Overview

Dataset statistics

Number of variables18
Number of observations231
Missing cells1361
Missing cells (%)32.7%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory34.4 KiB
Average record size in memory152.6 B

Variable types

Text3
Categorical4
Unsupported3
Numeric3
DateTime5

Dataset

Description전라남도 여수시 자동차정비업체현황
Author전라남도 여수시
URLhttps://www.data.go.kr/data/15025100/fileData.do

Alerts

관리기관명 has constant value ""Constant
관리기관전화번호 has constant value ""Constant
데이터기준일자 has constant value ""Constant
위도 is highly overall correlated with 경도High correlation
경도 is highly overall correlated with 위도High correlation
자동차정비업체종류 is highly imbalanced (54.5%)Imbalance
영업상태 is highly imbalanced (96.0%)Imbalance
소재지지번주소 has 231 (100.0%) missing valuesMissing
위도 has 5 (2.2%) missing valuesMissing
경도 has 5 (2.2%) missing valuesMissing
폐업일자 has 227 (98.3%) missing valuesMissing
휴업시작일자 has 231 (100.0%) missing valuesMissing
휴업종료일자 has 231 (100.0%) missing valuesMissing
운영시작시각 has 206 (89.2%) missing valuesMissing
운영종료시각 has 206 (89.2%) missing valuesMissing
전화번호 has 19 (8.2%) missing valuesMissing
소재지지번주소 is an unsupported type, check if it needs cleaning or further analysisUnsupported
휴업시작일자 is an unsupported type, check if it needs cleaning or further analysisUnsupported
휴업종료일자 is an unsupported type, check if it needs cleaning or further analysisUnsupported

Reproduction

Analysis started2023-12-12 21:36:11.222657
Analysis finished2023-12-12 21:36:12.892140
Duration1.67 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

자동차정비업체명
Text

Distinct230
Distinct (%)99.6%
Missing0
Missing (%)0.0%
Memory size1.9 KiB
2023-12-13T06:36:13.117208image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length18
Median length15
Mean length9.7445887
Min length4

Characters and Unicode

Total characters2251
Distinct characters222
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

Unique229 ?
Unique (%)99.1%

Sample

1st row중앙부분정비공업사
2nd row(유)동성자동차공업사
3rd row(유)신여천자동차공업사
4th row(주)동양교통 자가정비업
5th row엑스포정비서비스
ValueCountFrequency (%)
부분정비공업사 36
 
10.7%
현대자동차 7
 
2.1%
오토오아시스 6
 
1.8%
애니카랜드 4
 
1.2%
한국타이어 3
 
0.9%
쌍용자동차 3
 
0.9%
기아오토 3
 
0.9%
큐 3
 
0.9%
타이어프로 3
 
0.9%
중앙부분정비공업사 2
 
0.6%
Other values (251) 267
79.2%
2023-12-13T06:36:13.516286image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
비 133
 
5.9%
사 122
 
5.4%
공 118
 
5.2%
업 117
 
5.2%
정 112
 
5.0%
106
 
4.7%
부 95
 
4.2%
동 95
 
4.2%
분 86
 
3.8%
자 85
 
3.8%
Other values (212) 1182
52.5%

Most occurring categories

ValueCountFrequency (%)
Other Letter 2075
92.2%
Space Separator 106
 
4.7%
Open Punctuation 20
 
0.9%
Close Punctuation 20
 
0.9%
Uppercase Letter 18
 
0.8%
Decimal Number 9
 
0.4%
Other Punctuation 2
 
0.1%
Dash Punctuation 1
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
비 133
 
6.4%
사 122
 
5.9%
공 118
 
5.7%
업 117
 
5.6%
정 112
 
5.4%
부 95
 
4.6%
동 95
 
4.6%
분 86
 
4.1%
자 85
 
4.1%
차 85
 
4.1%
Other values (192) 1027
49.5%
Uppercase Letter
ValueCountFrequency (%)
S 5
27.8%
M 3
16.7%
T 2
 
11.1%
B 2
 
11.1%
D 1
 
5.6%
X 1
 
5.6%
A 1
 
5.6%
L 1
 
5.6%
C 1
 
5.6%
V 1
 
5.6%
Decimal Number
ValueCountFrequency (%)
2 3
33.3%
1 3
33.3%
3 1
 
11.1%
5 1
 
11.1%
6 1
 
11.1%
Space Separator
ValueCountFrequency (%)
106
100.0%
Open Punctuation
ValueCountFrequency (%)
( 20
100.0%
Close Punctuation
ValueCountFrequency (%)
) 20
100.0%
Other Punctuation
ValueCountFrequency (%)
. 2
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 2075
92.2%
Common 158
 
