Overview

Dataset statistics

Number of variables34
Number of observations2314
Missing cells24764
Missing cells (%)31.5%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory648.7 KiB
Average record size in memory287.1 B

Variable types

Text9
Categorical4
Numeric14
DateTime7

Dataset

Description공공데이터 제공 표준데이터 속성정보(허용값, 표현형식/단위 등)는 [공공데이터 제공 표준] 전문을 참고하시기 바랍니다.(공공데이터포털>정보공유>자료실) 각 기관에서 등록한 표준데이터를 취합하여 제공하기 때문에 갱신주기는 개별 파일마다 다릅니다.(기관에서 등록한 데이터를 취합한 것으로 개별 파일별 갱신시점이 다름)
Author지방자치단체
URLhttps://www.data.go.kr/data/15025689/standard.do

Alerts

전기승합자동차보유대수 is highly imbalanced (99.5%)Imbalance
중형차요금 is highly imbalanced (78.6%)Imbalance
휴무일 is highly imbalanced (76.3%)Imbalance
소재지도로명주소 has 43 (1.9%) missing valuesMissing
소재지지번주소 has 615 (26.6%) missing valuesMissing
차고지도로명주소 has 489 (21.1%) missing valuesMissing
차고지지번주소 has 624 (27.0%) missing valuesMissing
보유차고지수용능력 has 1372 (59.3%) missing valuesMissing
경차요금 has 1994 (86.2%) missing valuesMissing
소형차요금 has 1975 (85.4%) missing valuesMissing
대형차요금 has 1966 (85.0%) missing valuesMissing
승합차요금 has 1967 (85.0%) missing valuesMissing
레저용차요금 has 2102 (90.8%) missing valuesMissing
수입차요금 has 2101 (90.8%) missing valuesMissing
주말운영시작시각 has 1531 (66.2%) missing valuesMissing
주말운영종료시각 has 1532 (66.2%) missing valuesMissing
공휴일운영시작시각 has 1581 (68.3%) missing valuesMissing
공휴일운영종료시각 has 1581 (68.3%) missing valuesMissing
홈페이지주소 has 2160 (93.3%) missing valuesMissing
대표자명 has 1131 (48.9%) missing valuesMissing
보유차고지수용능력 is highly skewed (γ1 = 25.37566215)Skewed
자동차총보유대수 is highly skewed (γ1 = 31.05980292)Skewed
승용차보유대수 is highly skewed (γ1 = 30.76881267)Skewed
승합차보유대수 is highly skewed (γ1 = 31.29550432)Skewed
전기승용자동차보유대수 is highly skewed (γ1 = 31.26202146)Skewed
자동차총보유대수 has 164 (7.1%) zerosZeros
승용차보유대수 has 184 (8.0%) zerosZeros
승합차보유대수 has 1003 (43.3%) zerosZeros
전기승용자동차보유대수 has 2104 (90.9%) zerosZeros
경차요금 has 83 (3.6%) zerosZeros
소형차요금 has 79 (3.4%) zerosZeros
대형차요금 has 81 (3.5%) zerosZeros
승합차요금 has 79 (3.4%) zerosZeros
레저용차요금 has 96 (4.1%) zerosZeros
수입차요금 has 98 (4.2%) zerosZeros

Reproduction

Analysis started2024-05-04 08:11:18.321337
Analysis finished2024-05-04 08:11:22.652321
Duration4.33 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

Distinct1550
Distinct (%)67.0%
Missing0
Missing (%)0.0%
Memory size18.2 KiB
2024-05-04T08:11:23.146985image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length21
Median length19
Mean length7.4511668
Min length2

Characters and Unicode

Total characters17242
Distinct characters416
Distinct categories9 ?
Distinct scripts3 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1165 ?
Unique (%)50.3%

Sample

1st row㈜지엠물류
2nd row㈜지엠물류
3rd row㈜지엠물류
4th row누리렌트카㈜
5th row누리렌트카㈜
ValueCountFrequency (%)
㈜웨이 30
 
1.1%
울산영업소 22
 
0.8%
도도렌트카 21
 
0.8%
㈜스마트렌트카 21
 
0.8%
롯데렌탈㈜ 20
 
0.8%
주식회사 20
 
0.8%
㈜쏘카 19
 
0.7%
마스타자동차관리 19
 
0.7%
㈜현대관광렌트카 18
 
0.7%
㈜로또렌트카 16
 
0.6%
Other values (1521) 2421
92.2%
2024-05-04T08:11:24.891712image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1900
 
11.0%
1813
 
10.5%
1558
 
9.0%
1397
 
8.1%
) 523
 
3.0%
523
 
3.0%
( 522
 
3.0%
402
 
2.3%
352
 
2.0%
320
 
1.9%
Other values (406) 7932
46.0%

Most occurring categories

ValueCountFrequency (%)
Other Letter 14390
83.5%
Other Symbol 1397
 
8.1%
Close Punctuation 525
 
3.0%
Open Punctuation 524
 
3.0%
Space Separator 313
 
1.8%
Uppercase Letter 56
 
0.3%
Decimal Number 32
 
0.2%
Dash Punctuation 3
 
< 0.1%
Lowercase Letter 2
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
1900
 
13.2%
1813
 
12.6%
1558
 
10.8%
523
 
3.6%
402
 
2.8%
352
 
2.4%
320
 
2.2%
257
 
1.8%
255
 
1.8%
238
 
1.7%
Other values (380) 6772
47.1%
Uppercase Letter
ValueCountFrequency (%)
K 22
39.3%
S 17
30.4%
T 4
 
7.1%
M 3
 
5.4%
G 3
 
5.4%
X 3
 
5.4%
V 1
 
1.8%
I 1
 
1.8%
P 1
 
1.8%
D 1
 
1.8%
Decimal Number
ValueCountFrequency (%)
2 9
28.1%
1 6
18.8%
3 5
15.6%
0 5
15.6%
6 3
 
9.4%
4 3
 
9.4%
5 1
 
3.1%
Close Punctuation
ValueCountFrequency (%)
) 523
99.6%
] 2
 
0.4%
Open Punctuation
ValueCountFrequency (%)
( 522
99.6%
[ 2
 
0.4%
Lowercase Letter
ValueCountFrequency (%)
k 1
50.0%
s 1
50.0%
Other Symbol
ValueCountFrequency (%)
1397
100.0%
Space Separator
ValueCountFrequency (%)
313
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 3
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 15787
91.6%
Common 1397
 
8.1%
Latin 58
 
0.3%

Most frequent character per script

Hangul
ValueCountFrequency (%)
1900
 
12.0%
1813
 
11.5%
1558
 
9.9%
1397
 
8.8%
523
 
3.3%
402
 
2.5%
352
 
2.2%
320
 
2.0%
257
 
1.6%
255
 
1.6%
Other values (381) 7010
44.4%
Common
ValueCountFrequency (%)
) 523
37.4%
( 522
37.4%
313
22.4%
2 9
 
0.6%
1 6
 
0.4%
3 5
 
0.4%
0 5
 
0.4%
- 3
 
0.2%
6 3
 
0.2%
4 3
 
0.2%
Other values (3) 5
 
0.4%
Latin
ValueCountFrequency (%)
K 22
37.9%
S 17
29.3%
T 4
 
6.9%
M 3
 
5.2%
G 3
 
5.2%
X 3
 
5.2%
V 1
 
1.7%
I 1
 
1.7%
P 1
 
1.7%
k 1
 
1.7%
Other values (2) 2
 
3.4%

Most occurring blocks

ValueCountFrequency (%)
Hangul 14390
83.5%
ASCII 1455
 
8.4%
None 1397
 
8.1%

Most frequent character per block

Hangul
ValueCountFrequency (%)
1900
 
13.2%
1813
 
12.6%
1558
 
10.8%
523
 
3.6%
402
 
2.8%
352
 
2.4%
320
 
2.2%
257
 
1.8%
255
 
1.8%
238
 
1.7%
Other values (380) 6772
47.1%
None
ValueCountFrequency (%)
1397
100.0%
ASCII
ValueCountFrequency (%)
) 523
35.9%
( 522
35.9%
313
21.5%
K 22
 
1.5%
S 17
 
1.2%
2 9
 
0.6%
1 6
 
0.4%
3 5
 
0.3%
0 5
 
0.3%
T 4
 
0.3%
Other values (15) 29
 
2.0%

사업장구분
Categorical

Distinct2
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size18.2 KiB
주사업장
1296 
영업소
1018 

Length

Max length4
Median length4
Mean length3.5600691
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
주사업장 1296
56.0%
영업소 1018
44.0%

Length

2024-05-04T08:11:25.494966image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-04T08:11:25.845786image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
주사업장 1296
56.0%
영업소 1018
44.0%
Distinct1890
Distinct (%)83.2%
Missing43
Missing (%)1.9%
Memory size18.2 KiB
2024-05-04T08:11:26.622186image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length53
Median length43
Mean length23.457508
Min length13

Characters and Unicode

Total characters53272
Distinct characters468
Distinct categories9 ?
Distinct scripts3 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1649 ?
Unique (%)72.6%

Sample

1st row대전광역시 중구 대종로550번길 5, 1306호(선화동, 유원오피스텔)
2nd row대전광역시 중구 대종로550번길 5, 1306호(선화동, 유원오피스텔)
3rd row대전광역시 중구 대종로550번길 5, 1306호(선화동, 유원오피스텔)
4th row대전광역시 서구 월평로13번길 60, 1층(월평동)
5th row대전광역시 서구 월평로13번길 60, 1층(월평동)
ValueCountFrequency (%)
경기도 388
 
3.5%
서울특별시 338
 
3.1%
대전광역시 180
 
1.6%
경상북도 156
 
1.4%
강원도 155
 
1.4%
경상남도 122
 
1.1%
서구 118
 
1.1%
제주시 115
 
1.0%
제주특별자치도 115
 
1.0%
전라남도 115
 
1.0%
Other values (3473) 9169
83.6%
2024-05-04T08:11:28.098156image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
8700
 
