.119641image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-18T06:49:15.259212image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
현금 164
97.6%
현금+신용카드 2
 
1.2%
신용카드 2
 
1.2%

특기사항
Categorical

Distinct14
Distinct (%)8.3%
Missing0
Missing (%)0.0%
Memory size1.4 KiB
<NA>
112 
경차+장애인+국가유공자 할인
16 
1시간 2000원
12 
1시간 1500원
 
9
1시간 2200원
 
4
Other values (9)
15 

Length

Max length28
Median length4
Mean length6.547619
Min length4

Unique

Unique5 ?
Unique (%)3.0%

Sample

1st row<NA>
2nd row<NA>
3rd row<NA>
4th row<NA>
5th row<NA>

Common Values

ValueCountFrequency (%)
<NA> 112
66.7%
경차+장애인+국가유공자 할인 16
 
9.5%
1시간 2000원 12
 
7.1%
1시간 1500원 9
 
5.4%
1시간 2200원 4
 
2.4%
1시간 1900원 3
 
1.8%
1시간 2500원 3
 
1.8%
1시간 1200원 2
 
1.2%
1시간 2000원+2시간 3000원 2
 
1.2%
2시간 2000원+2시간 이상 3000원 1
 
0.6%
Other values (4) 4
 
2.4%

Length

2024-04-18T06:49:15.389767image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
na 112
48.1%
1시간 37
 
15.9%
경차+장애인+국가유공자 16
 
6.9%
할인 16
 
6.9%
2000원 13
 
5.6%
1500원 9
 
3.9%
3000원 4
 
1.7%
2200원 4
 
1.7%
1900원 3
 
1.3%
2500원 3
 
1.3%
Other values (12) 16
 
6.9%

관리기관명
Text

Distinct126
Distinct (%)75.0%
Missing0
Missing (%)0.0%
Memory size1.4 KiB
2024-04-18T06:49:15.637825image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length11
Median length7
Mean length7.4940476
Min length5

Characters and Unicode

Total characters1259
Distinct characters133
Distinct categories4 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique106 ?
Unique (%)63.1%

Sample

1st row동아쇼핑별관유료주차장
2nd row건영유료주차장
3rd row계산문화관유료주차장
4th row계성유료주차장
5th row남산유료주차장
ValueCountFrequency (%)
대구광역시 17
 
9.1%
중구청 17
 
9.1%
대구유료주차장 3
 
1.6%
현대유료주차장 3
 
1.6%
봉산유료주차장 3
 
1.6%
경북유료주차장 3
 
1.6%
한일유료주차장 3
 
1.6%
삼덕유료주차장 3
 
1.6%
덕영유료주차장 3
 
1.6%
제일유료주차장 2
 
1.1%
Other values (118) 129
69.4%
2024-04-18T06:49:16.060577image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
장 152
12.1%
주 151
12.0%
차 150
11.9%
유 148
11.8%
료 148
11.8%
대 41
 
3.3%
구 39
 
3.1%
중 23
 
1.8%
광 22
 
1.7%
시 21
 
1.7%
Other values (123) 364
28.9%

Most occurring categories

ValueCountFrequency (%)
Other Letter 1234
98.0%
Space Separator 18
 
1.4%
Uppercase Letter 4
 
0.3%
Decimal Number 3
 
0.2%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
장 152
12.3%
주 151
12.2%
차 150
12.2%
유 148
12.0%
료 148
12.0%
대 41
 
3.3%
구 39
 
3.2%
중 23
 
1.9%
광 22
 
1.8%
시 21
 
1.7%
Other values (117) 339
27.5%
Uppercase Letter
ValueCountFrequency (%)
S 1
25.0%
G 1
25.0%
D 1
25.0%
Z 1
25.0%
Space Separator
ValueCountFrequency (%)
18
100.0%
Decimal Number
ValueCountFrequency (%)
2 3
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 1234
98.0%
Common 21
 
1.7%
Latin 4
 
0.3%

Most frequent character per script

Hangul
ValueCountFrequency (%)
장 152
12.3%
주 151
12.2%
차 150
12.2%
유 148
12.0%
료 148
12.0%
대 41
 
3.3%
구 39
 
3.2%
중 23
 
1.9%
광 22
 
1.8%
시 21
 
1.7%
Other values (117) 339
27.5%
Latin
ValueCountFrequency (%)
S 1
25.0%
G 1
25.0%
D 1
25.0%
Z 1
25.0%
Common
ValueCountFrequency (%)
18
85.7%
2 3
 
14.3%

Most occurring blocks

ValueCountFrequency (%)
Hangul 1234
98.0%
ASCII 25
 
2.0%

Most frequent character per block

Hangul
ValueCountFrequency (%)
장 152
12.3%
주 151
12.2%
차 150
12.2%
유 148
12.0%
료 148
12.0%
대 41
 
