Overview

Dataset statistics

Number of variables17
Number of observations23
Missing cells42
Missing cells (%)10.7%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory3.3 KiB
Average record size in memory146.7 B

Variable types

Text10
Numeric4
DateTime1
Unsupported1
Categorical1

Dataset

Description견인차량보관소명,소재지도로명주소,소재지지번주소,위도,경도,보관소전화번호,보관소면적,보관가능대수,견인료기본요금,견인료추가요금,보관료,관리기관전화번호,관리기관명,데이터기준일자,제공기관코드,제공기관기관명,작업일시
Author서울특별시
URLhttps://data.seoul.go.kr/dataList/OA-20439/S/1/datasetView.do

Alerts

작업일시 has constant value ""Constant
보관소면적 is highly overall correlated with 보관가능대수High correlation
보관가능대수 is highly overall correlated with 보관소면적High correlation
소재지도로명주소 has 2 (8.7%) missing valuesMissing
보관소면적 has 2 (8.7%) missing valuesMissing
견인료추가요금 has 15 (65.2%) missing valuesMissing
제공기관기관명 has 23 (100.0%) missing valuesMissing
견인료기본요금 has unique valuesUnique
데이터기준일자 has unique valuesUnique
제공기관코드 has unique valuesUnique
제공기관기관명 is an unsupported type, check if it needs cleaning or further analysisUnsupported

Reproduction

Analysis started2024-05-03 23:46:57.438602
Analysis finished2024-05-03 23:47:07.189909
Duration9.75 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

견인차량보관소명
Text

Distinct19
Distinct (%)82.6%
Missing0
Missing (%)0.0%
Memory size316.0 B
2024-05-03T23:47:07.504900image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length15
Median length11
Mean length10.217391
Min length7

Characters and Unicode

Total characters235
Distinct characters42
Distinct categories2 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique15 ?
Unique (%)65.2%

Sample

1st row가양동차량보관소
2nd row용산견인차량보관소
3rd row영등포구견인차량보관소
4th row구로견인차량보관소
5th row관악동작견인차량보관소
ValueCountFrequency (%)
견인차량보관소 8
25.8%
금천구 2
 
6.5%
성북구견인차량보관소 2
 
6.5%
강북구견인차량보관소 2
 
6.5%
홍제견인차량보관소 2
 
6.5%
강남구 1
 
3.2%
가양동차량보관소 1
 
3.2%
은평구 1
 
3.2%
중구 1
 
3.2%
면목견인보관소 1
 
3.2%
Other values (10) 10
32.3%
2024-05-03T23:47:08.588515image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
관 24
10.2%
보 23
9.8%
소 23
9.8%
견 22
9.4%
인 22
9.4%
차 22
9.4%
량 22
9.4%
구 17
 
7.2%
8
 
3.4%
북 4
 
1.7%
Other values (32) 48
20.4%

Most occurring categories

ValueCountFrequency (%)
Other Letter 227
96.6%
Space Separator 8
 
3.4%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
관 24
10.6%
보 23
10.1%
소 23
10.1%
견 22
9.7%
인 22
9.7%
차 22
9.7%
량 22
9.7%
구 17
 
7.5%
북 4
 
1.8%
동 4
 
1.8%
Other values (31) 44
19.4%
Space Separator
ValueCountFrequency (%)
8
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 227
96.6%
Common 8
 
3.4%

Most frequent character per script

Hangul
ValueCountFrequency (%)
관 24
10.6%
보 23
10.1%
소 23
10.1%
견 22
9.7%
인 22
9.7%
차 22
9.7%
량 22
9.7%
구 17
 
7.5%
북 4
 
1.8%
동 4
 
1.8%
Other values (31) 44
19.4%
Common
ValueCountFrequency (%)
8
100.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 227
96.6%
ASCII 8
 
3.4%

Most frequent character per block

Hangul
ValueCountFrequency (%)
관 24
10.6%
보 23
10.1%
소 23
10.1%
견 22
9.7%
인 22
9.7%
차 22
9.7%
량 22
9.7%
구 17
 
7.5%
북 4
 
1.8%
동 4
 
1.8%
Other values (31) 44
19.4%
ASCII
ValueCountFrequency (%)
8
100.0%

소재지도로명주소
Text

MISSING 

Distinct18
Distinct (%)85.7%
Missing2
Missing (%)8.7%
Memory size316.0 B
2024-05-03T23:47:09.229787image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length26
Median length23
Mean length20.190476
Min length15

Characters and Unicode

Total characters424
Distinct characters87
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

Unique15 ?
Unique (%)71.4%

Sample

1st row서울특별시 강서구 양천로59길 16-9
2nd row서울특별시 용산구 새창로 170-4(한강로3가)
3rd row서울특별시 영등포구 경인로112길 28
4th row서울특별시 구로구 서해안로 2395
5th row서울특별시 관악구 신사로 7
ValueCountFrequency (%)
서울특별시 21
24.1%
678 2
 
2.3%
금천구 2
 
2.3%
227 2
 
2.3%
홍제내길 2
 
2.3%
서대문구 2
 
2.3%
성북구 2
 
2.3%
삼양로 2
 
2.3%
강북구 2
 
2.3%
169-34 2
 
2.3%
Other values (47) 48
55.2%
2024-05-03T23:47:10.432365image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
66
 
15.6%
서 26
 
6.1%
구 22
 
5.2%
별 21
 
5.0%
시 21
 
5.0%
특 21
 
5.0%
울 21
 
5.0%
로 21
 
5.0%
2 12
 
2.8%
1 10
 
2.4%
Other values (77) 183
43.2%

Most occurring categories

ValueCountFrequency (%)
Other Letter 276
65.1%
Decimal Number 73
 
17.2%
Space Separator 66
 
15.6%
Dash Punctuation 5
 
1.2%
Close Punctuation 2
 
0.5%
Open Punctuation 2
 
0.5%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
서 26
 
9.4%
구 22
 
8.0%
별 21
 
7.6%
시 21
 
7.6%
특 21
 
7.6%
울 21
 
7.6%
로 21
 
7.6%
천 7
 
2.5%
길 7
 
2.5%
동 6
 
2.2%
Other values (63) 103
37.3%
Decimal Number
ValueCountFrequency (%)
2 12
16.4%
1 10
13.7%
7 9
12.3%
4 9
12.3%
9 9
12.3%
6 6
8.2%
3 6
8.2%
8 5
6.8%
0 4
 
5.5%
5 3
 
4.1%
Space Separator
ValueCountFrequency (%)
66
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 5
100.0%
Close Punctuation
ValueCountFrequency (%)
) 2
100.0%
Open Punctuation
ValueCountFrequency (%)
( 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 276
65.1%
Common 148
34.9%