16.3%
1 2086
 
3.9%
2039
 
3.8%
1917
 
3.6%
1555
 
2.9%
2 1404
 
2.6%
1252
 
2.4%
1235
 
2.3%
3 1033
 
1.9%
866
 
1.6%
Other values (458) 31185
58.5%

Most occurring categories

ValueCountFrequency (%)
Other Letter 32298
60.6%
Decimal Number 9273
 
17.4%
Space Separator 8700
 
16.3%
Other Punctuation 830
 
1.6%
Open Punctuation 788
 
1.5%
Close Punctuation 787
 
1.5%
Dash Punctuation 478
 
0.9%
Uppercase Letter 112
 
0.2%
Math Symbol 6
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
2039
 
6.3%
1917
 
5.9%
1555
 
4.8%
1252
 
3.9%
1235
 
3.8%
866
 
2.7%
777
 
2.4%
756
 
2.3%
736
 
2.3%
705
 
2.2%
Other values (421) 20460
63.3%
Uppercase Letter
ValueCountFrequency (%)
A 20
17.9%
B 18
16.1%
T 18
16.1%
E 14
12.5%
K 13
11.6%
R 5
 
4.5%
W 4
 
3.6%
C 4
 
3.6%
O 4
 
3.6%
F 3
 
2.7%
Other values (7) 9
8.0%
Decimal Number
ValueCountFrequency (%)
1 2086
22.5%
2 1404
15.1%
3 1033
11.1%
0 857
9.2%
4 845
9.1%
6 725
 
7.8%
5 685
 
7.4%
7 602
 
6.5%
8 531
 
5.7%
9 505
 
5.4%
Other Punctuation
ValueCountFrequency (%)
, 823
99.2%
4
 
0.5%
@ 1
 
0.1%
· 1
 
0.1%
. 1
 
0.1%
Space Separator
ValueCountFrequency (%)
8700
100.0%
Open Punctuation
ValueCountFrequency (%)
( 788
100.0%
Close Punctuation
ValueCountFrequency (%)
) 787
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 478
100.0%
Math Symbol
ValueCountFrequency (%)
+ 6
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 32298
60.6%
Common 20862
39.2%
Latin 112
 
0.2%

Most frequent character per script

Hangul
ValueCountFrequency (%)
2039
 
6.3%
1917
 
5.9%
1555
 
4.8%
1252
 
3.9%
1235
 
3.8%
866
 
2.7%
777
 
2.4%
756
 
2.3%
736
 
2.3%
705
 
2.2%
Other values (421) 20460
63.3%
Common
ValueCountFrequency (%)
8700
41.7%
1 2086
 
10.0%
2 1404
 
6.7%
3 1033
 
5.0%
0 857
 
4.1%
4 845
 
4.1%
, 823
 
3.9%
( 788
 
3.8%
) 787
 
3.8%
6 725
 
3.5%
Other values (10) 2814
 
13.5%
Latin
ValueCountFrequency (%)
A 20
17.9%
B 18
16.1%
T 18
16.1%
E 14
12.5%
K 13
11.6%
R 5
 
4.5%
W 4
 
3.6%
C 4
 
3.6%
O 4
 
3.6%
F 3
 
2.7%
Other values (7) 9
8.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 32298
60.6%
ASCII 20969
39.4%
None 5
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
8700
41.5%
1 2086
 
9.9%
2 1404
 
6.7%
3 1033
 
4.9%
0 857
 
4.1%
4 845
 
4.0%
, 823
 
3.9%
( 788
 
3.8%
) 787
 
3.8%
6 725
 
3.5%
Other values (25) 2921
 
13.9%
Hangul
ValueCountFrequency (%)
2039
 
6.3%
1917
 
5.9%
1555
 
4.8%
1252
 
3.9%
1235
 
3.8%
866
 
2.7%
777
 
2.4%
756
 
2.3%
736
 
2.3%
705
 
2.2%
Other values (421) 20460
63.3%
None
ValueCountFrequency (%)
4
80.0%
· 1
 
20.0%

소재지지번주소
Text

MISSING 

Distinct1340
Distinct (%)78.9%
Missing615
Missing (%)26.6%
Memory size18.2 KiB
2024-05-04T08:11:28.826834image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length56
Median length45
Mean length21.226604
Min length14

Characters and Unicode

Total characters36064
Distinct characters364
Distinct categories8 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1122 ?
Unique (%)66.0%

Sample

1st row대전광역시 중구 선화동 79-14, 유원오피스텔 1306호
2nd row대전광역시 중구 선화동 79-14, 유원오피스텔 1306호
3rd row대전광역시 중구 선화동 79-14, 유원오피스텔 1306호
4th row대전광역시 서구 월평동 411
5th row대전광역시 서구 월평동 411
ValueCountFrequency (%)
경기도 331
 
4.3%
서울특별시 216
 
2.8%
대전광역시 179
 
2.3%
강원도 133
 
1.7%
서구 117
 
1.5%
제주시 115
 
1.5%
제주특별자치도 115
 
1.5%
경상남도 103
 
1.3%
경상북도 87
 
1.1%
충청남도 87
 
1.1%
Other values (2459) 6303
81.0%
2024-05-04T08:11:29.917748image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
6089
 
16.9%
1 1650
 
4.6%
1541
 
4.3%
1497
 
4.2%
- 1334
 
3.7%
1203
 
3.3%
2 1045
 
2.9%
915
 
2.5%
3 757
 
2.1%
4 651
 
1.8%
Other values (354) 19382
53.7%

Most occurring categories

ValueCountFrequency (%)
Other Letter 20647
57.3%
Decimal Number 7621
 
21.1%
Space Separator 6089
 
16.9%
Dash Punctuation 1334
 
3.7%
Other Punctuation 235
 
0.7%
Uppercase Letter 68
 
0.2%
Open Punctuation 35
 
0.1%
Close Punctuation 35
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
1541
 
7.5%
1497
 
7.3%
1203
 
5.8%
915
 
4.4%
551
 
2.7%
506
 
2.5%
505
 
2.4%
496
 
2.4%
429
 
2.1%
425
 
2.1%
Other values (325) 12579
60.9%
Uppercase Letter
ValueCountFrequency (%)
K 15
22.1%
T 14
20.6%
E 10
14.7%
B 9
13.2%
A 6
 
8.8%
S 3
 
4.4%
C 3
 
4.4%
F 3
 
4.4%
G 1
 
1.5%
H 1
 
1.5%
Other values (3) 3
 
4.4%
Decimal Number
ValueCountFrequency (%)
1 1650
21.7%
2 1045
13.7%
3 757
9.9%
4 651
 
8.5%
5 649
 
8.5%
6 646
 
8.5%
0 622
 
8.2%
7 547
 
7.2%
9 539
 
7.1%
8 515
 
6.8%
Other Punctuation
ValueCountFrequency (%)
, 234
99.6%
. 1
 
0.4%
Space Separator
ValueCountFrequency (%)
6089
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 1334
100.0%
Open Punctuation
ValueCountFrequency (%)
( 35
100.0%
Close Punctuation
ValueCountFrequency (%)
) 35
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 20647
57.3%
Common 15349
42.6%
Latin 68
 
0.2%

Most frequent character per script

Hangul
ValueCountFrequency (%)
1541
 
7.5%
1497
 
7.3%
1203
 
5.8%
915
 
4.4%
551
 
2.7%
506
 
2.5%
505
 
2.4%
496
 
2.4%
429
 
2.1%
425
 
2.1%
Other values (325) 12579
60.9%
Common
ValueCountFrequency (%)
6089
39.7%
1 1650
 
10.7%
- 1334
 
8.7%
2 1045
 
6.8%
3 757
 
4.9%
4 651
 
4.2%
5 649
 
4.2%
6 646
 
4.2%
0 622
 
4.1%
7 547
 
3.6%
Other values (6) 1359
 
8.9%
Latin
ValueCountFrequency (%)
K 15
22.1%
T 14
20.6%
E 10
14.7%
B 9
13.2%
A 6
 
8.8%
S 3
 
4.4%
C 3
 
4.4%
F 3
 
4.4%
G 1
 
1.5%
H 1
 
1.5%
Other values (3) 3
 
4.4%

Most occurring blocks

ValueCountFrequency (%)
Hangul 20647
57.3%
ASCII 15417
42.7%

Most frequent character per block

ASCII
ValueCountFrequency (%)
6089
39.5%
1 1650
 
10.7%
- 1334
 
8.7%
2 1045
 
6.8%
3 757
 
4.9%
4 651
 
4.2%
5 649
 
4.2%
6 646
 
4.2%
0 622
 
4.0%
7 547
 
3.5%
Other values (19) 1427
 
9.3%
Hangul
ValueCountFrequency (%)
1541
 
7.5%
1497
 
7.3%
1203
 
5.8%
915
 
4.4%
551
 
2.7%
506
 
2.5%
505
 
2.4%
496
 
2.4%
429
 
2.1%
425
 
2.1%
Other values (325) 12579
60.9%

위도
Real number (ℝ)

Distinct1810
Distinct (%)78.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean36.489546
Minimum33.48258
Maximum38.379741
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size20.5 KiB
2024-05-04T08:11:30.234514image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum33.48258
5-th percentile34.315508
Q135.565322
median36.767605
Q337.50381
95-th percentile37.76224
Maximum38.379741
Range4.8971615
Interquartile range (IQR)1.9384876

Descriptive statistics

Standard deviation1.1710503
Coefficient of variation (CV)0.032092761
Kurtosis-0.10710371
Mean36.489546
Median Absolute Deviation (MAD)0.78798268
Skewness-0.82656308
Sum84436.81
Variance1.3713588
MonotonicityNot monotonic
2024-05-04T08:11:30.641543image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
37.50532101 12
 
0.5%
37.54844358 11
 
0.5%
36.34872991 10
 
0.4%
36.34753577 10
 
0.4%
37.455019 9
 
0.4%
37.75515453 8
 
0.3%
36.33264646 7
 
0.3%
36.33046955 7
 
0.3%
33.51516802 7
 
0.3%
37.77614556 6
 
0.3%
Other values (1800) 2227
96.2%
ValueCountFrequency (%)
33.48257951 1
 
< 0.1%
33.48515863 1
 
< 0.1%
33.4884685 1
 
< 0.1%
33.48962059 1
 
< 0.1%
33.48962761 1
 
< 0.1%
33.48978769 1
 
< 0.1%
33.49016975 3
0.1%
33.49033561 1
 
< 0.1%
33.49198895 1
 
< 0.1%
33.4932207 1
 
< 0.1%
ValueCountFrequency (%)
38.379741 1
< 0.1%
38.37972734 1
< 0.1%
38.24348719 2
0.1%
38.21054477 2
0.1%
38.20662719 2
0.1%
38.15427952 1
< 0.1%
38.14821979 2
0.1%
38.1235600036 1
< 0.1%
38.10161831 2
0.1%
38.09929702 2
0.1%