7.0%
Latin 18
 
0.8%

Most frequent character per script

Hangul
ValueCountFrequency (%)
비 133
 
6.4%
사 122
 
5.9%
공 118
 
5.7%
업 117
 
5.6%
정 112
 
5.4%
부 95
 
4.6%
동 95
 
4.6%
분 86
 
4.1%
자 85
 
4.1%
차 85
 
4.1%
Other values (192) 1027
49.5%
Common
ValueCountFrequency (%)
106
67.1%
( 20
 
12.7%
) 20
 
12.7%
2 3
 
1.9%
1 3
 
1.9%
. 2
 
1.3%
3 1
 
0.6%
5 1
 
0.6%
6 1
 
0.6%
- 1
 
0.6%
Latin
ValueCountFrequency (%)
S 5
27.8%
M 3
16.7%
T 2
 
11.1%
B 2
 
11.1%
D 1
 
5.6%
X 1
 
5.6%
A 1
 
5.6%
L 1
 
5.6%
C 1
 
5.6%
V 1
 
5.6%

Most occurring blocks

ValueCountFrequency (%)
Hangul 2075
92.2%
ASCII 176
 
7.8%

Most frequent character per block

Hangul
ValueCountFrequency (%)
비 133
 
6.4%
사 122
 
5.9%
공 118
 
5.7%
업 117
 
5.6%
정 112
 
5.4%
부 95
 
4.6%
동 95
 
4.6%
분 86
 
4.1%
자 85
 
4.1%
차 85
 
4.1%
Other values (192) 1027
49.5%
ASCII
ValueCountFrequency (%)
106
60.2%
( 20
 
11.4%
) 20
 
11.4%
S 5
 
2.8%
M 3
 
1.7%
2 3
 
1.7%
1 3
 
1.7%
T 2
 
1.1%
B 2
 
1.1%
. 2
 
1.1%
Other values (10) 10
 
5.7%

자동차정비업체종류
Categorical

IMBALANCE 

Distinct4
Distinct (%)1.7%
Missing0
Missing (%)0.0%
Memory size1.9 KiB
3
187 
1
27 
2
 
16
4
 
1

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique1 ?
Unique (%)0.4%

Sample

1st row3
2nd row1
3rd row1
4th row1
5th row1

Common Values

ValueCountFrequency (%)
3 187
81.0%
1 27
 
11.7%
2 16
 
6.9%
4 1
 
0.4%

Length

2023-12-13T06:36:13.643566image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T06:36:13.738565image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
3 187
81.0%
1 27
 
11.7%
2 16
 
6.9%
4 1
 
0.4%

소재지도로명주소
Text

Distinct228
Distinct (%)98.7%
Missing0
Missing (%)0.0%
Memory size1.9 KiB
2023-12-13T06:36:13.985245image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length40
Median length36
Mean length21.047619
Min length15

Characters and Unicode

Total characters4862
Distinct characters116
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

Unique225 ?
Unique (%)97.4%

Sample

1st row전라남도 여수시 좌수영로 101(연등동)
2nd row전라남도 여수시 연등8길 23(연등동)
3rd row전라남도 여수시 여수산단로 327(평여동)
4th row전라남도 여수시 좌수영로 422(미평동)
5th row전라남도 여수시 망마로 58, 306동 1층 04호(신기동, 부영아파트)
ValueCountFrequency (%)
전라남도 231
23.8%
여수시 231
23.8%
좌수영로 37
 
3.8%
만성로 11
 
1.1%
쌍봉로 10
 
1.0%
여수산단로 9
 
0.9%
돌산읍 7
 
0.7%
소라면 6
 
0.6%
성산로 6
 
0.6%
율촌면 5
 
0.5%
Other values (337) 419
43.1%
2023-12-13T06:36:14.441680image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
741
 