Most frequent character per script

Hangul
ValueCountFrequency (%)
서 26
 
9.4%
구 22
 
8.0%
별 21
 
7.6%
시 21
 
7.6%
특 21
 
7.6%
울 21
 
7.6%
로 21
 
7.6%
천 7
 
2.5%
길 7
 
2.5%
동 6
 
2.2%
Other values (63) 103
37.3%
Common
ValueCountFrequency (%)
66
44.6%
2 12
 
8.1%
1 10
 
6.8%
7 9
 
6.1%
4 9
 
6.1%
9 9
 
6.1%
6 6
 
4.1%
3 6
 
4.1%
- 5
 
3.4%
8 5
 
3.4%
Other values (4) 11
 
7.4%

Most occurring blocks

ValueCountFrequency (%)
Hangul 276
65.1%
ASCII 148
34.9%

Most frequent character per block

ASCII
ValueCountFrequency (%)
66
44.6%
2 12
 
8.1%
1 10
 
6.8%
7 9
 
6.1%
4 9
 
6.1%
9 9
 
6.1%
6 6
 
4.1%
3 6
 
4.1%
- 5
 
3.4%
8 5
 
3.4%
Other values (4) 11
 
7.4%
Hangul
ValueCountFrequency (%)
서 26
 
9.4%
구 22
 
8.0%
별 21
 
7.6%
시 21
 
7.6%
특 21
 
7.6%
울 21
 
7.6%
로 21
 
7.6%
천 7
 
2.5%
길 7
 
2.5%
동 6
 
2.2%
Other values (63) 103
37.3%

소재지지번주소
Text

Distinct21
Distinct (%)91.3%
Missing0
Missing (%)0.0%
Memory size316.0 B
2024-05-03T23:47:11.287122image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length29
Median length21
Mean length19.695652
Min length16

Characters and Unicode

Total characters453
Distinct characters78
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

Unique19 ?
Unique (%)82.6%

Sample

1st row서울특별시 강서구 가양동 451-7
2nd row서울특별시 용산구 한강로3가 23-1
3rd row서울특별시 영등포구 영등포동1가 3-5
4th row서울특별시 구로구 개봉동 247-23
5th row서울특별시 관악구 신림동 1677-4
ValueCountFrequency (%)
서울특별시 23
25.0%
294-84 2
 
2.2%
우이동 2
 
2.2%
강북구 2
 
2.2%
성북구 2
 
2.2%
금천구 2
 
2.2%
홍제동 2
 
2.2%
서대문구 2
 
2.2%
614-34 2
 
2.2%
가산동 2
 
2.2%
Other values (51) 51
55.4%
2024-05-03T23:47:12.635274image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
69
 
15.2%
서 27
 
6.0%
구 24
 
5.3%
동 24
 
5.3%
시 23
 
5.1%
울 23
 
5.1%
별 23
 
5.1%
특 23
 
5.1%
- 21
 
4.6%
1 20
 
4.4%
Other values (68) 176
38.9%

Most occurring categories

ValueCountFrequency (%)
Other Letter 266
58.7%
Decimal Number 95
 
21.0%
Space Separator 69
 
15.2%
Dash Punctuation 21
 
4.6%
Open Punctuation 1
 
0.2%
Close Punctuation 1
 
0.2%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
서 27
 
10.2%
구 24
 
9.0%
동 24
 
9.0%
시 23
 
8.6%
울 23
 
8.6%
별 23
 
8.6%
특 23
 
8.6%
강 7
 
2.6%
가 6
 
2.3%
북 4
 
1.5%
Other values (54) 82
30.8%
Decimal Number
ValueCountFrequency (%)
1 20
21.1%
4 12
12.6%
2 12
12.6%
6 10
10.5%
3 9
9.5%
8 8
 
8.4%
7 8
 
8.4%
5 7
 
7.4%
9 7
 
7.4%
0 2
 
2.1%
Space Separator
ValueCountFrequency (%)
69
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 21
100.0%
Open Punctuation
ValueCountFrequency (%)
( 1
100.0%
Close Punctuation
ValueCountFrequency (%)
) 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 266
58.7%
Common 187
41.3%

Most frequent character per script

Hangul
ValueCountFrequency (%)
서 27
 
10.2%
구 24
 
9.0%
동 24
 
9.0%
시 23
 
8.6%
울 23
 
8.6%
별 23
 
8.6%
특 23
 
8.6%
강 7
 
2.6%
가 6
 
2.3%
북 4
 
1.5%
Other values (54) 82
30.8%
Common
ValueCountFrequency (%)
69
36.9%
- 21
 
11.2%
1 20
 
10.7%
4 12
 
6.4%
2 12
 
6.4%
6 10
 
5.3%
3 9
 
4.8%
8 8
 
4.3%
7 8
 
4.3%
5 7
 
3.7%
Other values (4) 11
 
5.9%

Most occurring blocks

ValueCountFrequency (%)
Hangul 266
58.7%
ASCII 187
41.3%

Most frequent character per block

ASCII
ValueCountFrequency (%)
69
36.9%
- 21
 
11.2%
1 20
 
10.7%
4 12
 
6.4%
2 12
 
6.4%
6 10
 
5.3%
3 9
 
4.8%
8 8
 
4.3%
7 8
 
4.3%
5 7
 
3.7%
Other values (4) 11
 
5.9%
Hangul
ValueCountFrequency (%)
서 27
 
10.2%
구 24
 
9.0%
동 24
 
9.0%
시 23
 
8.6%
울 23
 
8.6%
별 23
 
8.6%
특 23
 
8.6%
강 7
 
2.6%
가 6
 
2.3%
북 4
 
1.5%
Other values (54) 82
30.8%

위도
Real number (ℝ)

Distinct21
Distinct (%)91.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean37.550037
Minimum37.445883
Maximum37.663371
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size339.0 B
2024-05-03T23:47:13.137137image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum37.445883
5-th percentile37.477818
Q137.500269
median37.555479
Q337.590834
95-th percentile37.657925
Maximum37.663371
Range0.21748743
Interquartile range (IQR)0.090564469

Descriptive statistics

Standard deviation0.058875292
Coefficient of variation (CV)0.0015679157
Kurtosis-0.54597012
Mean37.550037
Median Absolute Deviation (MAD)0.0496696
Skewness0.22731212
Sum863.65085
Variance0.0034663
MonotonicityNot monotonic
2024-05-03T23:47:13.502558image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=21)
ValueCountFrequency (%)
37.5908337 2
 
8.7%
37.48330365 2
 
8.7%
37.56020334 1
 
4.3%
37.5052374 1
 
4.3%
37.6089213 1
 
4.3%
37.47720897 1
 
4.3%
37.6051491 1
 
4.3%
37.5554795 1
 
4.3%
37.5792085 1
 
4.3%
37.66336998 1
 
4.3%
Other values (11) 11
47.8%
ValueCountFrequency (%)
37.44588309 1
4.3%
37.47720897 1
4.3%
37.48330365 2
8.7%
37.4846975978 1
4.3%
37.4953010628 1
4.3%
37.5052374 1
4.3%
37.517462 1
4.3%
37.52813216 1
4.3%
37.5324193031 1
4.3%
37.54554956 1
4.3%
ValueCountFrequency (%)
37.66337052 1
4.3%
37.66336998 1
4.3%
37.6089213 1
4.3%
37.6059501 1
4.3%
37.6051491 1
4.3%
37.5908337 2
8.7%
37.5792085 1
4.3%
37.56598207 1
4.3%
37.5630545 1
4.3%
37.56020334 1
4.3%

경도
Real number (ℝ)

Distinct22
Distinct (%)95.7%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean126.97662
Minimum126.85022
Maximum127.17228
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size339.0 B
2024-05-03T23:47:13.969216image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum126.85022
5-th percentile126.86134
Q1126.90763
median126.96326
Q3127.05336
95-th percentile127.11466
Maximum127.17228
Range0.3220533
Interquartile range (IQR)0.14572319