경도
Real number (ℝ)

Distinct1804
Distinct (%)78.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean127.55436
Minimum126.36534
Maximum130.91202
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size20.5 KiB
2024-05-04T08:11:31.255396image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum126.36534
5-th percentile126.49652
Q1126.9088
median127.16224
Q3128.33354
95-th percentile129.12454
Maximum130.91202
Range4.5466713
Interquartile range (IQR)1.4247406

Descriptive statistics

Standard deviation0.87775697
Coefficient of variation (CV)0.0068814343
Kurtosis-0.16792942
Mean127.55436
Median Absolute Deviation (MAD)0.3598541
Skewness0.88919753
Sum295160.8
Variance0.77045729
MonotonicityNot monotonic
2024-05-04T08:11:31.772527image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
127.0528475 12
 
0.5%
126.9721128 11
 
0.5%
127.3882511 10
 
0.4%
127.3826059 10
 
0.4%
127.06536 9
 
0.4%
128.8865447 8
 
0.3%
128.8799999 8
 
0.3%
127.3371455 7
 
0.3%
127.3937558 7
 
0.3%
126.4913275502 7
 
0.3%
Other values (1794) 2225
96.2%
ValueCountFrequency (%)
126.3653449 3
0.1%
126.3792289227 1
 
< 0.1%
126.3816327 1
 
< 0.1%
126.3984589 1
 
< 0.1%
126.3998723 1
 
< 0.1%
126.4022574037 1
 
< 0.1%
126.4066469 1
 
< 0.1%
126.4171085 1
 
< 0.1%
126.4236808 1
 
< 0.1%
126.4262359 1
 
< 0.1%
ValueCountFrequency (%)
130.9120162 1
< 0.1%
130.9094171587 1
< 0.1%
130.9086855385 1
< 0.1%
130.908515943 1
< 0.1%
130.9072082153 1
< 0.1%
130.8984717 1
< 0.1%
130.8969168546 1
< 0.1%
130.8735594959 1
< 0.1%
130.8377230977 1
< 0.1%
130.8376504 1
< 0.1%
Distinct1516
Distinct (%)83.1%
Missing489
Missing (%)21.1%
Memory size18.2 KiB
2024-05-04T08:11:32.490120image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length101
Median length66
Mean length22.249863
Min length1

Characters and Unicode

Total characters40606
Distinct characters455
Distinct categories10 ?
Distinct scripts3 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1311 ?
Unique (%)71.8%

Sample

1st row대전광역시 대덕구 한남로114번길 1
2nd row충남 금산군 진산면 만악리 432-5
3rd row충남 논산시 광석면 천동리 373-1
4th row대전광역시 동구 대전천동로 58
5th row대전광역시 서구 신갈마로141번길 14
ValueCountFrequency (%)
경기도 361
 
4.2%
서울특별시 255
 
2.9%
강원도 146
 
1.7%
경상북도 145
 
1.7%
대전광역시 137
 
1.6%
경상남도 123
 
1.4%
서구 97
 
1.1%
전라북도 89
 
1.0%
충청남도 81
 
0.9%
강릉시 79
 
0.9%
Other values (2929) 7162
82.6%
2024-05-04T08:11:33.976689image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
6856
 
16.9%
1620
 
4.0%
1448
 
3.6%
1 1394
 
3.4%
1266
 
3.1%
967
 
2.4%
2 964
 
2.4%
791
 
1.9%
3 704
 
1.7%
702
 
1.7%
Other values (445) 23894
58.8%

Most occurring categories

ValueCountFrequency (%)
Other Letter 25189
62.0%
Decimal Number 6884
 
17.0%
Space Separator 6856
 
16.9%
Dash Punctuation 533
 
1.3%
Close Punctuation 378
 
0.9%
Open Punctuation 377
 
0.9%
Other Punctuation 263
 
0.6%
Math Symbol 71
 
0.2%
Uppercase Letter 53
 
0.1%
Lowercase Letter 2
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
1620
 
6.4%
1448
 
5.7%
1266
 
5.0%
967
 
3.8%
791
 
3.1%
702
 
2.8%
660
 
2.6%
588
 
2.3%
568
 
2.3%
547
 
2.2%
Other values (411) 16032
63.6%
Uppercase Letter
ValueCountFrequency (%)
B 19
35.8%
A 7
 
13.2%
C 6
 
11.3%
D 4
 
7.5%
P 3
 
5.7%
F 3
 
5.7%
I 2
 
3.8%
L 2
 
3.8%
E 2
 
3.8%
G 2
 
3.8%
Other values (3) 3
 
5.7%
Decimal Number
ValueCountFrequency (%)
1 1394
20.2%
2 964
14.0%
3 704
10.2%
4 689
10.0%
6 633
9.2%
5 560
8.1%
7 527
 
7.7%
0 508
 
7.4%
8 468
 
6.8%
9 437
 
6.3%
Other Punctuation
ValueCountFrequency (%)
, 257
97.7%
/ 4
 
1.5%
. 2
 
0.8%
Math Symbol
ValueCountFrequency (%)
+ 61
85.9%
~ 9
 
12.7%
1
 
1.4%
Space Separator
ValueCountFrequency (%)
6856
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 533
100.0%
Close Punctuation
ValueCountFrequency (%)
) 378
100.0%
Open Punctuation
ValueCountFrequency (%)
( 377
100.0%
Lowercase Letter
ValueCountFrequency (%)
b 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 25189
62.0%
Common 15362
37.8%
Latin 55
 
0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
1620
 
6.4%
1448
 
5.7%
1266
 
5.0%
967
 
3.8%
791
 
3.1%
702
 
2.8%
660
 
2.6%
588
 
2.3%
568
 
2.3%
547
 
2.2%
Other values (411) 16032
63.6%
Common
ValueCountFrequency (%)
6856
44.6%
1 1394
 
9.1%
2 964
 
6.3%
3 704
 
4.6%
4 689
 
4.5%
6 633
 
4.1%
5 560
 
3.6%
- 533
 
3.5%
7 527
 
3.4%
0 508
 
3.3%
Other values (10) 1994
 
13.0%
Latin
ValueCountFrequency (%)
B 19
34.5%
A 7
 
12.7%
C 6
 
10.9%
D 4
 
7.3%
P 3
 
5.5%
F 3
 
5.5%
I 2
 
3.6%
b 2
 
3.6%
L 2
 
3.6%
E 2
 
3.6%
Other values (4) 5
 
9.1%

Most occurring blocks

ValueCountFrequency (%)
Hangul 25189
62.0%
ASCII 15416
38.0%
Math Operators 1
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
6856
44.5%
1 1394
 
9.0%
2 964
 
6.3%
3 704
 
4.6%
4 689
 
4.5%
6 633
 
4.1%
5 560
 
3.6%
- 533
 
3.5%
7 527
 
3.4%
0 508
 
3.3%
Other values (23) 2048
 
13.3%
Hangul
ValueCountFrequency (%)
1620
 
6.4%
1448
 
5.7%
1266
 
5.0%
967
 
3.8%
791
 
3.1%
702
 
2.8%
660
 
2.6%
588
 
2.3%
568
 
2.3%
547
 
2.2%
Other values (411) 16032
63.6%
Math Operators
ValueCountFrequency (%)
1
100.0%

차고지지번주소
Text

MISSING 

Distinct1414
Distinct (%)83.7%
Missing624
Missing (%)27.0%
Memory size18.2 KiB
2024-05-04T08:11:35.135672image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length136
Median length112
Mean length21.921893
Min length14

Characters and Unicode

Total characters37048
Distinct characters381
Distinct categories10 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1224 ?
Unique (%)72.4%

Sample

1st row대전광역시 대덕구 오정동 448-5
2nd row충남 금산군 진산면 만악리 432-5
3rd row충남 논산시 광석면 천동리 373-1
4th row대전광역시 동구 대성동 173-3
5th row대전광역시 서구 갈마동 377-21
ValueCountFrequency (%)
경기도 290
 
3.6%
서울특별시 208
 
2.6%
대전광역시 137
 
1.7%
제주시 112
 
1.4%
제주특별자치도 112
 
1.4%
경상남도 109
 
1.3%
경상북도 108
 
1.3%
강원도 100
 
1.2%
서구 86
 
1.1%
전라남도 84
 
1.0%
Other values (2857) 6748
83.4%
2024-05-04T08:11:36.596833image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
6405
 
17.3%
1 1562
 
4.2%
1466
 
4.0%
1323
 
3.6%
- 1292
 
3.5%
1226
 
3.3%
2 1000
 
2.7%
844
 
2.3%
3 809
 
2.2%
5 698
 
1.9%
Other values (371) 20423
55.1%

Most occurring categories

ValueCountFrequency (%)
Other Letter 21465
57.9%
Decimal Number 7485
 
20.2%
Space Separator 6405
 
17.3%
Dash Punctuation 1292
 
3.5%
Other Punctuation 191
 
0.5%
Math Symbol 75
 
0.2%
Uppercase Letter 57
 
0.2%
Open Punctuation 35
 
0.1%
Close Punctuation 33
 
0.1%
Lowercase Letter 10
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
1466
 
6.8%
1323
 
6.2%
1226
 
5.7%
844
 
3.9%
627
 
2.9%
557
 
2.6%
546
 
2.5%
486
 
2.3%
481
 
2.2%
475
 
2.2%
Other values (330) 13434
62.6%
Uppercase Letter
ValueCountFrequency (%)
D 9
15.8%
L 9
15.8%
A 6
10.5%
C 6
10.5%
B 4
7.0%
K 4
7.0%
S 3
 
5.3%
E 3
 
5.3%
F 3
 
5.3%
M 2
 
3.5%
Other values (6) 8
14.0%
Decimal Number
ValueCountFrequency (%)
1 1562
20.9%
2 1000
13.4%
3 809
10.8%
5 698
9.3%
4 671
9.0%
6 617
 
8.2%
8 587
 
7.8%
7 544
 
7.3%
9 499
 
6.7%
0 498
 
6.7%
Lowercase Letter
ValueCountFrequency (%)
o 2
20.0%
s 2
20.0%
e 2
20.0%
t 2
20.0%
r 1
10.0%
m 1
10.0%
Other Punctuation
ValueCountFrequency (%)
, 185
96.9%
. 4
 