15.2%
수 293
 
6.0%
여 270
 
5.6%
시 244
 
5.0%
남 243
 
5.0%
도 238
 
4.9%
라 237
 
4.9%
전 231
 
4.8%
동 181
 
3.7%
1 171
 
3.5%
Other values (106) 2013
41.4%

Most occurring categories

ValueCountFrequency (%)
Other Letter 2959
60.9%
Decimal Number 747
 
15.4%
Space Separator 741
 
15.2%
Open Punctuation 165
 
3.4%
Close Punctuation 165
 
3.4%
Dash Punctuation 61
 
1.3%
Other Punctuation 24
 
0.5%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
수 293
 
9.9%
여 270
 
9.1%
시 244
 
8.2%
남 243
 
8.2%
도 238
 
8.0%
라 237
 
8.0%
전 231
 
7.8%
동 181
 
6.1%
로 158
 
5.3%
길 72
 
2.4%
Other values (91) 792
26.8%
Decimal Number
ValueCountFrequency (%)
1 171
22.9%
2 98
13.1%
4 83
11.1%
3 80
10.7%
5 64
 
8.6%
7 61
 
8.2%
8 50
 
6.7%
6 49
 
6.6%
9 46
 
6.2%
0 45
 
6.0%
Space Separator
ValueCountFrequency (%)
741
100.0%
Open Punctuation
ValueCountFrequency (%)
( 165
100.0%
Close Punctuation
ValueCountFrequency (%)
) 165
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 61
100.0%
Other Punctuation
ValueCountFrequency (%)
, 24
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 2959
60.9%
Common 1903
39.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
수 293
 
9.9%
여 270
 
9.1%
시 244
 
8.2%
남 243
 
8.2%
도 238
 
8.0%
라 237
 
8.0%
전 231
 
7.8%
동 181
 
6.1%
로 158
 
5.3%
길 72
 
2.4%
Other values (91) 792
26.8%
Common
ValueCountFrequency (%)
741
38.9%
1 171
 
9.0%
( 165
 
8.7%
) 165
 
8.7%
2 98
 
5.1%
4 83
 
4.4%
3 80
 
4.2%
5 64
 
3.4%
- 61
 
3.2%
7 61
 
3.2%
Other values (5) 214
 
11.2%

Most occurring blocks

ValueCountFrequency (%)
Hangul 2959
60.9%
ASCII 1903
39.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
741
38.9%
1 171
 
9.0%
( 165
 
8.7%
) 165
 
8.7%
2 98
 
5.1%
4 83
 
4.4%
3 80
 
4.2%
5 64
 
3.4%
- 61
 
3.2%
7 61
 
3.2%
Other values (5) 214
 
11.2%
Hangul
ValueCountFrequency (%)
수 293
 
9.9%
여 270
 
9.1%
시 244
 
8.2%
남 243
 
8.2%
도 238
 
8.0%
라 237
 
8.0%
전 231
 
7.8%
동 181
 
6.1%
로 158
 
5.3%
길 72
 
2.4%
Other values (91) 792
26.8%

소재지지번주소
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing231
Missing (%)100.0%
Memory size2.2 KiB

위도
Real number (ℝ)

HIGH CORRELATION  MISSING 

Distinct222
Distinct (%)98.2%
Missing5
Missing (%)2.2%
Infinite0
Infinite (%)0.0%
Mean34.768741
Minimum34.642023
Maximum34.880339
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size2.2 KiB
2023-12-13T06:36:14.650520image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum34.642023
5-th percentile34.729391
Q134.75366
median34.767665
Q334.776056
95-th percentile34.825961
Maximum34.880339
Range0.23831541
Interquartile range (IQR)0.022395153

Descriptive statistics

Standard deviation0.029842743
Coefficient of variation (CV)0.00085832105
Kurtosis4.1754389
Mean34.768741
Median Absolute Deviation (MAD)0.011946535
Skewness0.99382549
Sum7857.7356
Variance0.0008905893
MonotonicityNot monotonic
2023-12-13T06:36:14.808263image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
34.81155677 2
 
0.9%
34.76682341 2
 
0.9%
34.75441739 2
 
0.9%
34.74856666 2
 
0.9%
34.80010123 1
 
0.4%
34.76922482 1
 
0.4%
34.78393963 1
 
0.4%
34.72634613 1
 
0.4%
34.76595424 1
 
0.4%
34.77229869 1
 
0.4%
Other values (212) 212
91.8%
(Missing) 5
 
2.2%
ValueCountFrequency (%)
34.64202324 1
0.4%
34.71537808 1
0.4%
34.71887875 1
0.4%
34.71976408 1
0.4%
34.72092976 1
0.4%
34.72119249 1
0.4%
34.72214868 1
0.4%
34.72477533 1
0.4%
34.72634613 1
0.4%
34.72837725 1
0.4%
ValueCountFrequency (%)
34.88033865 1
0.4%
34.88027435 1
0.4%
34.8795849 1
0.4%
34.87908925 1
0.4%
34.85945902 1
0.4%
34.85878553 1
0.4%
34.84862192 1
0.4%
34.83958697 1
0.4%
34.83122929 1
0.4%
34.83112031 1
0.4%