Descriptive statistics

Standard deviation0.090515268
Coefficient of variation (CV)0.00071284991
Kurtosis-0.78688337
Mean126.97662
Median Absolute Deviation (MAD)0.086738436
Skewness0.41197735
Sum2920.4621
Variance0.0081930138
MonotonicityNot monotonic
2024-05-03T23:47:14.490645image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=22)
ValueCountFrequency (%)
126.9410088 2
 
8.7%
126.8597014 1
 
4.3%
127.0681833 1
 
4.3%
127.0505934 1
 
4.3%
127.1183734 1
 
4.3%
126.9230408 1
 
4.3%
126.9648157 1
 
4.3%
127.0812073 1
 
4.3%
127.0126665 1
 
4.3%
127.0568139 1
 
4.3%
Other values (12) 12
52.2%
ValueCountFrequency (%)
126.850224601 1
4.3%
126.8597014 1
4.3%
126.8760467 1
4.3%
126.8760816 1
4.3%
126.8765231 1
4.3%
126.9040672258 1
4.3%
126.9111988 1
4.3%
126.915928 1
4.3%
126.9230408 1
4.3%
126.9410088 2
8.7%
ValueCountFrequency (%)
127.1722779 1
4.3%
127.1183734 1
4.3%
127.0812073 1
4.3%
127.0681833 1
4.3%
127.0568139 1
4.3%
127.056119 1
4.3%
127.0505934 1
4.3%
127.0303396 1
4.3%
127.0126665 1
4.3%
127.0126653 1
4.3%

보관소전화번호
Text

Distinct19
Distinct (%)82.6%
Missing0
Missing (%)0.0%
Memory size316.0 B
2024-05-03T23:47:15.084277image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length12
Median length11
Mean length11.391304
Min length11

Characters and Unicode

Total characters262
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

Unique15 ?
Unique (%)65.2%

Sample

1st row02-3661-1936
2nd row02-707-3173
3rd row02-2650-1485
4th row02-2066-1325
5th row02-855-8611
ValueCountFrequency (%)
02-854-5273 2
 
8.7%
02-944-3027 2
 
8.7%
02-360-8542 2
 
8.7%
02-6925-2004 2
 
8.7%
02-558-7230 1
 
4.3%
02-3661-1936 1
 
4.3%
02-350-5180 1
 
4.3%
02-2280-8374 1
 
4.3%
02-492-8185 1
 
4.3%
02-575-5022 1
 
4.3%
Other values (9) 9
39.1%
2024-05-03T23:47:16.294960image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
2 46
17.6%
- 46
17.6%
0 42
16.0%
5 24
9.2%
3 22
8.4%
4 20
7.6%
7 15
 
5.7%
8 14
 
5.3%
6 13
 
5.0%
1 12
 
4.6%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 216
82.4%
Dash Punctuation 46
 
17.6%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
2 46
21.3%
0 42
19.4%
5 24
11.1%
3 22
10.2%
4 20
9.3%
7 15
 
6.9%
8 14
 
6.5%
6 13
 
6.0%
1 12
 
5.6%
9 8
 
3.7%
Dash Punctuation
ValueCountFrequency (%)
- 46
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 262
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
2 46
17.6%
- 46
17.6%
0 42
16.0%
5 24
9.2%
3 22
8.4%
4 20
7.6%
7 15
 
5.7%
8 14
 
5.3%
6 13
 
5.0%
1 12
 
4.6%

Most occurring blocks

ValueCountFrequency (%)
ASCII 262
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
2 46
17.6%
- 46
17.6%
0 42
16.0%
5 24
9.2%
3 22
8.4%
4 20
7.6%
7 15
 
5.7%
8 14
 
5.3%
6 13
 
5.0%
1 12
 
4.6%

보관소면적
Real number (ℝ)

HIGH CORRELATION  MISSING 

Distinct19
Distinct (%)90.5%
Missing2
Missing (%)8.7%
Infinite0
Infinite (%)0.0%
Mean2364.2619
Minimum101
Maximum7310
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size339.0 B
2024-05-03T23:47:16.904660image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum101
5-th percentile852
Q1962.5
median1715
Q32700
95-th percentile6099
Maximum7310
Range7209
Interquartile range (IQR)1737.5

Descriptive statistics

Standard deviation1897.1338
Coefficient of variation (CV)0.80242115
Kurtosis1.4438612
Mean2364.2619
Median Absolute Deviation (MAD)825
Skewness1.406761
Sum49649.5
Variance3599116.5
MonotonicityNot monotonic
2024-05-03T23:47:17.430927image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=19)
ValueCountFrequency (%)
2514.0 2
 
8.7%
852.0 2
 
8.7%
890.0 1
 
4.3%
6099.0 1
 
4.3%
1083.0 1
 
4.3%
3777.0 1
 
4.3%
1609.0 1
 
4.3%
962.5 1
 
4.3%
5497.0 1
 
4.3%
2700.0 1
 
4.3%
Other values (9) 9
39.1%
(Missing) 2
 
8.7%
ValueCountFrequency (%)
101.0 1
4.3%
852.0 2
8.7%
890.0 1
4.3%
924.0 1
4.3%
962.5 1
4.3%
1006.0 1
4.3%
1083.0 1
4.3%
1609.0 1
4.3%
1707.0 1
4.3%
1715.0 1
4.3%
ValueCountFrequency (%)
7310.0 1
4.3%
6099.0 1
4.3%
5497.0 1
4.3%
3777.0 1
4.3%
3032.0 1
4.3%
2700.0 1
4.3%
2650.0 1
4.3%
2514.0 2
8.7%
1855.0 1
4.3%
1715.0 1
4.3%

보관가능대수
Real number (ℝ)

HIGH CORRELATION 

Distinct20
Distinct (%)87.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean57.782609
Minimum16
Maximum200
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size339.0 B
2024-05-03T23:47:17.927153image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum16
5-th percentile17.4
Q135.5
median48
Q368.5
95-th percentile118.9
Maximum200
Range184
Interquartile range (IQR)33

Descriptive statistics

Standard deviation39.685075
Coefficient of variation (CV)0.68679963
Kurtosis7.0814411
Mean57.782609
Median Absolute Deviation (MAD)17
Skewness2.3108035
Sum1329
Variance1574.9051
MonotonicityNot monotonic
2024-05-03T23:47:18.551680image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=20)
ValueCountFrequency (%)
39 3
 
13.0%
65 2
 
8.7%
123 1
 
4.3%
29 1
 
4.3%
76 1
 
4.3%
17 1
 
4.3%
32 1
 
4.3%
64 1
 
4.3%
60 1
 
4.3%
55 1
 
4.3%
Other values (10) 10
43.5%
ValueCountFrequency (%)
16 1
 
4.3%
17 1
 
4.3%
21 1
 
4.3%
29 1
 
4.3%
31 1
 
4.3%
32 1
 
4.3%
39 3
13.0%
40 1
 
4.3%
43 1
 
4.3%
48 1
 
4.3%
ValueCountFrequency (%)
200 1
4.3%
123 1
4.3%
82 1
4.3%
76 1
4.3%
73 1
4.3%
72 1
4.3%
65 2
8.7%
64 1
4.3%
60 1
4.3%
55 1
4.3%

견인료기본요금
Text

UNIQUE 

Distinct23
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size316.0 B
2024-05-03T23:47:19.285454image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length223
Median length120
Mean length109.69565
Min length5

Characters and Unicode

Total characters2523
Distinct characters61
Distinct categories7 ?
Distinct scripts2 ?
Distinct blocks4 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique23 ?
Unique (%)100.0%