3.3%
구 39
 
3.2%
중 23
 
1.9%
광 22
 
1.8%
시 21
 
1.7%
Other values (117) 339
27.5%
ASCII
ValueCountFrequency (%)
18
72.0%
2 3
 
12.0%
S 1
 
4.0%
G 1
 
4.0%
D 1
 
4.0%
Z 1
 
4.0%

전화번호
Text

Distinct90
Distinct (%)53.6%
Missing0
Missing (%)0.0%
Memory size1.4 KiB
2024-04-18T06:49:16.322472image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length12
Median length12
Mean length12
Min length12

Characters and Unicode

Total characters2016
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

Unique87 ?
Unique (%)51.8%

Sample

1st row053-123-4567
2nd row053-555-2001
3rd row053-251-1680
4th row053-123-4567
5th row053-123-4567
ValueCountFrequency (%)
053-123-4567 63
37.5%
053-661-3173 16
 
9.5%
053-255-0525 2
 
1.2%
053-241-7002 1
 
0.6%
053-254-5498 1
 
0.6%
053-253-6999 1
 
0.6%
053-428-7177 1
 
0.6%
053-424-8266 1
 
0.6%
053-568-7452 1
 
0.6%
053-255-5860 1
 
0.6%
Other values (80) 80
47.6%
2024-04-18T06:49:16.662875image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
- 336
16.7%
5 330
16.4%
3 315
15.6%
0 218
10.8%
2 185
9.2%
4 161
8.0%
6 144
7.1%
1 137
6.8%
7 133
 
6.6%
8 35
 
1.7%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 1680
83.3%
Dash Punctuation 336
 
16.7%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
5 330
19.6%
3 315
18.8%
0 218
13.0%
2 185
11.0%
4 161
9.6%
6 144
8.6%
1 137
8.2%
7 133
7.9%
8 35
 
2.1%
9 22
 
1.3%
Dash Punctuation
ValueCountFrequency (%)
- 336
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 2016
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
- 336
16.7%
5 330
16.4%
3 315
15.6%
0 218
10.8%
2 185
9.2%
4 161
8.0%
6 144
7.1%
1 137
6.8%
7 133
 
6.6%
8 35
 
1.7%

Most occurring blocks

ValueCountFrequency (%)
ASCII 2016
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
- 336
16.7%
5 330
16.4%
3 315
15.6%
0 218
10.8%
2 185
9.2%
4 161
8.0%
6 144
7.1%
1 137
6.8%
7 133
 
6.6%
8 35
 
1.7%

위도
Real number (ℝ)

Distinct167
Distinct (%)99.4%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean35.868829
Minimum35.855715
Maximum35.876325
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.6 KiB
2024-04-18T06:49:16.799598image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum35.855715
5-th percentile35.860378
Q135.866259
median35.869328
Q335.872079
95-th percentile35.874777
Maximum35.876325
Range0.02060984
Interquartile range (IQR)0.0058202625

Descriptive statistics

Standard deviation0.0045292252
Coefficient of variation (CV)0.0001262719
Kurtosis0.015063312
Mean35.868829
Median Absolute Deviation (MAD)0.003027565
Skewness-0.66833332
Sum6025.9632
Variance2.051388 × 10-5
MonotonicityNot monotonic
2024-04-18T06:49:16.936109image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
35.87177174 2
 
1.2%
35.86642142 1
 
0.6%
35.86428119 1
 
0.6%
35.86896422 1
 
0.6%
35.86836398 1
 
0.6%
35.87459648 1
 
0.6%
35.87069954 1
 
0.6%
35.866317 1
 
0.6%
35.87455396 1
 
0.6%
35.86798375 1
 
0.6%
Other values (157) 157
93.5%
ValueCountFrequency (%)
35.85571524 1
0.6%
35.85586261 1
0.6%
35.85718972 1
0.6%
35.8574236 1
0.6%
35.8587307 1
0.6%
35.85903497 1
0.6%
35.85929974 1
0.6%
35.85974263 1
0.6%
35.860076 1
0.6%
35.860938 1
0.6%
ValueCountFrequency (%)
35.87632508 1
0.6%
35.8760471 1
0.6%
35.87569661 1
0.6%
35.87562417 1
0.6%
35.8750398 1
0.6%
35.87503331 1
0.6%
35.87490662 1
0.6%
35.87486539 1
0.6%
35.87484043 1
0.6%
35.874659 1
0.6%

경도
Real number (ℝ)

Distinct165
Distinct (%)98.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean128.5939
Minimum128.5742
Maximum128.61248
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.6 KiB
2024-04-18T06:49:17.049330image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum128.5742
5-th percentile128.58006
Q1128.58932
median128.59366
Q3128.59946
95-th percentile128.60588
Maximum128.61248
Range0.0382895
Interquartile range (IQR)0.0101426