경도
Real number (ℝ)

HIGH CORRELATION  MISSING 

Distinct222
Distinct (%)98.2%
Missing5
Missing (%)2.2%
Infinite0
Infinite (%)0.0%
Mean127.68542
Minimum127.56871
Maximum127.78171
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size2.2 KiB
2023-12-13T06:36:14.946711image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum127.56871
5-th percentile127.63886
Q1127.65619
median127.69375
Q3127.70995
95-th percentile127.7428
Maximum127.78171
Range0.2129965
Interquartile range (IQR)0.053751525

Descriptive statistics

Standard deviation0.036176512
Coefficient of variation (CV)0.00028332533
Kurtosis0.15778504
Mean127.68542
Median Absolute Deviation (MAD)0.02964905
Skewness-0.26320781
Sum28856.904
Variance0.00130874
MonotonicityNot monotonic
2023-12-13T06:36:15.088809image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
127.670452 2
 
0.9%
127.7030077 2
 
0.9%
127.7324978 2
 
0.9%
127.6551039 2
 
0.9%
127.6615809 1
 
0.4%
127.6991554 1
 
0.4%
127.6694073 1
 
0.4%
127.7103639 1
 
0.4%
127.6641471 1
 
0.4%
127.6547152 1
 
0.4%
Other values (212) 212
91.8%
(Missing) 5
 
2.2%
ValueCountFrequency (%)
127.5687114 1
0.4%
127.5693522 1
0.4%
127.5772511 1
0.4%
127.592979 1
0.4%
127.5929938 1
0.4%
127.6192989 1
0.4%
127.6323246 1
0.4%
127.633207 1
0.4%
127.6347121 1
0.4%
127.6353928 1
0.4%
ValueCountFrequency (%)
127.7817079 1
0.4%
127.7571094 1
0.4%
127.754799 1
0.4%
127.7537038 1
0.4%
127.751061 1
0.4%
127.7509417 1
0.4%
127.7486993 1
0.4%
127.748262 1
0.4%
127.747298 1
0.4%
127.7437319 1
0.4%

사업등록일자
Date

Distinct212
Distinct (%)91.8%
Missing0
Missing (%)0.0%
Memory size1.9 KiB
Minimum1970-06-30 00:00:00
Maximum2021-03-18 00:00:00
2023-12-13T06:36:15.224431image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T06:36:15.379710image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

면적
Real number (ℝ)

Distinct212
Distinct (%)91.8%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean336.45281
Minimum24
Maximum13442
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size2.2 KiB
2023-12-13T06:36:15.868316image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum24
5-th percentile36.24
Q177.04
median108
Q3189.81
95-th percentile1034.41
Maximum13442
Range13418
Interquartile range (IQR)112.77

Descriptive statistics

Standard deviation1212.9357
Coefficient of variation (CV)3.6050692
Kurtosis91.997364
Mean336.45281
Median Absolute Deviation (MAD)45
Skewness9.2346248
Sum77720.6
Variance1471213
MonotonicityNot monotonic
2023-12-13T06:36:16.021298image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
98.0 5
 
2.2%
84.0 3
 
1.3%
85.0 3
 
1.3%
78.0 3
 
1.3%
122.0 2
 
0.9%
129.0 2
 
0.9%
96.0 2
 
0.9%
126.36 2
 
0.9%
48.0 2
 
0.9%
66.0 2
 
0.9%
Other values (202) 205
88.7%
ValueCountFrequency (%)
24.0 1
0.4%
24.46 1
0.4%
24.5 1
0.4%
28.0 1
0.4%
28.33 1
0.4%
29.0 1
0.4%
29.47 1
0.4%
30.48 1
0.4%
32.0 1
0.4%
34.5 1
0.4%
ValueCountFrequency (%)
13442.0 1
0.4%
11663.0 1
0.4%
3396.3 1
0.4%
2387.97 1
0.4%
2332.54 1
0.4%
1899.65 1
0.4%
1804.78 1
0.4%
1187.25 1
0.4%
1179.92 1
0.4%
1165.92 1
0.4%