2.1%
/ 2
 
1.0%
Math Symbol
ValueCountFrequency (%)
+ 68
90.7%
~ 7
 
9.3%
Space Separator
ValueCountFrequency (%)
6405
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 1292
100.0%
Open Punctuation
ValueCountFrequency (%)
( 35
100.0%
Close Punctuation
ValueCountFrequency (%)
) 33
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 21465
57.9%
Common 15516
41.9%
Latin 67
 
0.2%

Most frequent character per script

Hangul
ValueCountFrequency (%)
1466
 
6.8%
1323
 
6.2%
1226
 
5.7%
844
 
3.9%
627
 
2.9%
557
 
2.6%
546
 
2.5%
486
 
2.3%
481
 
2.2%
475
 
2.2%
Other values (330) 13434
62.6%
Latin
ValueCountFrequency (%)
D 9
13.4%
L 9
13.4%
A 6
 
9.0%
C 6
 
9.0%
B 4
 
6.0%
K 4
 
6.0%
S 3
 
4.5%
E 3
 
4.5%
F 3
 
4.5%
M 2
 
3.0%
Other values (12) 18
26.9%
Common
ValueCountFrequency (%)
6405
41.3%
1 1562
 
10.1%
- 1292
 
8.3%
2 1000
 
6.4%
3 809
 
5.2%
5 698
 
4.5%
4 671
 
4.3%
6 617
 
4.0%
8 587
 
3.8%
7 544
 
3.5%
Other values (9) 1331
 
8.6%

Most occurring blocks

ValueCountFrequency (%)
Hangul 21465
57.9%
ASCII 15583
42.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
6405
41.1%
1 1562
 
10.0%
- 1292
 
8.3%
2 1000
 
6.4%
3 809
 
5.2%
5 698
 
4.5%
4 671
 
4.3%
6 617
 
4.0%
8 587
 
3.8%
7 544
 
3.5%
Other values (31) 1398
 
9.0%
Hangul
ValueCountFrequency (%)
1466
 
6.8%
1323
 
6.2%
1226
 
5.7%
844
 
3.9%
627
 
2.9%
557
 
2.6%
546
 
2.5%
486
 
2.3%
481
 
2.2%
475
 
2.2%
Other values (330) 13434
62.6%

보유차고지수용능력
Real number (ℝ)

MISSING  SKEWED 

Distinct345
Distinct (%)36.6%
Missing1372
Missing (%)59.3%
Infinite0
Infinite (%)0.0%
Mean448.13246
Minimum0
Maximum67000
Zeros9
Zeros (%)0.4%
Negative0
Negative (%)0.0%
Memory size20.5 KiB
2024-05-04T08:11:37.026437image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile4
Q122
median80
Q3320
95-th percentile1753.05
Maximum67000
Range67000
Interquartile range (IQR)298

Descriptive statistics

Standard deviation2318.2406
Coefficient of variation (CV)5.1731147
Kurtosis723.80052
Mean448.13246
Median Absolute Deviation (MAD)67
Skewness25.375662
Sum422140.78
Variance5374239.6
MonotonicityNot monotonic
2024-05-04T08:11:37.593816image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
100.0 66
 
2.9%
20.0 30
 
1.3%
130.0 25
 
1.1%
10.0 21
 
0.9%
50.0 21
 
0.9%
65.0 18
 
0.8%
2.0 18
 
0.8%
30.0 16
 
0.7%
13.0 15
 
0.6%
15.0 14
 
0.6%
Other values (335) 698
30.2%
(Missing) 1372
59.3%
ValueCountFrequency (%)
0.0 9
0.4%
1.0 5
 
0.2%
2.0 18
0.8%
3.0 14
0.6%
4.0 4
 
0.2%
5.0 13
0.6%
6.0 13
0.6%
7.0 10
0.4%
8.0 14
0.6%
9.0 5
 
0.2%
ValueCountFrequency (%)
67000.0 1
< 0.1%
6749.0 1
< 0.1%
6688.0 1
< 0.1%
6600.0 1
< 0.1%
6390.0 1
< 0.1%
5630.0 1
< 0.1%
5596.0 1
< 0.1%
5370.0 1
< 0.1%
5323.0 1
< 0.1%
5064.0 1
< 0.1%

자동차총보유대수
Real number (ℝ)

SKEWED  ZEROS 

Distinct350
Distinct (%)15.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean228.11063
Minimum0
Maximum127601
Zeros164
Zeros (%)7.1%
Negative0
Negative (%)0.0%
Memory size20.5 KiB
2024-05-04T08:11:38.219866image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q18
median36
Q392
95-th percentile291.35
Maximum127601
Range127601
Interquartile range (IQR)84

Descriptive statistics

Standard deviation3211.8824
Coefficient of variation (CV)14.080371
Kurtosis1125.26
Mean228.11063
Median Absolute Deviation (MAD)31
Skewness31.059803
Sum527848
Variance10316188
MonotonicityNot monotonic
2024-05-04T08:11:38.722576image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 164
 
7.1%
8 65
 
2.8%
10 61
 
2.6%
7 59
 
2.5%
1 58
 
2.5%
6 56
 
2.4%
2 55
 
2.4%
3 50
 
2.2%
4 44
 
1.9%
5 40
 
1.7%
Other values (340) 1662
71.8%
ValueCountFrequency (%)
0 164
7.1%
1 58
 
2.5%
2 55
 
2.4%
3 50
 
2.2%
4 44
 
1.9%
5 40
 
1.7%
6 56
 
2.4%
7 59
 
2.5%
8 65
 
2.8%
9 33
 
1.4%
ValueCountFrequency (%)
127601 1
< 0.1%
51355 1
< 0.1%
46693 1
< 0.1%
31167 2
0.1%
26381 1
< 0.1%
6835 1
< 0.1%
5211 1
< 0.1%
4831 1
< 0.1%
4780 1
< 0.1%
4342 1
< 0.1%

승용차보유대수
Real number (ℝ)

SKEWED  ZEROS 

Distinct323
Distinct (%)14.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean219.51556
Minimum0
Maximum122934
Zeros184
Zeros (%)8.0%
Negative0
Negative (%)0.0%
Memory size20.5 KiB
2024-05-04T08:11:39.194749image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q17
median33
Q386
95-th percentile260
Maximum122934
Range122934
Interquartile range (IQR)79

Descriptive statistics

Standard deviation3109.0081
Coefficient of variation (CV)14.163042
Kurtosis1106.3464
Mean219.51556
Median Absolute Deviation (MAD)29
Skewness30.768813
Sum507959
Variance9665931.3
MonotonicityNot monotonic
2024-05-04T08:11:39.698662image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 184
 
8.0%
7 69
 
3.0%
6 67
 
2.9%
1 66
 
2.9%
10 61
 
2.6%
2 58
 
2.5%
4 51
 
2.2%
3 48
 
2.1%
8 44
 
1.9%
5 41
 
1.8%
Other values (313) 1625
70.2%
ValueCountFrequency (%)
0 184
8.0%
1 66
 
2.9%
2 58
 
2.5%
3 48
 
2.1%
4 51
 
2.2%
5 41
 
1.8%
6 67
 
2.9%
7 69
 
3.0%
8 44
 
1.9%
9 39
 
1.7%
ValueCountFrequency (%)
122934 1
< 0.1%
49244 1
< 0.1%
45867 1
< 0.1%
30855 2
0.1%
26286 1
< 0.1%
6655 1
< 0.1%
5210 1
< 0.1%
4831 1
< 0.1%
4780 1
< 0.1%
4174 1
< 0.1%

승합차보유대수
Real number (ℝ)

SKEWED  ZEROS 

Distinct72
Distinct (%)3.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean7.1365601
Minimum0
Maximum2914
Zeros1003
Zeros (%)43.3%
Negative0
Negative (%)0.0%
Memory size20.5 KiB
2024-05-04T08:11:40.141259image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median1
Q34
95-th percentile18
Maximum2914
Range2914
Interquartile range (IQR)4

Descriptive statistics

Standard deviation78.151523
Coefficient of variation (CV)10.950867
Kurtosis1059.8129
Mean7.1365601
Median Absolute Deviation (MAD)1
Skewness31.295504
Sum16514
Variance6107.6605
MonotonicityNot monotonic
2024-05-04T08:11:40.589014image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 1003
43.3%
1 321
 
13.9%
2 205
 
8.9%
3 139
 
6.0%
5 96
 
4.1%
4 94
 
4.1%
6 79
 
3.4%
8 46
 
2.0%
7 44
 
1.9%
9 36
 
1.6%
Other values (62) 251
 
10.8%
ValueCountFrequency (%)
0 1003
43.3%
1 321
 
13.9%
2 205
 
8.9%
3 139
 
6.0%
4 94
 
4.1%
5 96
 
4.1%
6 79
 
3.4%
7 44
 
1.9%
8 46
 
2.0%
9 36
 
1.6%
ValueCountFrequency (%)
2914 1
< 0.1%
2111 1
< 0.1%
826 1
< 0.1%
312 2
0.1%
240 1
< 0.1%
180 1
< 0.1%
172 1
< 0.1%
168 1
< 0.1%
167 1
< 0.1%
134 1
< 0.1%

전기승용자동차보유대수
Real number (ℝ)

SKEWED  ZEROS 

Distinct57
Distinct (%)2.5%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean3.3336214
Minimum0
Maximum1753
Zeros2104
Zeros (%)90.9%
Negative0
Negative (%)0.0%
Memory size20.5 KiB
2024-05-04T08:11:41.018708image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile7.35
Maximum1753
Range1753
Interquartile range (IQR)0

Descriptive statistics

Standard deviation46.637245
Coefficient of variation (CV)13.989964
Kurtosis1072.7951
Mean3.3336214
Median Absolute Deviation (MAD)0
Skewness31.262021
Sum7714
Variance2175.0326
MonotonicityNot monotonic
2024-05-04T08:11:41.627678image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 2104
90.9%
1 33
 