Sample

1st row승용자동차(경형 40000원+소형 45000원+중형 50000원+대형 60000원)+승합자동차(경형 40000원+소형 60000원+중형 80000원+대형 140000원)+화물 및 특수자동차(2.5톤 미만 40000원+2.5톤 이상 ~ 6.5톤 미만 60000원+6.5톤 이상 ~ 10톤 미만 80000원+10톤 이상 140000원) * 종전 무게중심(2.5톤 기준 40000원) → 배기량별 차등적용
2nd row승용(경형 40000원+소형 45000원+중형 50000원+대형 60000원)+승합(경형 40000원+소형 60000원+중형 80000원+대형 140000원)+화물 및 특수(2.5톤미만 40000원+2.5톤이상 6.5톤미만 60000원+6.5톤이상 10톤미만 80000원+10톤이상 140000원)
3rd row4만원~14만원
4th row경차 40000원+소형 45000원+중형 50000원+대형 60000원
5th row승용자동차((경형 40000원+소형 45000원+중형 50000원+대형 60000원)+승합자동차(경형 40000원+소형 60000원+중형 80000원+대형 140000원+이륜자동차 40000원)+화물자동차?특수자동차(2.5톤 미만 40000원+2.5톤 이상 6.5톤 미만 60000원+6.5톤 이상 10톤 미만 80000원+10톤 이상 140000원)
ValueCountFrequency (%)
40000원+소형 16
 
7.0%
15
 
6.6%
미만 13
 
5.7%
이상 12
 
5.3%
45000원+중형 9
 
4.0%
50000원+대형 8
 
3.5%
60000원+중형 7
 
3.1%
80000원+대형 7
 
3.1%
140000원 7
 
3.1%
경형 5
 
2.2%
Other values (87) 128
56.4%
2024-05-03T23:47:20.494078image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 704
27.9%
205
 
8.1%
원 172
 
6.8%
형 122
 
4.8%
+ 121
 
4.8%
4 97
 
3.8%
5 79
 
3.1%
톤 68
 
2.7%
6 62
 
2.5%
1 52
 
2.1%
Other values (51) 841
33.3%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 1040
41.2%
Other Letter 961
38.1%
Space Separator 205
 
8.1%
Math Symbol 129
 
5.1%
Other Punctuation 123
 
4.9%
Open Punctuation 33
 
1.3%
Close Punctuation 32
 
1.3%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
원 172
17.9%
형 122
 
12.7%
톤 68
 
7.1%
승 50
 
5.2%
이 41
 
4.3%
차 41
 
4.3%
만 39
 
4.1%
미 37
 
3.9%
상 31
 
3.2%
소 31
 
3.2%
Other values (32) 329
34.2%
Decimal Number
ValueCountFrequency (%)
0 704
67.7%
4 97
 
9.3%
5 79
 
7.6%
6 62
 
6.0%
1 52
 
5.0%
2 23
 
2.2%
8 23
 
2.2%
Other Punctuation
ValueCountFrequency (%)
. 44
35.8%
: 35
28.5%
, 31
25.2%
/ 9
 
7.3%
? 3
 
2.4%
* 1
 
0.8%
Math Symbol
ValueCountFrequency (%)
+ 121
93.8%
~ 7
 
5.4%
→ 1
 
0.8%
Space Separator
ValueCountFrequency (%)
205
100.0%
Open Punctuation
ValueCountFrequency (%)
( 33
100.0%
Close Punctuation
ValueCountFrequency (%)
) 32
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 1562
61.9%
Hangul 961
38.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
원 172
17.9%
형 122
 
12.7%
톤 68
 
7.1%
승 50
 
5.2%
이 41
 
4.3%
차 41
 
4.3%
만 39
 
4.1%
미 37
 
3.9%
상 31
 
3.2%
소 31
 
3.2%
Other values (32) 329
34.2%
Common
ValueCountFrequency (%)
0 704
45.1%
205
 
13.1%
+ 121
 
7.7%
4 97
 
6.2%
5 79
 
5.1%
6 62
 
4.0%
1 52
 
3.3%
. 44
 
2.8%
: 35
 
2.2%
( 33
 
2.1%
Other values (9) 130
 
8.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1561
61.9%
Hangul 953
37.8%
Compat Jamo 8
 
0.3%
Arrows 1
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 704
45.1%
205
 
13.1%
+ 121
 
7.8%
4 97
 
6.2%
5 79
 
5.1%
6 62
 
4.0%
1 52
 
3.3%
. 44
 
2.8%
: 35
 
2.2%
( 33
 
2.1%
Other values (8) 129
 
8.3%
Hangul
ValueCountFrequency (%)
원 172
18.0%
형 122
 
12.8%
톤 68
 
7.1%
승 50
 
5.2%
이 41
 
4.3%
차 41
 
4.3%
만 39
 
4.1%
미 37
 
3.9%
상 31
 
3.3%
소 31
 
3.3%
Other values (31) 321
33.7%
Compat Jamo
ValueCountFrequency (%)
ㆍ 8
100.0%
Arrows
ValueCountFrequency (%)
→ 1
100.0%

견인료추가요금
Text

MISSING 

Distinct4
Distinct (%)50.0%
Missing15
Missing (%)65.2%
Memory size316.0 B
2024-05-03T23:47:21.089357image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length39
Median length2
Mean length9.125
Min length2

Characters and Unicode

Total characters73
Distinct characters43
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

Unique3 ?
Unique (%)37.5%

Sample

1st row없음
2nd row없음
3rd row없음
4th row해당 없음
5th row없음
ValueCountFrequency (%)
없음 6
35.3%
해당 1
 
5.9%
승용?승합자동차의 1
 
5.9%
규모별 1
 
5.9%
세부기준은 1
 
5.9%
자동차관리법 1
 
5.9%
시행규칙 1
 
5.9%
별표1에 1
 
5.9%
따름 1
 
5.9%
1회보관료 1
 
5.9%
Other values (2) 2
 
11.8%
2024-05-03T23:47:21.850686image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
9
 
12.3%
없 6
 
8.2%
음 6
 
8.2%
0 5
 
6.8%
동 2
 
2.7%
1 2
 
2.7%
별 2
 
2.7%
규 2
 
2.7%
차 2
 
2.7%
관 2
 
2.7%
Other values (33) 35
47.9%

Most occurring categories

ValueCountFrequency (%)
Other Letter 54
74.0%
Space Separator 9
 
12.3%
Decimal Number 8
 
11.0%
Other Punctuation 2
 
2.7%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
없 6
 
11.1%
음 6
 
11.1%
동 2
 
3.7%
별 2
 
3.7%
규 2
 
3.7%
차 2
 
3.7%
관 2
 
3.7%
자 2
 
3.7%
승 2
 
3.7%
료 1
 
1.9%
Other values (27) 27
50.0%
Decimal Number
ValueCountFrequency (%)
0 5
62.5%
1 2
 
25.0%
5 1
 
12.5%
Other Punctuation
ValueCountFrequency (%)
, 1
50.0%
? 1
50.0%
Space Separator
ValueCountFrequency (%)
9
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 54
74.0%
Common 19
 
26.0%

Most frequent character per script

Hangul
ValueCountFrequency (%)
없 6
 
11.1%
음 6
 
11.1%
동 2
 
3.7%
별 2
 
3.7%
규 2
 
3.7%
차 2
 
3.7%
관 2
 
3.7%
자 2
 
3.7%
승 2
 
3.7%
료 1
 
1.9%
Other values (27) 27
50.0%
Common
ValueCountFrequency (%)
9
47.4%
0 5
26.3%
1 2
 