영업상태
Categorical

IMBALANCE 

Distinct2
Distinct (%)0.9%
Missing0
Missing (%)0.0%
Memory size1.9 KiB
1
230 
2
 
1

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique1 ?
Unique (%)0.4%

Sample

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

Common Values

ValueCountFrequency (%)
1 230
99.6%
2 1
 
0.4%

Length

2023-12-13T06:36:16.143213image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T06:36:16.253094image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
1 230
99.6%
2 1
 
0.4%

폐업일자
Date

MISSING 

Distinct4
Distinct (%)100.0%
Missing227
Missing (%)98.3%
Memory size1.9 KiB
Minimum2016-07-05 00:00:00
Maximum2020-01-02 00:00:00
2023-12-13T06:36:16.331476image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T06:36:16.415095image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=4)

휴업시작일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing231
Missing (%)100.0%
Memory size2.2 KiB

휴업종료일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing231
Missing (%)100.0%
Memory size2.2 KiB

운영시작시각
Date

MISSING 

Distinct2
Distinct (%)8.0%
Missing206
Missing (%)89.2%
Memory size1.9 KiB
Minimum2023-12-13 08:00:00
Maximum2023-12-13 09:00:00
2023-12-13T06:36:16.501541image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T06:36:16.613674image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=2)

운영종료시각
Date

MISSING 

Distinct4
Distinct (%)16.0%
Missing206
Missing (%)89.2%
Memory size1.9 KiB
Minimum2023-12-13 18:00:00
Maximum2023-12-13 21:00:00
2023-12-13T06:36:16.726302image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T06:36:16.816629image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=4)

전화번호
Text

MISSING 

Distinct211
Distinct (%)99.5%
Missing19
Missing (%)8.2%
Memory size1.9 KiB
2023-12-13T06:36:17.008992image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length13
Median length12
Mean length12.004717
Min length11

Characters and Unicode

Total characters2545
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

Unique210 ?
Unique (%)99.1%

Sample

1st row061-643-0058
2nd row061-663-2222
3rd row061-685-5773
4th row061-653-3001
5th row061-691-7114
ValueCountFrequency (%)
061-686-8040 2
 
0.9%
061-686-2940 1
 
0.5%
061-684-8572 1
 
0.5%
061-643-0058 1
 
0.5%
061-652-2084 1
 
0.5%
061-651-3181 1
 
0.5%
061-681-0038 1
 
0.5%
061-653-6652 1
 
0.5%
061-643-1953 1
 
0.5%
061-685-4692 1
 
0.5%
Other values (201) 201
94.8%
2023-12-13T06:36:17.350410image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
6 500
19.6%
- 424
16.7%
1 372
14.6%
0 329
12.9%
5 202
7.9%
8 195
 
7.7%
4 132
 
5.2%
3 121
 
4.8%
2 116
 
4.6%
9 79
 
3.1%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 2121
83.3%
Dash Punctuation 424
 
16.7%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
6 500
23.6%
1 372
17.5%
0 329
15.5%
5 202
9.5%
8 195
 
9.2%
4 132
 
6.2%
3 121
 
5.7%
2 116
 
5.5%
9 79
 
3.7%
7 75
 
3.5%
Dash Punctuation
ValueCountFrequency (%)
- 424
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 2545
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
6 500
19.6%
- 424
16.7%
1 372
14.6%
0 329
12.9%
5 202
7.9%
8 195
 
7.7%
4 132
 
5.2%
3 121
 
4.8%
2 116
 
4.6%
9 79
 
3.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 2545
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
6 500
19.6%
- 424
16.7%
1 372
14.6%
0 329
12.9%
5 202
7.9%
8 195
 
7.7%
4 132
 
5.2%
3 121
 
4.8%
2 116
 
4.6%
9 79
 
3.1%

관리기관명
Categorical

CONSTANT 

Distinct1
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Memory size1.9 KiB
전라남도 여수시
231 

Length

Max length8
Median length8
Mean length8
Min length8

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row전라남도 여수시
2nd row전라남도 여수시
3rd row전라남도 여수시
4th row전라남도 여수시
5th row전라남도 여수시

Common Values

ValueCountFrequency (%)
전라남도 여수시 231
100.0%

Length

2023-12-13T06:36:17.517614image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T06:36:17.614655image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
전라남도 231
50.0%
여수시 231
50.0%