1.4%
2 24
 
1.0%
5 13
 
0.6%
6 10
 
0.4%
3 8
 
0.3%
11 8
 
0.3%
9 7
 
0.3%
12 6
 
0.3%
24 6
 
0.3%
Other values (47) 95
 
4.1%
ValueCountFrequency (%)
0 2104
90.9%
1 33
 
1.4%
2 24
 
1.0%
3 8
 
0.3%
4 3
 
0.1%
5 13
 
0.6%
6 10
 
0.4%
7 3
 
0.1%
8 4
 
0.2%
9 7
 
0.3%
ValueCountFrequency (%)
1753 1
< 0.1%
1242 1
< 0.1%
285 1
< 0.1%
229 1
< 0.1%
216 2
0.1%
193 1
< 0.1%
120 1
< 0.1%
119 1
< 0.1%
108 2
0.1%
106 1
< 0.1%

전기승합자동차보유대수
Categorical

IMBALANCE 

Distinct2
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size18.2 KiB
0
2313 
10
 
1

Length

Max length2
Median length1
Mean length1.0004322
Min length1

Unique

Unique1 ?
Unique (%)< 0.1%

Sample

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

Common Values

ValueCountFrequency (%)
0 2313
> 99.9%
10 1
 
< 0.1%

Length

2024-05-04T08:11:42.084751image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-04T08:11:42.368996image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 2313
> 99.9%
10 1
 
< 0.1%

경차요금
Real number (ℝ)

MISSING  ZEROS 

Distinct28
Distinct (%)8.8%
Missing1994
Missing (%)86.2%
Infinite0
Infinite (%)0.0%
Mean41894.281
Minimum0
Maximum380000
Zeros83
Zeros (%)3.6%
Negative0
Negative (%)0.0%
Memory size20.5 KiB
2024-05-04T08:11:42.743659image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median50000
Q360000
95-th percentile95000
Maximum380000
Range380000
Interquartile range (IQR)60000

Descriptive statistics

Standard deviation35120.546
Coefficient of variation (CV)0.83831361
Kurtosis26.513306
Mean41894.281
Median Absolute Deviation (MAD)10000
Skewness2.8740271
Sum13406170
Variance1.2334528 × 109
MonotonicityNot monotonic
2024-05-04T08:11:43.300772image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=28)
ValueCountFrequency (%)
50000 119
 
5.1%
0 83
 
3.6%
60000 54
 
2.3%
40000 11
 
0.5%
95000 6
 
0.3%
105000 5
 
0.2%
70000 4
 
0.2%
100000 4
 
0.2%
6 4
 
0.2%
53000 4
 
0.2%
Other values (18) 26
 
1.1%
(Missing) 1994
86.2%
ValueCountFrequency (%)
0 83
3.6%
5 2
 
0.1%
6 4
 
0.2%
8 2
 
0.1%
5000 1
 
< 0.1%
35000 1
 
< 0.1%
40000 11
 
0.5%
44410 2
 
0.1%
45000 1
 
< 0.1%
50000 119
5.1%
ValueCountFrequency (%)
380000 1
 
< 0.1%
190000 1
 
< 0.1%
120000 1
 
< 0.1%
105000 5
0.2%
104500 1
 
< 0.1%
100000 4
0.2%
95000 6
0.3%
80000 1
 
< 0.1%
74000 1
 
< 0.1%
70000 4
0.2%

소형차요금
Real number (ℝ)

MISSING  ZEROS 

Distinct29
Distinct (%)8.6%
Missing1975
Missing (%)85.4%
Infinite0
Infinite (%)0.0%
Mean54466.077
Minimum0
Maximum570000
Zeros79
Zeros (%)3.4%
Negative0
Negative (%)0.0%
Memory size20.5 KiB
2024-05-04T08:11:43.833087image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q150000
median60000
Q370000
95-th percentile108200
Maximum570000
Range570000
Interquartile range (IQR)20000

Descriptive statistics

Standard deviation43996.616
Coefficient of variation (CV)0.80778016
Kurtosis55.220359
Mean54466.077
Median Absolute Deviation (MAD)10000
Skewness4.731172
Sum18464000
Variance1.9357022 × 109
MonotonicityNot monotonic
2024-05-04T08:11:44.254648image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=29)
ValueCountFrequency (%)
60000 118
 
5.1%
0 79
 
3.4%
70000 71
 
3.1%
80000 15
 
0.6%
50000 13
 
0.6%
121000 5
 
0.2%
56000 4
 
0.2%
71500 4
 
0.2%
100000 3
 
0.1%
120000 2
 
0.1%
Other values (19) 25
 
1.1%
(Missing) 1975
85.4%
ValueCountFrequency (%)
0 79
3.4%
11000 1
 
< 0.1%
50000 13
 
0.6%
56000 4
 
0.2%
57000 2
 
0.1%
60000 118
5.1%
65000 1
 
< 0.1%
67000 2
 
0.1%
70000 71
3.1%
71500 4
 
0.2%
ValueCountFrequency (%)
570000 1
 
< 0.1%
210000 1
 
< 0.1%
163000 1
 
< 0.1%
147000 2
 
0.1%
130000 1
 
< 0.1%
125000 1
 
< 0.1%
121000 5
0.2%
120000 2
 
0.1%
115000 1
 
< 0.1%
110000 2
 
0.1%

중형차요금
Categorical

IMBALANCE 

Distinct38
Distinct (%)1.6%
Missing0
Missing (%)0.0%
Memory size18.2 KiB
<NA>
1950 
70000
 
115
0
 
79
80000
 
69
90000
 
23
Other values (33)
 
78

Length

Max length6
Median length4
Mean length4.0475367
Min length1

Unique

Unique17 ?
Unique (%)0.7%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 1950
84.3%
70000 115
 
5.0%
0 79
 
3.4%
80000 69
 
3.0%
90000 23
 
1.0%
100000 19
 
0.8%
60000 5
 
0.2%
84000 4
 
0.2%
170000 4
 
0.2%
160000 3
 
0.1%
Other values (28) 43
 
1.9%

Length

2024-05-04T08:11:44.744961image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
na 1950
84.3%
70000 116
 
5.0%
0 79
 
3.4%
80000 70
 
3.0%
90000 23
 
1.0%
100000 19
 
0.8%
60000 5
 
0.2%
84000 4
 
0.2%
170000 4
 
0.2%
160000 3
 
0.1%
Other values (26) 41
 
1.8%

대형차요금
Real number (ℝ)

MISSING  ZEROS 

Distinct37
Distinct (%)10.6%
Missing1966
Missing (%)85.0%
Infinite0
Infinite (%)0.0%
Mean106967.84
Minimum0
Maximum820000
Zeros81
Zeros (%)3.5%
Negative0
Negative (%)0.0%
Memory size20.5 KiB
2024-05-04T08:11:45.399428image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q190000
median100000
Q3130000
95-th percentile285000
Maximum820000
Range820000
Interquartile range (IQR)40000

Descriptive statistics

Standard deviation89685.115
Coefficient of variation (CV)0.83843061
Kurtosis12.604349
Mean106967.84
Median Absolute Deviation (MAD)30000
Skewness2.2398221
Sum37224810
Variance8.0434199 × 109
MonotonicityNot monotonic
2024-05-04T08:11:45.840256image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=37)
ValueCountFrequency (%)
100000 114
 
4.9%
0 81
 
3.5%
120000 33
 
1.4%
130000 32
 
1.4%
150000 23
 
1.0%
110000 8
 
0.3%
90000 5
 
0.2%
300000 5
 
0.2%
170000 4
 
0.2%
80000 4
 
0.2%
Other values (27) 39
 
1.7%
(Missing) 1966
85.0%
ValueCountFrequency (%)
0 81
3.5%
80000 4
 
0.2%
90000 5
 
0.2%
100000 114
4.9%
110000 8
 
0.3%
120000 33
 
1.4%
130000 32
 
1.4%
140000 4
 
0.2%
150000 23
 
1.0%
155000 1
 
< 0.1%
ValueCountFrequency (%)
820000 1
 
< 0.1%
460000 1
 
< 0.1%
450000 1
 
< 0.1%
439000 1
 
< 0.1%
399000 1
 
< 0.1%
340000 1
 
< 0.1%
320000 2
 
0.1%
310000 2
 
0.1%
300000 5
0.2%
299000 2
 
0.1%

승합차요금
Real number (ℝ)

MISSING  ZEROS 

Distinct40
Distinct (%)11.5%
Missing1967
Missing (%)85.0%
Infinite0
Infinite (%)0.0%
Mean102738.53
Minimum0
Maximum900000
Zeros79
Zeros (%)3.4%
Negative0
Negative (%)0.0%
Memory size20.5 KiB
2024-05-04T08:11:46.319488image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q1913
median120000
Q3141500
95-th percentile200000
Maximum900000
Range900000
Interquartile range (IQR)140587

Descriptive statistics

Standard deviation78986.344
Coefficient of variation (CV)0.76880934
Kurtosis28.857653
Mean102738.53
Median Absolute Deviation (MAD)30000
Skewness2.7765881
Sum35650271
Variance6.2388425 × 109
MonotonicityNot monotonic
2024-05-04T08:11:46.757145image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=40)
ValueCountFrequency (%)
120000 120
 
5.2%
0 79
 
3.4%
150000 53
 
2.3%
100000 16
 
0.7%
130000 13
 
0.6%
110000 8
 
0.3%
160000 5
 
0.2%
220000 5
 
0.2%
95000 4
 
0.2%
250000 3
 
0.1%
Other values (30) 41
 
1.8%
(Missing) 1967
85.0%
ValueCountFrequency (%)
0 79
3.4%
10 2
 
0.1%
12 2
 
0.1%
13 2
 
0.1%
15 2
 
0.1%
1811 1
 
< 0.1%
10000 1
 
< 0.1%
12000 1
 
< 0.1%
80000 1
 
< 0.1%
85180 2
 
0.1%
ValueCountFrequency (%)
900000 1
 
< 0.1%
290000 1
 
< 0.1%
280000 1
 
< 0.1%
270000 1
 
< 0.1%
257000 1
 
< 0.1%
250000 3
0.1%
242000 1
 
< 0.1%
240000 1
 
< 0.1%
236000 2
 
0.1%
220000 5
0.2%

레저용차요금
Real number (ℝ)

MISSING  ZEROS 

Distinct18
Distinct (%)8.5%
Missing2102
Missing (%)90.8%
Infinite0
Infinite (%)0.0%
Mean123098.4
Minimum0
Maximum500000
Zeros96
Zeros (%)4.1%
Negative0
Negative (%)0.0%
Memory size20.5 KiB
2024-05-04T08:11:47.268615image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median130000
Q3300000
95-th percentile300000
Maximum500000
Range500000
Interquartile range (IQR)300000