Descriptive statistics

Standard deviation0.0078647061
Coefficient of variation (CV)6.1159245 × 10-5
Kurtosis-0.28052508
Mean128.5939
Median Absolute Deviation (MAD)0.00559975
Skewness-0.33613642
Sum21603.776
Variance6.1853602 × 10-5
MonotonicityNot monotonic
2024-04-18T06:49:17.173132image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
128.5985915 2
 
1.2%
128.5930125 2
 
1.2%
128.5971644 2
 
1.2%
128.5914102 1
 
0.6%
128.602642 1
 
0.6%
128.593606 1
 
0.6%
128.603078 1
 
0.6%
128.602434 1
 
0.6%
128.591605 1
 
0.6%
128.5930188 1
 
0.6%
Other values (155) 155
92.3%
ValueCountFrequency (%)
128.574195 1
0.6%
128.5743671 1
0.6%
128.5759201 1
0.6%
128.5761695 1
0.6%
128.576754 1
0.6%
128.576874 1
0.6%
128.5787446 1
0.6%
128.579693 1
0.6%
128.5799537 1
0.6%
128.5802556 1
0.6%
ValueCountFrequency (%)
128.6124845 1
0.6%
128.609621 1
0.6%
128.6080343 1
0.6%
128.6064945 1
0.6%
128.6064066 1
0.6%
128.6063962 1
0.6%
128.6063792 1
0.6%
128.6059928 1
0.6%
128.6059047 1
0.6%
128.6058385 1
0.6%

데이터기준일자
Categorical

CONSTANT 

Distinct1
Distinct (%)0.6%
Missing0
Missing (%)0.0%
Memory size1.4 KiB
2023-07-10
168 

Length

Max length10
Median length10
Mean length10
Min length10

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row2023-07-10
2nd row2023-07-10
3rd row2023-07-10
4th row2023-07-10
5th row2023-07-10

Common Values

ValueCountFrequency (%)
2023-07-10 168
100.0%

Length

2024-04-18T06:49:17.289512image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-18T06:49:17.378282image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2023-07-10 168
100.0%