10.5%
5 1
 
5.3%
, 1
 
5.3%
? 1
 
5.3%

Most occurring blocks

ValueCountFrequency (%)
Hangul 54
74.0%
ASCII 19
 
26.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
9
47.4%
0 5
26.3%
1 2
 
10.5%
5 1
 
5.3%
, 1
 
5.3%
? 1
 
5.3%
Hangul
ValueCountFrequency (%)
없 6
 
11.1%
음 6
 
11.1%
동 2
 
3.7%
별 2
 
3.7%
규 2
 
3.7%
차 2
 
3.7%
관 2
 
3.7%
자 2
 
3.7%
승 2
 
3.7%
료 1
 
1.9%
Other values (27) 27
50.0%

보관료
Text

Distinct22
Distinct (%)95.7%
Missing0
Missing (%)0.0%
Memory size316.0 B
2024-05-03T23:47:22.354309image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length107
Median length64
Mean length52.130435
Min length8

Characters and Unicode

Total characters1199
Distinct characters62
Distinct categories7 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique21 ?
Unique (%)91.3%

Sample

1st row6.5톤 미만 30분당 700원+6.5톤 이상~10톤 미만 30분당 1200원 (단 1회 보관료는 50만 원 한도)
2nd row30분당 700원+승합자동차 중 중과 대형 1200원+1회 보관료 500000원
3rd row30분당 700원~1200원
4th row30분당 700원(승용+승합+ 이륜차, 화물+ 특수자동차 6.5톤 미만)/ 30분당 1200원(승합(중형+대형)+화물+ 특수자동차 6.5톤이상)/ 1회 보관료는 50만원 한도료는 50만원 한도
5th row기본 30분당 700원(승합자동차중 중형과 대형은 1200원)+화물자동차?특수자동차 6.5톤 이상 30분당 1200원(1회 보관료는 50만원 한도로 함)
ValueCountFrequency (%)
30분당 26
 
12.6%
1200원 9
 
4.3%
보관료는 9
 
4.3%
1회 8
 
3.9%
단 6
 
2.9%
50만원 6
 
2.9%
한도 6
 
2.9%
기본 6
 
2.9%
대형 5
 
2.4%
6.5톤 5
 
2.4%
Other values (68) 121
58.5%
2024-05-03T23:47:23.104271image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
185
 
15.4%
0 163
 
13.6%
원 68
 
5.7%
1 37
 
3.1%
분 34
 
2.8%
3 33
 
2.8%
5 32
 
2.7%
7 31
 
2.6%
형 31
 
2.6%
+ 30
 
2.5%
Other values (52) 555
46.3%

Most occurring categories

ValueCountFrequency (%)
Other Letter 551
46.0%
Decimal Number 334
27.9%
Space Separator 185
 
15.4%
Other Punctuation 43
 
3.6%
Math Symbol 32
 
2.7%
Close Punctuation 27
 
2.3%
Open Punctuation 27
 
2.3%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
원 68
 
12.3%
분 34
 
6.2%
형 31
 
5.6%
당 29
 
5.3%
중 22
 
4.0%
승 21
 
3.8%
만 19
 
3.4%
합 17
 
3.1%
톤 17
 
3.1%
한 16
 
2.9%
Other values (34) 277
50.3%
Decimal Number
ValueCountFrequency (%)
0 163
48.8%
1 37
 
11.1%
3 33
 
9.9%
5 32
 
9.6%
7 31
 
9.3%
2 22
 
6.6%
6 16
 
4.8%
Other Punctuation
ValueCountFrequency (%)
. 21
48.8%
, 8
 
18.6%
? 7
 
16.3%
* 3
 
7.0%
: 2
 
4.7%
/ 2
 
4.7%
Math Symbol
ValueCountFrequency (%)
+ 30
93.8%
~ 2
 
6.2%
Space Separator
ValueCountFrequency (%)
185
100.0%
Close Punctuation
ValueCountFrequency (%)
) 27
100.0%
Open Punctuation
ValueCountFrequency (%)
( 27
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 648
54.0%
Hangul 551
46.0%

Most frequent character per script

Hangul
ValueCountFrequency (%)
원 68
 
12.3%
분 34
 
6.2%
형 31
 
5.6%
당 29
 
5.3%
중 22
 
4.0%
승 21
 
3.8%
만 19
 
3.4%
합 17
 
3.1%
톤 17
 
3.1%
한 16
 
2.9%
Other values (34) 277
50.3%
Common
ValueCountFrequency (%)
185
28.5%
0 163
25.2%
1 37
 
5.7%
3 33
 
5.1%
5 32
 
4.9%
7 31
 
4.8%
+ 30
 
4.6%
) 27
 
4.2%
( 27
 
4.2%
2 22
 
3.4%
Other values (8) 61
 
9.4%

Most occurring blocks

ValueCountFrequency (%)
ASCII 648
54.0%
Hangul 551
46.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
185
28.5%
0 163
25.2%
1 37
 
5.7%
3 33
 
5.1%
5 32
 
4.9%
7 31
 
4.8%
+ 30
 
4.6%
) 27
 
4.2%
( 27
 
4.2%
2 22
 
3.4%
Other values (8) 61
 
9.4%
Hangul
ValueCountFrequency (%)
원 68
 
12.3%
분 34
 
6.2%
형 31
 
5.6%
당 29
 
5.3%
중 22
 
4.0%
승 21
 
3.8%
만 19
 
3.4%
합 17
 
3.1%
톤 17
 
3.1%
한 16
 
2.9%
Other values (34) 277
50.3%

관리기관전화번호
Text

Distinct22
Distinct (%)95.7%
Missing0
Missing (%)0.0%
Memory size316.0 B
2024-05-03T23:47:23.525676image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length13
Median length11
Mean length11.347826
Min length9

Characters and Unicode

Total characters261
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

Unique21 ?
Unique (%)91.3%

Sample

1st row02-3661-1936
2nd row070-4906-2525
3rd row02-2650-1400
4th row02-860-3191
5th row02-832-2445
ValueCountFrequency (%)
02-360-8542 2
 
8.7%
02-3661-1936 1
 
4.3%
070-4906-2525 1
 
4.3%
02-214-3204 1
 
4.3%
02-350-5181 1
 
4.3%
02-3396-6254 1
 
4.3%
02-2094-2634 1
 
4.3%
02-944-3026 1
 
4.3%
02-2155-7250 1
 
4.3%
02-809-0061 1
 
4.3%
Other values (12) 12
52.2%
2024-05-03T23:47:24.427044image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 49
18.8%
2 48
18.4%
- 45
17.2%
4 25
9.6%
3 19
 
7.3%
5 18
 
6.9%
6 17
 
6.5%
1 15
 
5.7%
9 11
 
4.2%
8 8
 
3.1%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 216
82.8%
Dash Punctuation 45
 
17.2%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 49
22.7%
2 48
22.2%
4 25
11.6%
3 19
 
8.8%
5 18
 
8.3%
6 17
 
7.9%
1 15
 
6.9%
9 11
 
5.1%
8 8
 
3.7%
7 6
 
2.8%
Dash Punctuation
ValueCountFrequency (%)
- 45
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 261
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 49
18.8%
2 48
18.4%
- 45
17.2%
4 25
9.6%
3 19
 