Descriptive statistics

Standard deviation127724.65
Coefficient of variation (CV)1.0375818
Kurtosis-1.2628635
Mean123098.4
Median Absolute Deviation (MAD)130000
Skewness0.43396279
Sum26096860
Variance1.6313587 × 1010
MonotonicityNot monotonic
2024-05-04T08:11:47.852525image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=18)
ValueCountFrequency (%)
0 96
 
4.1%
300000 55
 
2.4%
150000 33
 
1.4%
130000 5
 
0.2%
100000 3
 
0.1%
200000 3
 
0.1%
245000 2
 
0.1%
85180 2
 
0.1%
120000 2
 
0.1%
145000 2
 
0.1%
Other values (8) 9
 
0.4%
(Missing) 2102
90.8%
ValueCountFrequency (%)
0 96
4.1%
85180 2
 
0.1%
90000 2
 
0.1%
100000 3
 
0.1%
120000 2
 
0.1%
130000 5
 
0.2%
145000 2
 
0.1%
150000 33
 
1.4%
171500 1
 
< 0.1%
180000 1
 
< 0.1%
ValueCountFrequency (%)
500000 1
 
< 0.1%
300000 55
2.4%
250000 1
 
< 0.1%
245000 2
 
0.1%
240000 1
 
< 0.1%
200000 3
 
0.1%
195000 1
 
< 0.1%
190000 1
 
< 0.1%
180000 1
 
< 0.1%
171500 1
 
< 0.1%

수입차요금
Real number (ℝ)

MISSING  ZEROS 

Distinct21
Distinct (%)9.9%
Missing2101
Missing (%)90.8%
Infinite0
Infinite (%)0.0%
Mean142728.36
Minimum0
Maximum790000
Zeros98
Zeros (%)4.2%
Negative0
Negative (%)0.0%
Memory size20.5 KiB
2024-05-04T08:11:48.419894image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median185000
Q3250000
95-th percentile364000
Maximum790000
Range790000
Interquartile range (IQR)250000

Descriptive statistics

Standard deviation147479.33
Coefficient of variation (CV)1.0332869
Kurtosis0.50340338
Mean142728.36
Median Absolute Deviation (MAD)185000
Skewness0.67572956
Sum30401140
Variance2.1750154 × 1010
MonotonicityNot monotonic
2024-05-04T08:11:48.891111image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=21)
ValueCountFrequency (%)
0 98
 
4.2%
250000 77
 
3.3%
200000 6
 
0.3%
150000 4
 
0.2%
400000 4
 
0.2%
350000 3
 
0.1%
185000 2
 
0.1%
500000 2
 
0.1%
330000 2
 
0.1%
60570 2
 
0.1%
Other values (11) 13
 
0.6%
(Missing) 2101
90.8%
ValueCountFrequency (%)
0 98
4.2%
60570 2
 
0.1%
130000 1
 
< 0.1%
135000 1
 
< 0.1%
150000 4
 
0.2%
185000 2
 
0.1%
200000 6
 
0.3%
220000 2
 
0.1%
230000 1
 
< 0.1%
250000 77
3.3%
ValueCountFrequency (%)
790000 1
 
< 0.1%
580000 1
 
< 0.1%
500000 2
0.1%
450000 2
0.1%
400000 4
0.2%
385000 1
 
< 0.1%
350000 3
0.1%
340000 1
 
< 0.1%
330000 2
0.1%
320000 1
 
< 0.1%
Distinct11
Distinct (%)0.5%
Missing0
Missing (%)0.0%
Memory size18.2 KiB
Minimum2024-05-04 00:00:00
Maximum2024-05-04 19:00:00
2024-05-04T08:11:49.233496image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-04T08:11:49.723406image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=11)
Distinct16
Distinct (%)0.7%
Missing0
Missing (%)0.0%
Memory size18.2 KiB
Minimum2024-05-04 00:00:00
Maximum2024-05-04 23:59:00
2024-05-04T08:11:50.247370image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-04T08:11:50.846352image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=16)
Distinct10
Distinct (%)1.3%
Missing1531
Missing (%)66.2%
Memory size18.2 KiB
Minimum2024-05-04 00:00:00
Maximum2024-05-04 13:00:00
2024-05-04T08:11:51.139690image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-04T08:11:51.765159image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=10)
Distinct17
Distinct (%)2.2%
Missing1532
Missing (%)66.2%
Memory size18.2 KiB
Minimum2024-05-04 00:00:00
Maximum2024-05-04 23:59:00
2024-05-04T08:11:52.256126image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-04T08:11:52.674564image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=17)
Distinct11
Distinct (%)1.5%
Missing1581
Missing (%)68.3%
Memory size18.2 KiB
Minimum2024-05-04 00:00:00
Maximum2024-05-04 18:00:00
2024-05-04T08:11:53.005927image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-04T08:11:53.456378image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=11)
Distinct15
Distinct (%)2.0%
Missing1581
Missing (%)68.3%
Memory size18.2 KiB
Minimum2024-05-04 00:00:00
Maximum2024-05-04 23:59:00
2024-05-04T08:11:53.821561image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-04T08:11:54.177659image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=15)

휴무일
Categorical

IMBALANCE 

Distinct26
Distinct (%)1.1%
Missing0
Missing (%)0.0%
Memory size18.2 KiB
<NA>
1886 
연중무휴
265 
명절
 
55
토+일+공휴일
 
20
연중
 
15
Other values (21)
 
73

Length

Max length15
Median length4
Mean length4.0177182
Min length1

Unique

Unique8 ?
Unique (%)0.3%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 1886
81.5%
연중무휴 265
 
11.5%
명절 55
 
2.4%
토+일+공휴일 20
 
0.9%
연중 15
 
0.6%
없음 11
 
0.5%
공휴일 9
 
0.4%
설 당일+추석 당일 6
 
0.3%
토(격주)+일+국가지정공휴일 6
 
0.3%
일요일+공휴일 5
 
0.2%
Other values (16) 36
 
1.6%

Length

2024-05-04T08:11:54.507711image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
na 1886
80.8%
연중무휴 265
 
11.4%
명절 55
 
2.4%
토+일+공휴일 20
 
0.9%
연중 15
 
0.6%
없음 11
 
0.5%
10
 
0.4%
공휴일 9
 
0.4%
당일+추석 6
 
0.3%
당일 6
 
0.3%
Other values (19) 51
 
2.2%

홈페이지주소
Text

MISSING 

Distinct59
Distinct (%)38.3%
Missing2160
Missing (%)93.3%
Memory size18.2 KiB
2024-05-04T08:11:54.965487image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length47
Median length37
Mean length14.363636
Min length2

Characters and Unicode

Total characters2212
Distinct characters47
Distinct categories6 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique43 ?
Unique (%)27.9%

Sample

1st rowhttps://djbest.modoo.at/
2nd rowwww.woosungrentcar.com
3rd rowwww.skcarrental.com
4th rowhttp://www.1rent.co.kr/
5th row없음
ValueCountFrequency (%)
없음 61
39.6%
dysrentcar.com 8
 
5.2%
dyrentacar.co.kr 7
 
4.5%
www.jetcar.co.kr 6
 
3.9%
www.skcarrental.com 4
 
2.6%
http://hanilrent.alltheway.kr 4
 
2.6%
www.socar.kr 3
 
1.9%
http://www.dyrentcar.kr 2
 
1.3%
https://onelentcar.modoo.at 2
 
1.3%
https://hansolnetworks.com 2
 
1.3%
Other values (49) 55
35.7%
2024-05-04T08:11:56.125044image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
t 207
 
9.4%
r 191
 
8.6%
. 189
 
8.5%
w 142
 
6.4%
/ 138
 
6.2%
c 138
 
6.2%
a 137
 
6.2%
o 122
 
5.5%
e 107
 
4.8%
n 106
 
4.8%
Other values (37) 735
33.2%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 1653
74.7%
Other Punctuation 380
 
17.2%
Other Letter 127
 
5.7%
Decimal Number 46
 
2.1%
Dash Punctuation 5
 
0.2%
Connector Punctuation 1
 
< 0.1%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
t 207
12.5%
r 191
11.6%
w 142
 
8.6%
c 138
 
8.3%
a 137
 
8.3%
o 122
 
7.4%
e 107
 
6.5%
n 106
 
6.4%
h 78
 
4.7%
k 62
 
3.8%
Other values (14) 363
22.0%
Decimal Number
ValueCountFrequency (%)
1 7
15.2%
5 7
15.2%
2 5
10.9%
6 5
10.9%
4 4
8.7%
7 4
8.7%
8 4
8.7%
0 4
8.7%
9 4
8.7%
3 2
 
4.3%
Other Letter
ValueCountFrequency (%)
61
48.0%
61
48.0%
1
 
0.8%
1
 
0.8%
1
 
0.8%
1
 
0.8%
1
 
0.8%
Other Punctuation
ValueCountFrequency (%)
. 189
49.7%
/ 138
36.3%
: 52
 
13.7%
? 1
 
0.3%
Dash Punctuation
ValueCountFrequency (%)
- 5
100.0%
Connector Punctuation
ValueCountFrequency (%)
_ 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 1653
74.7%
Common 432
 
19.5%
Hangul 127
 
5.7%

Most frequent character per script

Latin
ValueCountFrequency (%)
t 207
12.5%
r 191
11.6%
w 142
 
8.6%
c 138
 
8.3%
a 137
 
8.3%
o 122
 
7.4%
e 107
 
6.5%
n 106
 
6.4%
h 78
 
4.7%
k 62
 
3.8%
Other values (14) 363
22.0%
Common
ValueCountFrequency (%)
. 189
43.8%
/ 138
31.9%
: 52
 