Sample

주차장관리번호주차장명주차장구분주차장유형소재지도로명주소소재지지번주소주차구획수급지구분부제시행구분운영요일평일운영시작시각평일운영종료시각토요일운영시작시각토요일운영종료시각공휴일운영시작시각공휴일운영종료시각요금정보주차기본시간주차기본요금추가단위시간추가단위요금1일주차권요금적용시간1일주차권요금월정기권요금결제방법특기사항관리기관명전화번호위도경도데이터기준일자
0150-4-000076동아쇼핑별관유료주차장민영노외<NA>대구광역시 중구 남성로 84-12821미시행평일+토요일+공휴일10:0021:3010:0021:3010:0021:30유료301000<NA><NA><NA><NA><NA>현금<NA>동아쇼핑별관유료주차장053-123-456735.867477128.591412023-07-10
1150-4-000027건영유료주차장민영노외대구광역시 중구 달성공원로 14대구광역시 중구 대신동 69-13101미시행평일+토요일08:0019:0008:0019:0000:0000:00유료301000301000<NA><NA><NA>현금<NA>건영유료주차장053-555-200135.871772128.5796932023-07-10
2150-4-000028계산문화관유료주차장민영노외대구광역시 중구 서성로 10대구광역시 중구 계산동2가 70-33001미시행평일+토요일+공휴일00:0023:5900:0023:5900:0023:59유료30800<NA><NA><NA><NA><NA>현금<NA>계산문화관유료주차장053-251-168035.873324128.5870612023-07-10
3150-4-000029계성유료주차장민영노외<NA>대구광역시 중구 대신동 259-5781미시행평일+토요일08:0020:0008:0020:0000:0000:00유료301500301500<NA><NA><NA>현금<NA>계성유료주차장053-123-456735.86845128.5818732023-07-10
4150-4-000030남산유료주차장민영노외대구광역시 중구 명륜로 19대구광역시 중구 남산동 437-1251미시행평일+토요일08:0019:0008:0019:0000:0000:00유료301000301000<NA><NA><NA>현금<NA>남산유료주차장053-123-456735.864743128.5889482023-07-10
5150-4-000031뉴대구유료주차장민영노외대구광역시 중구 국채보상로142길 33-29대구광역시 중구 동인동4가 400-4251미시행평일+토요일07:0022:0007:0022:0000:0000:00유료601000<NA><NA><NA><NA><NA>현금2시간 2000원+2시간 이상 3000원뉴대구유료주차장053-123-456735.867054128.6096212023-07-10
6150-4-000032달성빌딩유료주차장민영노외<NA>대구광역시 중구 달성동 259-152001미시행평일+토요일+공휴일00:0023:5900:0023:5900:0023:59유료301000301000<NA><NA><NA>현금<NA>달성빌딩유료주차장053-554-117635.873721128.5809282023-07-10
7150-4-000033대구유료주차장민영노외대구광역시 중구 중앙대로 354-42(남산동)대구광역시 중구 남산동 921-5351미시행평일+토요일09:0023:0009:0023:0000:0000:00유료301000301000<NA><NA><NA>현금<NA>대구유료주차장053-123-456735.864431128.5942272023-07-10
8150-4-000034대본유료주차장민영노외대구광역시 중구 달성로26길 98대구광역시 중구 수창동 46-1101미시행평일+토요일08:0018:0008:0018:0000:0000:00유료301000<NA><NA><NA><NA><NA>현금1시간 1500원대본유료주차장053-257-073435.875033128.5872952023-07-10
9150-4-000035동산유료주차장민영노외<NA>대구광역시 중구 대신동 1527501미시행평일+토요일07:3018:0007:3018:0000:0000:00유료301000301000<NA><NA><NA>현금<NA>동산유료주차장053-123-456735.866539128.5761692023-07-10
주차장관리번호주차장명주차장구분주차장유형소재지도로명주소소재지지번주소주차구획수급지구분부제시행구분운영요일평일운영시작시각평일운영종료시각토요일운영시작시각토요일운영종료시각공휴일운영시작시각공휴일운영종료시각요금정보주차기본시간주차기본요금추가단위시간추가단위요금1일주차권요금적용시간1일주차권요금월정기권요금결제방법특기사항관리기관명전화번호위도경도데이터기준일자
158150-4-000066평화유료주차장민영노외<NA>대구광역시 중구 대안동 50-8381미시행평일+토요일09:0019:0009:0019:0000:0000:00유료601000601000<NA><NA><NA>현금<NA>평화유료주차장053-123-456735.873147128.591482023-07-10
159150-4-000067도경유료주차장민영노외대구광역시 중구 공평로 26-17대구광역시 중구 삼덕동2가 128-9131미시행평일+토요일00:0023:5900:0023:5900:0000:00유료601000601000<NA><NA><NA>현금<NA>도경유료주차장053-123-456735.866233128.6010332023-07-10
160150-4-000068대구유료주차장민영노외대구광역시 중구 봉산문화길 101대구광역시 중구 봉산동 129-15641미시행평일+토요일07:0023:0007:0023:0000:0000:00유료301000<NA><NA><NA><NA><NA>현금1시간 1900원대구유료주차장053-123-456735.864406128.5963362023-07-10
161150-4-000069동인유료주차장민영노외대구광역시 중구 동덕로 179(동인동1가)대구광역시 중구 동인동1가 288-3151미시행평일+토요일09:0018:0009:0018:0000:0000:00유료301000<NA><NA><NA><NA><NA>현금1시간 2500원동인유료주차장053-422-508535.870806128.604072023-07-10
162150-4-000070대호유료주차장민영노외<NA>대구광역시 중구 서성로2가 51-1201미시행평일+토요일+공휴일08:0022:0008:0022:0008:0022:00유료30100030500<NA>10000100000현금<NA>대호유료주차장053-123-456735.869462128.5868612023-07-10
163150-4-000071창조유료주차장민영노외<NA>대구광역시 중구 남산동 911-14401미시행평일+토요일09:0021:0009:0021:0000:0000:00유료301000<NA><NA><NA><NA><NA>현금1시간 2200원창조유료주차장053-123-456735.864762128.594122023-07-10
164150-4-000072메트로유료주차장민영노외<NA>대구광역시 중구 삼덕동2가 149-39401미시행평일+토요일07:3022:0007:3022:0000:0000:00유료601500601500<NA><NA><NA>현금<NA>메트로유료주차장053-123-456735.865282128.6006672023-07-10
165150-4-000073장인유료주차장민영노외대구광역시 중구 서성로 81(수창동)대구광역시 중구 수창동 101-11421미시행평일+토요일07:3019:0007:3019:0000:0000:00유료30100010300<NA><NA><NA>현금<NA>장인유료주차장053-255-067535.874022128.5874162023-07-10
166150-4-000074예술유료주차장민영노외대구광역시 중구 봉산문화1길 17대구광역시 중구 봉산동 168-6751미시행평일+토요일07:3021:3007:3021:3000:0000:00유료301000<NA><NA><NA><NA><NA>현금1시간 1500원예술유료주차장053-123-456735.863054128.5982672023-07-10
167150-4-000075신우유료주차장민영노외대구광역시 중구 공평로 46(삼덕동2가)대구광역시 중구 삼덕동2가 3-41701미시행평일+토요일00:0023:5900:0023:5900:0000:00유료301000<NA><NA><NA><NA><NA>현금1시간 1900원신우유료주차장053-424-380735.868102128.6000612023-07-10