7.3%
5 18
 
6.9%
6 17
 
6.5%
1 15
 
5.7%
9 11
 
4.2%
8 8
 
3.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 261
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 49
18.8%
2 48
18.4%
- 45
17.2%
4 25
9.6%
3 19
 
7.3%
5 18
 
6.9%
6 17
 
6.5%
1 15
 
5.7%
9 11
 
4.2%
8 8
 
3.1%

관리기관명
Text

Distinct21
Distinct (%)91.3%
Missing0
Missing (%)0.0%
Memory size316.0 B
2024-05-03T23:47:24.853631image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length22
Median length15
Mean length12.695652
Min length4

Characters and Unicode

Total characters292
Distinct characters51
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

Unique19 ?
Unique (%)82.6%

Sample

1st row서울특별시 강서구시설관리공단
2nd row서울특별시 용산구 시설관리공단
3rd row영등포구시설관리공단
4th row서울특별시 구로구청 주차관리과
5th row서울특별시 동작구시설관리공단
ValueCountFrequency (%)
서울특별시 15
34.9%
주차관리과 3
 
7.0%
금천구시설관리공단 2
 
4.7%
서대문구청 2
 
4.7%
강북구도시관리공단 2
 
4.7%
강서구시설관리공단 1
 
2.3%
송파구청 1
 
2.3%
은평구시설관리공단 1
 
2.3%
중구청 1
 
2.3%
중랑구청 1
 
2.3%
Other values (14) 14
32.6%
2024-05-03T23:47:25.695105image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
시 30
 
10.3%
구 24
 
8.2%
서 20
 
6.8%
20
 
6.8%
관 17
 
5.8%
리 17
 
5.8%
특 16
 
5.5%
별 16
 
5.5%
울 16
 
5.5%
공 14
 
4.8%
Other values (41) 102
34.9%

Most occurring categories

ValueCountFrequency (%)
Other Letter 268
91.8%
Space Separator 20
 
6.8%
Close Punctuation 2
 
0.7%
Open Punctuation 2
 
0.7%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
시 30
 
11.2%
구 24
 
9.0%
서 20
 
7.5%
관 17
 
6.3%
리 17
 
6.3%
특 16
 
6.0%
별 16
 
6.0%
울 16
 
6.0%
공 14
 
5.2%
단 14
 
5.2%
Other values (38) 84
31.3%
Space Separator
ValueCountFrequency (%)
20
100.0%
Close Punctuation
ValueCountFrequency (%)
) 2
100.0%
Open Punctuation
ValueCountFrequency (%)
( 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 268
91.8%
Common 24
 
8.2%

Most frequent character per script

Hangul
ValueCountFrequency (%)
시 30
 
11.2%
구 24
 
9.0%
서 20
 
7.5%
관 17
 
6.3%
리 17
 
6.3%
특 16
 
6.0%
별 16
 
6.0%
울 16
 
6.0%
공 14
 
5.2%
단 14
 
5.2%
Other values (38) 84
31.3%
Common
ValueCountFrequency (%)
20
83.3%
) 2
 
8.3%
( 2
 
8.3%

Most occurring blocks

ValueCountFrequency (%)
Hangul 268
91.8%
ASCII 24
 
8.2%

Most frequent character per block

Hangul
ValueCountFrequency (%)
시 30
 
11.2%
구 24
 
9.0%
서 20
 
7.5%
관 17
 
6.3%
리 17
 
6.3%
특 16
 
6.0%
별 16
 
6.0%
울 16
 
6.0%
공 14
 
5.2%
단 14
 
5.2%
Other values (38) 84
31.3%
ASCII
ValueCountFrequency (%)
20
83.3%
) 2
 
8.3%
( 2
 
8.3%

데이터기준일자
Date

UNIQUE 

Distinct23
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size316.0 B
Minimum2017-05-18 00:00:00
Maximum2024-02-22 00:00:00
2024-05-03T23:47:25.984021image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-03T23:47:26.336556image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=23)

제공기관코드
Text

UNIQUE 

Distinct23
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size316.0 B
2024-05-03T23:47:26.734307image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length7
Median length7
Mean length7
Min length7

Characters and Unicode

Total characters161
Distinct characters11
Distinct categories2 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique23 ?
Unique (%)100.0%

Sample

1st row3150000
2nd row3020000
3rd row3180000
4th row3160000
5th row3200000
ValueCountFrequency (%)
3150000 1
 
4.3%
3220000 1
 
4.3%
3230000 1
 
4.3%
3110000 1
 
4.3%
3000000 1
 
4.3%
3120000 1
 
4.3%
3010000 1
 
4.3%
3060000 1
 
4.3%
3080000 1
 
4.3%
3210000 1
 
4.3%
Other values (13) 13
56.5%
2024-05-03T23:47:27.426850image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 89
55.3%
3 23
 
14.3%
1 15
 
9.3%
2 11
 
6.8%
5 7
 
4.3%
8 6
 
3.7%
B 3
 
1.9%
6 2
 
1.2%
4 2
 
1.2%
7 2
 
1.2%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 158
98.1%
Uppercase Letter 3
 
1.9%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 89
56.3%
3 23
 
14.6%
1 15
 
9.5%
2 11
 
7.0%
5 7
 
4.4%
8 6
 
3.8%
6 2
 
1.3%
4 2
 
1.3%
7 2
 
1.3%
9 1
 
0.6%
Uppercase Letter
ValueCountFrequency (%)
B 3
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 158
98.1%
Latin 3
 
1.9%

Most frequent character per script

Common
ValueCountFrequency (%)
0 89
56.3%
3 23
 
14.6%
1 15
 
9.5%
2 11
 
7.0%
5 7
 
4.4%
8 6
 
3.8%
6 2
 
1.3%
4 2
 
1.3%
7 2
 
1.3%
9 1
 
0.6%
Latin
ValueCountFrequency (%)
B 3
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 161
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 89
55.3%
3 23
 
14.3%
1 15
 
9.3%
2 11
 
6.8%
5 7
 
4.3%
8 6
 
3.7%
B 3
 
1.9%
6 2
 
1.2%
4 2
 
1.2%
7 2
 
1.2%

제공기관기관명
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing23
Missing (%)100.0%
Memory size339.0 B

작업일시
Categorical

CONSTANT 

Distinct1
Distinct (%)4.3%
Missing0
Missing (%)0.0%
Memory size316.0 B
2024-05-02 15:11:49.0
23 

Length

Max length21
Median length21
Mean length21
Min length21

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row2024-05-02 15:11:49.0
2nd row2024-05-02 15:11:49.0
3rd row2024-05-02 15:11:49.0
4th row2024-05-02 15:11:49.0
5th row2024-05-02 15:11:49.0

Common Values

ValueCountFrequency (%)
2024-05-02 15:11:49.0 23
100.0%

Length

2024-05-03T23:47:27.710494image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-03T23:47:27.897906image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2024-05-02 23
50.0%
15:11:49.0 23
50.0%