12.0%
1 7
 
1.6%
5 7
 
1.6%
- 5
 
1.2%
2 5
 
1.2%
6 5
 
1.2%
4 4
 
0.9%
7 4
 
0.9%
Other values (6) 16
 
3.7%
Hangul
ValueCountFrequency (%)
61
48.0%
61
48.0%
1
 
0.8%
1
 
0.8%
1
 
0.8%
1
 
0.8%
1
 
0.8%

Most occurring blocks

ValueCountFrequency (%)
ASCII 2085
94.3%
Hangul 127
 
5.7%

Most frequent character per block

ASCII
ValueCountFrequency (%)
t 207
 
9.9%
r 191
 
9.2%
. 189
 
9.1%
w 142
 
6.8%
/ 138
 
6.6%
c 138
 
6.6%
a 137
 
6.6%
o 122
 
5.9%
e 107
 
5.1%
n 106
 
5.1%
Other values (30) 608
29.2%
Hangul
ValueCountFrequency (%)
61
48.0%
61
48.0%
1
 
0.8%
1
 
0.8%
1
 
0.8%
1
 
0.8%
1
 
0.8%

대표자명
Text

MISSING 

Distinct727
Distinct (%)61.5%
Missing1131
Missing (%)48.9%
Memory size18.2 KiB
2024-05-04T08:11:56.937367image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length11
Median length3
Mean length3.103973
Min length2

Characters and Unicode

Total characters3672
Distinct characters201
Distinct categories5 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique516 ?
Unique (%)43.6%

Sample

1st row김성환
2nd row김성환
3rd row김성환
4th row김효순
5th row김효순
ValueCountFrequency (%)
표현명 17
 
1.4%
홍성희 13
 
1.1%
박재욱 12
 
1.0%
소옥자 12
 
1.0%
김경수 11
 
0.9%
이재웅 10
 
0.8%
조석호 10
 
0.8%
최은주 9
 
0.8%
구순희 9
 
0.8%
김원길 8
 
0.7%
Other values (724) 1083
90.7%
2024-05-04T08:11:58.266258image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
255
 
6.9%
137
 
3.7%
109
 
3.0%
106
 
2.9%
93
 
2.5%
84
 
2.3%
81
 
2.2%
75
 
2.0%
64
 
1.7%
63
 
1.7%
Other values (191) 2605
70.9%

Most occurring categories

ValueCountFrequency (%)
Other Letter 3635
99.0%
Math Symbol 21
 
0.6%
Space Separator 11
 
0.3%
Decimal Number 3
 
0.1%
Other Punctuation 2
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
255
 
7.0%
137
 
3.8%
109
 
3.0%
106
 
2.9%
93
 
2.6%
84
 
2.3%
81
 
2.2%
75
 
2.1%
64
 
1.8%
63
 
1.7%
Other values (186) 2568
70.6%
Decimal Number
ValueCountFrequency (%)
1 2
66.7%
2 1
33.3%
Math Symbol
ValueCountFrequency (%)
+ 21
100.0%
Space Separator
ValueCountFrequency (%)
11
100.0%
Other Punctuation
ValueCountFrequency (%)
, 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 3635
99.0%
Common 37
 
1.0%

Most frequent character per script

Hangul
ValueCountFrequency (%)
255
 
7.0%
137
 
3.8%
109
 
3.0%
106
 
2.9%
93
 
2.6%
84
 
2.3%
81
 
2.2%
75
 
2.1%
64
 
1.8%
63
 
1.7%
Other values (186) 2568
70.6%
Common
ValueCountFrequency (%)
+ 21
56.8%
11
29.7%
1 2
 
5.4%
, 2
 
5.4%
2 1
 
2.7%

Most occurring blocks

ValueCountFrequency (%)
Hangul 3635
99.0%
ASCII 37
 
1.0%

Most frequent character per block

Hangul
ValueCountFrequency (%)
255
 
7.0%
137
 
3.8%
109
 
3.0%
106
 
2.9%
93
 
2.6%
84
 
2.3%
81
 
2.2%
75
 
2.1%
64
 
1.8%
63
 
1.7%
Other values (186) 2568
70.6%
ASCII
ValueCountFrequency (%)
+ 21
56.8%
11
29.7%
1 2
 
5.4%
, 2
 
5.4%
2 1
 
2.7%
Distinct1564
Distinct (%)67.6%
Missing0
Missing (%)0.0%
Memory size18.2 KiB
2024-05-04T08:11:59.335055image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length13
Median length12
Mean length11.8414
Min length9

Characters and Unicode

Total characters27401
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

Unique1208 ?
Unique (%)52.2%

Sample

1st row042-226-7770
2nd row042-226-7770
3rd row042-226-7770
4th row042-610-0014
5th row042-610-0014
ValueCountFrequency (%)
000-0000-0000 68
 
2.9%
1833-2816 22
 
1.0%
02-3461-1437 19
 
0.8%
02-590-7264 18
 
0.8%
02-599-0333 15
 
0.6%
080-2000-3000 15
 
0.6%
1661-3315 13
 
0.6%
02-2241-8278 11
 
0.5%
070-4352-2110 11
 
0.5%
041-853-1527 11
 
0.5%
Other values (1554) 2111
91.2%
2024-05-04T08:12:00.671507image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 5168
18.9%
- 4487
16.4%
3 2582
9.4%
2 2422
8.8%
5 2254
8.2%
1 2250
8.2%
4 2169
7.9%
6 1839
 
6.7%
7 1645
 
6.0%
8 1516
 
5.5%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 22914
83.6%
Dash Punctuation 4487
 
16.4%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 5168
22.6%
3 2582
11.3%
2 2422
10.6%
5 2254
9.8%
1 2250
9.8%
4 2169
9.5%
6 1839
 
8.0%
7 1645
 
7.2%
8 1516
 
6.6%
9 1069
 
4.7%
Dash Punctuation
ValueCountFrequency (%)
- 4487
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 27401
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 5168
18.9%
- 4487
16.4%
3 2582
9.4%
2 2422
8.8%
5 2254
8.2%
1 2250
8.2%
4 2169
7.9%
6 1839
 
6.7%
7 1645
 
6.0%
8 1516
 
5.5%

Most occurring blocks

ValueCountFrequency (%)
ASCII 27401
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 5168
18.9%
- 4487
16.4%
3 2582
9.4%
2 2422
8.8%
5 2254
8.2%
1 2250
8.2%
4 2169
7.9%
6 1839
 
6.7%
7 1645
 
6.0%
8 1516
 
5.5%
Distinct124
Distinct (%)5.4%
Missing0
Missing (%)0.0%
Memory size18.2 KiB
Minimum2020-01-29 00:00:00
Maximum2024-03-11 00:00:00
2024-05-04T08:12:01.145618image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-04T08:12:01.656997image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

제공기관코드
Real number (ℝ)

Distinct197
Distinct (%)8.5%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean4653081.9
Minimum3000000
Maximum6500000
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size20.5 KiB
2024-05-04T08:12:02.143888image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum3000000
5-th percentile3150000
Q13900000
median4480000
Q35530000
95-th percentile6310000
Maximum6500000
Range3500000
Interquartile range (IQR)1630000

Descriptive statistics

Standard deviation1078763.1
Coefficient of variation (CV)0.2318384
Kurtosis-1.0957065
Mean4653081.9
Median Absolute Deviation (MAD)850000
Skewness0.2879006
Sum1.0767232 × 1010
Variance1.1637298 × 1012
MonotonicityNot monotonic
2024-05-04T08:12:02.596235image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
6300000 176
 
7.6%
6500000 112
 
4.8%
3210000 103
 
4.5%
6310000 55
 
2.4%
6270000 55
 
2.4%
3940000 48
 
2.1%
4200000 44
 
1.9%
4020000 43
 
1.9%
6260000 43
 
1.9%
4201000 43
 
1.9%
Other values (187) 1592
68.8%
ValueCountFrequency (%)
3000000 5
 
0.2%
3010000 11
0.5%
3020000 15
0.6%
3030000 22
1.0%
3040000 14
0.6%
3050000 6
 
0.3%
3060000 5
 
0.2%
3070000 1
 
< 0.1%
3090000 3
 
0.1%
3100000 7
 
0.3%
ValueCountFrequency (%)
6500000 112
4.8%
6310000 55
 
2.4%
6300000 176
7.6%
6270000 55
 
2.4%
6260000 43
 
1.9%
5710000 36
 
1.6%
5700000 2
 
0.1%
5690000 17
 
0.7%
5680000 15
 
0.6%
5670000 32
 
1.4%
Distinct197
Distinct (%)8.5%
Missing0
Missing (%)0.0%
Memory size18.2 KiB
2024-05-04T08:12:03.629284image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length11
Median length10
Mean length7.7104581
Min length5

Characters and Unicode

Total characters17842
Distinct characters124
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

Unique20 ?
Unique (%)0.9%

Sample

1st row대전광역시
2nd row대전광역시
3rd row대전광역시
4th row대전광역시
5th row대전광역시
ValueCountFrequency (%)
경기도 429
 
10.3%
서울특별시 355
 
8.5%
대전광역시 176
 
4.2%
경상북도 152
 
3.6%
경상남도 132
 
3.2%
강원도 127
 
3.0%
충청남도 120
 
2.9%
강원특별자치도 114
 
2.7%
제주특별자치도 112
 
2.7%
전라남도 112
 
2.7%
Other values (172) 2341
56.1%
2024-05-04T08:12:05.360558image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1940
 
10.9%
1856
 
10.4%
1496
 
8.4%
747
 
4.2%
647
 
3.6%
647
 
3.6%
608
 
3.4%
570
 
3.2%
541
 
3.0%
482
 
2.7%
Other values (114) 8308
46.6%

Most occurring categories

ValueCountFrequency (%)
Other Letter 15986
89.6%
Space Separator 1856
 
10.4%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
1940
 
12.1%
1496
 
9.4%
747
 
4.7%
647
 
4.0%
647
 
4.0%
608
 
3.8%
570
 
3.6%
541
 
3.4%
482
 
3.0%
459
 
2.9%
Other values (113) 7849
49.1%
Space Separator
ValueCountFrequency (%)
1856
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 15986
89.6%
Common 1856
 
10.4%

Most frequent character per script

Hangul
ValueCountFrequency (%)
1940
 
12.1%
1496
 
9.4%
747
 
4.7%
647
 
4.0%
647
 
4.0%
608
 
3.8%
570
 
3.6%
541
 
3.4%
482
 
3.0%
459
 
2.9%
Other values (113) 7849
49.1%
Common
ValueCountFrequency (%)
1856
100.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 15986
89.6%
ASCII 1856
 