Interactions

2024-05-03T23:47:04.038437image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-03T23:46:59.611102image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-03T23:47:00.924091image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-03T23:47:02.711766image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-03T23:47:04.350985image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-03T23:46:59.921606image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-03T23:47:01.285434image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-03T23:47:03.024259image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-03T23:47:04.758287image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-03T23:47:00.260277image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-03T23:47:01.599679image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-03T23:47:03.405790image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-03T23:47:05.096551image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-03T23:47:00.616169image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-03T23:47:02.307323image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-03T23:47:03.712993image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-05-03T23:47:28.095956image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
견인차량보관소명소재지도로명주소소재지지번주소위도경도보관소전화번호보관소면적보관가능대수견인료기본요금견인료추가요금보관료관리기관전화번호관리기관명데이터기준일자제공기관코드
견인차량보관소명1.0001.0001.0001.0000.9841.0000.9600.9781.0001.0000.9641.0001.0001.0001.000
소재지도로명주소1.0001.0001.0001.0001.0001.0000.9760.9501.0001.0000.9321.0001.0001.0001.000
소재지지번주소1.0001.0001.0001.0001.0001.0001.0000.9661.0001.0000.9531.0000.9941.0001.000
위도1.0001.0001.0001.0000.5151.0000.8500.6241.0000.5190.9451.0001.0001.0001.000
경도0.9841.0001.0000.5151.0000.9840.5690.0001.0000.9070.6501.0001.0001.0001.000
보관소전화번호1.0001.0001.0001.0000.9841.0000.9600.9781.0001.0000.9641.0001.0001.0001.000
보관소면적0.9600.9761.0000.8500.5690.9601.0000.8711.0000.0000.9701.0000.9131.0001.000
보관가능대수0.9780.9500.9660.6240.0000.9780.8711.0001.0000.4860.9141.0001.0001.0001.000
견인료기본요금1.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.000
견인료추가요금1.0001.0001.0000.5190.9071.0000.0000.4861.0001.0001.0001.0001.0001.0001.000
보관료0.9640.9320.9530.9450.6500.9640.9700.9141.0001.0001.0000.9850.9531.0001.000
관리기관전화번호1.0001.0001.0001.0001.0001.0001.0001.0001.0001.0000.9851.0001.0001.0001.000
관리기관명1.0001.0000.9941.0001.0001.0000.9131.0001.0001.0000.9531.0001.0001.0001.000
데이터기준일자1.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.000
제공기관코드1.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.000
2024-05-03T23:47:28.827602image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
위도경도보관소면적보관가능대수
위도1.0000.237-0.330-0.280
경도0.2371.0000.1790.185
보관소면적-0.3300.1791.0000.786
보관가능대수-0.2800.1850.7861.000

Missing values

2024-05-03T23:47:05.669551image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-05-03T23:47:06.598038image/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.
2024-05-03T23:47:07.023264image/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