10.4%

Most frequent character per block

Hangul
ValueCountFrequency (%)
1940
 
12.1%
1496
 
9.4%
747
 
4.7%
647
 
4.0%
647
 
4.0%
608
 
3.8%
570
 
3.6%
541
 
3.4%
482
 
3.0%
459
 
2.9%
Other values (113) 7849
49.1%
ASCII
ValueCountFrequency (%)
1856
100.0%

Sample

업체명사업장구분소재지도로명주소소재지지번주소위도경도차고지도로명주소차고지지번주소보유차고지수용능력자동차총보유대수승용차보유대수승합차보유대수전기승용자동차보유대수전기승합자동차보유대수경차요금소형차요금중형차요금대형차요금승합차요금레저용차요금수입차요금평일운영시작시각평일운영종료시각주말운영시작시각주말운영종료시각공휴일운영시작시각공휴일운영종료시각휴무일홈페이지주소대표자명전화번호데이터기준일자제공기관코드제공기관명
0㈜지엠물류주사업장대전광역시 중구 대종로550번길 5, 1306호(선화동, 유원오피스텔)대전광역시 중구 선화동 79-14, 유원오피스텔 1306호36.332571127.421647대전광역시 대덕구 한남로114번길 1대전광역시 대덕구 오정동 448-556.03623412100<NA><NA><NA><NA><NA><NA><NA>09:0018:0009:0018:0009:0018:00<NA><NA>김성환042-226-77702021-07-056300000대전광역시
1㈜지엠물류주사업장대전광역시 중구 대종로550번길 5, 1306호(선화동, 유원오피스텔)대전광역시 중구 선화동 79-14, 유원오피스텔 1306호36.332571127.421647충남 금산군 진산면 만악리 432-5충남 금산군 진산면 만악리 432-5112.000000<NA><NA><NA><NA><NA><NA><NA>09:0018:0009:0018:0009:0018:00<NA><NA>김성환042-226-77702021-07-056300000대전광역시
2㈜지엠물류주사업장대전광역시 중구 대종로550번길 5, 1306호(선화동, 유원오피스텔)대전광역시 중구 선화동 79-14, 유원오피스텔 1306호36.332571127.421647충남 논산시 광석면 천동리 373-1충남 논산시 광석면 천동리 373-1246.000000<NA><NA><NA><NA><NA><NA><NA>09:0018:0009:0018:0009:0018:00<NA><NA>김성환042-226-77702021-07-056300000대전광역시
3누리렌트카㈜주사업장대전광역시 서구 월평로13번길 60, 1층(월평동)대전광역시 서구 월평동 41136.357411127.359417대전광역시 동구 대전천동로 58대전광역시 동구 대성동 173-357.05952700<NA><NA><NA><NA><NA><NA><NA>09:0018:0009:0018:0009:0018:00<NA><NA>김효순042-610-00142021-07-056300000대전광역시
4누리렌트카㈜주사업장대전광역시 서구 월평로13번길 60, 1층(월평동)대전광역시 서구 월평동 41136.357411127.359417대전광역시 서구 신갈마로141번길 14대전광역시 서구 갈마동 377-2131.000000<NA><NA><NA><NA><NA><NA><NA>09:0018:0009:0018:0009:0018:00<NA><NA>김효순042-610-00142021-07-056300000대전광역시
5대경렌트카㈜주사업장대전광역시 서구 계백로 1400, 2층(도마동)대전광역시 서구 도마동 188-736.311493127.37733대전광역시 서구 가수원동 1090대전광역시 서구 가수원동 109078.06262000<NA><NA><NA><NA><NA><NA><NA>09:0018:0009:0018:0009:0018:00<NA><NA>김성태042-586-60612021-07-056300000대전광역시
6㈜대원렌트카주사업장대전광역시 서구 갈마로 146, 2층(괴정동)대전광역시 서구 괴정동 413-8, 2층36.340394127.373354대전광역시 서구 갈마로 146(괴정동)대전광역시 서구 괴정동 413-87.055000<NA><NA><NA><NA><NA><NA><NA>09:0018:0009:0018:0009:0018:00<NA><NA>조정식042-476-33222021-07-056300000대전광역시
7대전렌트카㈜주사업장대전광역시 서구 둔산서로 9, 603호(둔산동, 씨에프프라자)대전광역시 서구 둔산동 1251, 씨에프프라자 603호36.347536127.382606세종특별자치시 부강면 연청로 745-46세종특별자치시 부강면 갈산리 470-273.0153148500<NA><NA><NA><NA><NA><NA><NA>09:0018:0009:0018:0009:0018:00<NA><NA>임완수042-484-31102021-07-056300000대전광역시
8대전렌트카㈜주사업장대전광역시 서구 둔산서로 9, 603호(둔산동, 씨에프프라자)대전광역시 서구 둔산동 1251, 씨에프프라자 603호36.347536127.382606대전광역시 서구 우명동 326-1대전광역시 서구 우명동 326-120.000000<NA><NA><NA><NA><NA><NA><NA>09:0018:0009:0018:0009:0018:00<NA><NA>임완수042-484-31102021-07-056300000대전광역시
9대전렌트카㈜주사업장대전광역시 서구 둔산서로 9, 603호(둔산동, 씨에프프라자)대전광역시 서구 둔산동 1251, 씨에프프라자 603호36.347536127.382606충남 금산군 복수면 다복리 168-4충남 금산군 복수면 다복리 168-450.000000<NA><NA><NA><NA><NA><NA><NA>09:0018:0009:0018:0009:0018:00<NA><NA>임완수042-484-31102021-07-056300000대전광역시
업체명사업장구분소재지도로명주소소재지지번주소위도경도차고지도로명주소차고지지번주소보유차고지수용능력자동차총보유대수승용차보유대수승합차보유대수전기승용자동차보유대수전기승합자동차보유대수경차요금소형차요금중형차요금대형차요금승합차요금레저용차요금수입차요금평일운영시작시각평일운영종료시각주말운영시작시각주말운영종료시각공휴일운영시작시각공휴일운영종료시각휴무일홈페이지주소대표자명전화번호데이터기준일자제공기관코드제공기관명
2304(주)조은렌트카주사업장경상북도 구미시 구미대로 144(사곡동)경상북도 구미시 사곡동 354-1536.09953128.363085경상북도 구미시 구미대로 144(사곡동)+해평면 도리사로 269경상북도 구미시 사곡동 354-15+해평면 송곡리 364-31350.08679700<NA><NA><NA><NA><NA><NA><NA>09:0018:0009:0013:00<NA><NA>공휴일<NA>윤정희054-463-62632023-10-175080000경상북도 구미시
2305(주)수성렌트카주사업장경상북도 구미시 야은로 626경상북도 구미시 지산동 660-10336.128153128.348672경상북도 구미시 비산로 25+화신로4길 15+천생산길 33-6경상북도 구미시 비산동 493-2+광평동 389-2+구평동 40-12707.084741000<NA><NA><NA><NA><NA><NA><NA>09:0019:0009:0019:0009:0019:00<NA><NA>김병한054-464-82622023-10-175080000경상북도 구미시
2306(주)뉴신화렌트카주사업장경상북도 구미시 송정대로10길5경상북도 구미시 송정동 277-436.119269128.356451경상북도 구미시 송정대로10길 5+거양길 231-7경상북도 구미시 송정동 277-4+양호동 809993.06560500<NA><NA><NA><NA><NA><NA><NA>08:3020:0008:3020:0008:3020:00<NA><NA>임은경054-444-81822023-10-175080000경상북도 구미시
2307(주)한화렌트카주사업장경상북도 구미시 송원서로 80 (원평동)경상북도 구미시 원평동 1042-336.124598128.343947경상북도 구미시 산동읍 옥계2공단로 642+송원서로78경상북도 구미시 산동읍 성수리 146+원평동 1042-46688.06362100<NA><NA><NA><NA><NA><NA><NA>09:0020:0009:0020:00<NA><NA>일+공휴일<NA>한인석054-457-20022023-10-175080000경상북도 구미시
2308㈜용인렌트카주사업장경상북도 구미시 야은로 276경상북도 구미시 봉곡동 48-836.139087128.313179<NA>경상북도 구미시 봉곡동 48-122023.0140136400<NA><NA><NA><NA><NA><NA><NA>09:0023:0009:0023:0009:0023:00<NA><NA>백선미054-457-19112023-10-175080000경상북도 구미시
2309브이아이피렌트카㈜주사업장경상북도 구미시 야은로 713(원평동)경상북도 구미시 원평동 560-136.126042128.35792<NA>경상북도 구미시 도개면 신곡리54+고아읍 문성리 163-231169.160501000<NA><NA><NA><NA><NA><NA><NA>08:3021:0008:3021:0008:3021:00<NA><NA>홍현표054-456-00442023-10-175080000경상북도 구미시
2310에스디렌터카주사업장전라북도 익산시 익산대로 433(신동)전라북도 익산시 신동 401-335.964638126.953093전라북도 익산시 황등면 후정길 68전라북도 익산시 황등면 율촌리 804-172.05852600600007500090000140000<NA><NA><NA>09:0018:00<NA><NA><NA><NA>토+일+공휴일<NA>김수정063-0858-44382024-01-094680000전라북도 익산시
2311아이엠에스원(주)주사업장서울특별시 광진구 아차산로 355, 305호-307호 (자양동, 타워더모스트광진아크로텔)<NA>37.537368127.082566서울특별시 영등포구 국제금융로2길 37 에스트레뉴 주차장<NA><NA>3535000<NA><NA><NA><NA><NA><NA><NA>00:0023:59<NA><NA><NA><NA><NA><NA><NA>02-557-87522024-02-133040000서울특별시 광진구
2312(주)솔렌터카주사업장서울특별시 광진구 아차산로 355,207호 (타워더모스트 광진아크로텔)<NA>37.537368127.082566서울특별시 서초구 매헌로 16서울특별시 양천구 신월동 21-1<NA>33000<NA><NA><NA><NA><NA><NA><NA>00:0023:59<NA><NA><NA><NA><NA><NA><NA>1599-19402024-02-133040000서울특별시 광진구
2313(주)조렌트카주사업장서울특별시 광진구 천호대로136길 7 (구의동)<NA>37.548902127.091686서울특별시 강서구 마곡서로 157<NA><NA>9999000<NA><NA><NA><NA><NA><NA><NA>00:0023:59<NA><NA><NA><NA><NA><NA><NA>02-458-93142024-02-133040000서울특별시 광진구