견인차량보관소명소재지도로명주소소재지지번주소위도경도보관소전화번호보관소면적보관가능대수견인료기본요금견인료추가요금보관료관리기관전화번호관리기관명데이터기준일자제공기관코드제공기관기관명작업일시
0가양동차량보관소서울특별시 강서구 양천로59길 16-9서울특별시 강서구 가양동 451-737.560203126.85970102-3661-19367310.0123승용자동차(경형 40000원+소형 45000원+중형 50000원+대형 60000원)+승합자동차(경형 40000원+소형 60000원+중형 80000원+대형 140000원)+화물 및 특수자동차(2.5톤 미만 40000원+2.5톤 이상 ~ 6.5톤 미만 60000원+6.5톤 이상 ~ 10톤 미만 80000원+10톤 이상 140000원) * 종전 무게중심(2.5톤 기준 40000원) → 배기량별 차등적용없음6.5톤 미만 30분당 700원+6.5톤 이상~10톤 미만 30분당 1200원 (단 1회 보관료는 50만 원 한도)02-3661-1936서울특별시 강서구시설관리공단2024-02-223150000<NA>2024-05-02 15:11:49.0
1용산견인차량보관소서울특별시 용산구 새창로 170-4(한강로3가)서울특별시 용산구 한강로3가 23-137.532419126.96326202-707-31731715.043승용(경형 40000원+소형 45000원+중형 50000원+대형 60000원)+승합(경형 40000원+소형 60000원+중형 80000원+대형 140000원)+화물 및 특수(2.5톤미만 40000원+2.5톤이상 6.5톤미만 60000원+6.5톤이상 10톤미만 80000원+10톤이상 140000원)없음30분당 700원+승합자동차 중 중과 대형 1200원+1회 보관료 500000원070-4906-2525서울특별시 용산구 시설관리공단2023-12-063020000<NA>2024-05-02 15:11:49.0
2영등포구견인차량보관소서울특별시 영등포구 경인로112길 28서울특별시 영등포구 영등포동1가 3-537.517462126.91592802-2650-14851609.0394만원~14만원<NA>30분당 700원~1200원02-2650-1400영등포구시설관리공단2023-12-013180000<NA>2024-05-02 15:11:49.0
3구로견인차량보관소서울특별시 구로구 서해안로 2395서울특별시 구로구 개봉동 247-2337.495301126.85022502-2066-1325890.048경차 40000원+소형 45000원+중형 50000원+대형 60000원없음30분당 700원(승용+승합+ 이륜차, 화물+ 특수자동차 6.5톤 미만)/ 30분당 1200원(승합(중형+대형)+화물+ 특수자동차 6.5톤이상)/ 1회 보관료는 50만원 한도료는 50만원 한도02-860-3191서울특별시 구로구청 주차관리과2023-11-223160000<NA>2024-05-02 15:11:49.0
4관악동작견인차량보관소서울특별시 관악구 신사로 7서울특별시 관악구 신림동 1677-437.484698126.90406702-855-86113032.082승용자동차((경형 40000원+소형 45000원+중형 50000원+대형 60000원)+승합자동차(경형 40000원+소형 60000원+중형 80000원+대형 140000원+이륜자동차 40000원)+화물자동차?특수자동차(2.5톤 미만 40000원+2.5톤 이상 6.5톤 미만 60000원+6.5톤 이상 10톤 미만 80000원+10톤 이상 140000원)해당 없음기본 30분당 700원(승합자동차중 중형과 대형은 1200원)+화물자동차?특수자동차 6.5톤 이상 30분당 1200원(1회 보관료는 50만원 한도로 함)02-832-2445서울특별시 동작구시설관리공단2023-10-103200000<NA>2024-05-02 15:11:49.0
5마포구 견인차량보관소서울특별시 마포구 토정로2(양화진공영주차장)서울특별시 마포구 합정동 139-2137.54555126.91119902-373-5401101.016승용(경형 40000원+소형 45000원+중형 50000원+대형 60000원)+승합(경형 40000원+소형 60000원+중형 80000원+대형 140000)<NA>30분당 승용(경형 700원+소형 700원+중형 700원+대형 700원)+30분당 승합(경형 700원+소형 700원+중형 1200원+대형 1200원)+(*단, 1회 보관료 한도는 50만원)02-373-5405마포구시설관리공단2023-08-283130000<NA>2024-05-02 15:11:49.0
6서울특별시성동구견인차량보관소서울특별시 성동구 천호대로 78길 9서울특별시 성동구 용답동 182-1037.563054127.05611902-2204-7984924.040경형40000원+소형45000원+중형50000원+대형60000원+경형승합40000원+소형승합60000원+중형80000원승합+대형승합140000원+2.5톤미만화물또는특수40000원+2.5톤이상6.5톤미만화물또는특수60000원+6.5톤이상10톤미만화물또는특수80000원+10톤이상화물또는특수140000원<NA>승용700원+경형승합700원+소형승합700원+6.5톤미만 화물 또는 특수700원+중대형 승합1200원+6.5톤이상 화물 또는 특수1200원02-2204-7900서울특별시성동구도시관리공단2023-08-253030000<NA>2024-05-02 15:11:49.0
7강동구견인차량보관소서울특별시 강동구 아리수로91길 54서울특별시 강동구 665-4(강일동)37.565982127.17227802-3425-69352650.07340000원~140000원<NA>30분당 700원02-424-0101강동운수2023-08-183240000<NA>2024-05-02 15:11:49.0
8성북구견인차량보관소서울특별시 성북구 동소문로 44길 44-1서울특별시 성북구 하월곡동 88-837.60595127.0303402-6925-20041006.02140000<NA>30분당 700원(승합자동차 중 중형과 대형 및 화물자동차 중 6.5톤 이상은 1200원) * 단 1회 보관료는 50만원을 한도로 한다.02-6925-2004성북구도시관리공단2023-08-173070000<NA>2024-05-02 15:11:49.0
9양천구 견인차량보관소서울특별시 양천구 목동동로 298서울특별시 양천구 목동 91537.528132126.87652302-2643-13371855.072경형 40000원+소형 45000원+중형 50000원+대형60000원<NA>기본 30분 700원+30분당 700원02-2620-3736서울특별시 양천구청2023-08-143140000<NA>2024-05-02 15:11:49.0
견인차량보관소명소재지도로명주소소재지지번주소위도경도보관소전화번호보관소면적보관가능대수견인료기본요금견인료추가요금보관료관리기관전화번호관리기관명데이터기준일자제공기관코드제공기관기관명작업일시
13금천구 견인차량보관소서울특별시 금천구 가산디지털2로 169-34서울특별시 금천구 가산동 614-3437.483304126.87608202-854-52732514.055승용차 : 경형 40,000원승용차 : 소형 45,000원승용차 : 중형 50,000원승용차 : 대형 60,000원승합차 : 경형 40,000원승합차 : 소형 60,000원승합차 : 중형 80,000원화물차(2.5톤미만) : 40,000원이륜차 : 40,000원없음150원(5분)02-809-0061서울특별시 금천구시설관리공단 (구청위탁)2023-07-14B551898<NA>2024-05-02 15:11:49.0
14서초구견인차량보관소<NA>서울특별시 서초구 원지동 361-137.445883127.05681402-575-50222700.06050000원<NA>700원(30분당)02-2155-7250서울특별시 서초구청 주차관리과2023-07-073210000<NA>2024-05-02 15:11:49.0
15강북구견인차량보관소서울특별시 강북구 삼양로 678서울특별시 강북구 우이동 26537.66337127.01266602-944-30275497.065승용자동차(경형:40000원+소형:45000원+중형:50000원+대형:60000원)승합자동차(경형:40000원+소형:60000원+중형:80000원+대형:140000원)이륜자동차?개인형이동장치:40000원+화물자동차 및 특수자동차(2.5톤미만:40,000원+2.5톤이상6.5톤미만:60000원+6.5톤이상10톤미만:80000원+10톤이상:140000원)<NA>30분당 700원(승합자동차중 중형과 대형+ 화물 및 특수자동차중 6.5톤이상은 30분당 1200원). 단 1회 보관료는 50만원을 한도로 한다.02-944-3026서울특별시 강북구도시관리공단2023-07-053080000<NA>2024-05-02 15:11:49.0
16면목견인보관소서울특별시 중랑구 면목천로 33서울특별시 중랑구 면목동168-237.579209127.08120702-492-8185<NA>64승용(경형 40000원+소형 45000원+중형 50000원+대형 60000원)+승합(경형 40000원+소형 60000원+중형 80000원+대형 140000원)+화물?특수(2.5톤미만 40000원+2.5톤이상 6.5톤미만 60000원+6.5톤이상 10톤미만 80000원+10톤이상 140000원)<NA>승용?승합(소형)?화물(6.5톤미만)?특수(6.5톤미만) 30분당 700원+승합(중형?대형)?화물(6.5톤이상)?특수(6.5톤이상) 1200원+1회 보관료 한도 50만 원02-2094-2634서울특별시 중랑구청2023-05-023060000<NA>2024-05-02 15:11:49.0
17중구 견인차량보관소서울특별시 중구 손기정로 101서울특별시 중구 만리동2가 6-137.555479126.96481602-2280-8374962.532승용자동차 경형 40000원/소형 45000원/중형 50000원/대형 60000원승합자동차 경형 40000원/소형 60000원/중형 80000원/대형 140000원승용?승합자동차의 규모별 세부기준은 자동차관리법 시행규칙 별표1에 따름기본 30분 700원(승합차 중 중형과 대형은 1200원)1회 보관료는 50만원을 한도로 함02-3396-6254서울특별시 중구청 주차관리과2023-04-123010000<NA>2024-05-02 15:11:49.0
18홍제견인차량보관소서울특별시 서대문구 홍제내길 227서울특별시 서대문구 홍제동 294-8437.590834126.94100902-360-8542852.039승용경형,승합경형,이륜자동차,화물특수2.5톤미만40000원 승용소형45000원 승용중형50000원 승용대형,승합소형,화물특수6.5톤미만60000원 승합중형,10톤미만80000원 승합대형,화물특수10톤이상140000원<NA>기본 30분당 700원(승합중형,대형 30분당 1200원), 화물특수 30분당 1200원02-360-8542서울특별시 서대문구청2022-10-303120000<NA>2024-05-02 15:11:49.0
19홍제견인차량보관소서울특별시 서대문구 홍제내길 227서울특별시 서대문구 홍제동 294-8437.590834126.94100902-360-8542852.039승용경형ㆍ승합경형ㆍ이륜자동차ㆍ화물특수2.5톤미만40000원+승용소형45000원+승용중형50000원+승용대형ㆍ승합소형ㆍ화물특수6.5톤미만60000원+승합중형ㆍ10톤미만80000원+승합대형ㆍ화물특수10톤이상140000원+개인형이동장치 40000원<NA>기본 30분당 700원(승합 중형+승합 대형 30분당 1200원)+화물특수 30분당 1200원02-360-8542서울특별시 서대문구청2022-06-303000000<NA>2024-05-02 15:11:49.0
20은평구 견인차량보관소서울특별시 은평구 서오릉로 47 지하서울특별시 은평구 녹번동 153-137.605149126.92304102-350-5180<NA>17승용소형 기준 45,000원(차종별 상이)<NA>30분당 700원(화물,특수자동차 1,200원)02-350-5181서울특별시 은평구시설관리공단2021-07-013110000<NA>2024-05-02 15:11:49.0
21송파구 견인차량보관소서울특별시 송파구 탄천동로 690서울특별시 송파구 장지동 770-137.477209127.11837302-414-70373777.076승용자동차(40,000~60,000원), 승합자동차(40,000~140,000원), 화물,특수자동차(40,000~140,000원)<NA>30분당 700원(1회 보관료는 50만원 한도)02-214-3204서울특별시 송파구청2021-03-033230000<NA>2024-05-02 15:11:49.0
22성북구견인차량보관소서울특별시 성북구 화랑로207 한신저축은행 옆서울특별시 성북구 장위동 65-171 한신저축은행 옆37.608921127.05059302-6925-20041083.0292.5톤 미만 40,000원 / 6.5톤미만 46,000원 / 10톤미만 66,000원 / 10톤이상 115,000원1회보관료 최고한도 500,000원30분당 700원02-962-2082성북구도시관리공단(주차사업팀)2017-05-18B551281<NA>2024-05-02 15:11:49.0