관리기관전화번호
Categorical

CONSTANT 

Distinct1
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Memory size1.9 KiB
061-659-4144
231 

Length

Max length12
Median length12
Mean length12
Min length12

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row061-659-4144
2nd row061-659-4144
3rd row061-659-4144
4th row061-659-4144
5th row061-659-4144

Common Values

ValueCountFrequency (%)
061-659-4144 231
100.0%

Length

2023-12-13T06:36:17.720421image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T06:36:17.826496image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
061-659-4144 231
100.0%

데이터기준일자
Date

CONSTANT 

Distinct1
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Memory size1.9 KiB
Minimum2021-06-30 00:00:00
Maximum2021-06-30 00:00:00
2023-12-13T06:36:17.914089image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T06:36:18.015611image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=1)

Interactions

2023-12-13T06:36:12.186667image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T06:36:11.721547image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T06:36:11.977841image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T06:36:12.261041image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T06:36:11.792786image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T06:36:12.047962image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T06:36:12.329549image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T06:36:11.885115image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T06:36:12.112996image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-13T06:36:18.109341image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
자동차정비업체종류위도경도면적영업상태폐업일자운영시작시각운영종료시각
자동차정비업체종류1.0000.2370.1340.3010.0001.0000.0000.027
위도0.2371.0000.8260.0000.0001.0000.7880.260
경도0.1340.8261.0000.0000.0001.0000.0000.463
면적0.3010.0000.0001.0000.000NaN0.0000.000
영업상태0.0000.0000.0000.0001.0001.000NaNNaN
폐업일자1.0001.0001.000NaN1.0001.000NaN1.000
운영시작시각0.0000.7880.0000.000NaNNaN1.0000.354
운영종료시각0.0270.2600.4630.000NaN1.0000.3541.000
2023-12-13T06:36:18.324578image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
영업상태자동차정비업체종류
영업상태1.0000.000
자동차정비업체종류0.0001.000
2023-12-13T06:36:18.435960image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
위도경도면적자동차정비업체종류영업상태
위도1.000-0.6030.2050.1060.000
경도-0.6031.000-0.1020.0780.000
면적0.205-0.1021.0000.2490.000
자동차정비업체종류0.1060.0780.2491.0000.000
영업상태0.0000.0000.0000.0001.000

Missing values

2023-12-13T06:36:12.455284image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-13T06:36:12.670604image/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.
2023-12-13T06:36:12.808258image/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

자동차정비업체명자동차정비업체종류소재지도로명주소소재지지번주소위도경도사업등록일자면적영업상태폐업일자휴업시작일자휴업종료일자운영시작시각운영종료시각전화번호관리기관명관리기관전화번호데이터기준일자
0중앙부분정비공업사3전라남도 여수시 좌수영로 101(연등동)<NA>34.749325127.7275611998-07-29139.322016-07-05<NA><NA><NA><NA>061-643-0058전라남도 여수시061-659-41442021-06-30
1(유)동성자동차공업사1전라남도 여수시 연등8길 23(연등동)<NA>34.756305127.7228491970-06-301179.921<NA><NA><NA><NA><NA>061-663-2222전라남도 여수시061-659-41442021-06-30
2(유)신여천자동차공업사1전라남도 여수시 여수산단로 327(평여동)<NA>34.811557127.6704521981-12-221804.781<NA><NA><NA><NA><NA>061-685-5773전라남도 여수시061-659-41442021-06-30
3(주)동양교통 자가정비업1전라남도 여수시 좌수영로 422(미평동)<NA>34.766823127.7030081989-02-20354.21<NA><NA><NA><NA><NA>061-653-3001전라남도 여수시061-659-41442021-06-30
4엑스포정비서비스1전라남도 여수시 망마로 58, 306동 1층 04호(신기동, 부영아파트)<NA>34.758535127.6690931993-06-073396.31<NA><NA><NA><NA><NA>061-691-7114전라남도 여수시061-659-41442021-06-30
5제일보링4전라남도 여수시 봉산남7길 17-13<NA>34.732838127.7244481994-01-13341.941<NA><NA><NA><NA><NA>061-643-1889전라남도 여수시061-659-41442021-06-30
6(주)신광자동차공업사1전라남도 여수시 만성로 184-19<NA>34.772811127.7177151994-12-3011663.01<NA><NA><NA><NA><NA>061-651-8611전라남도 여수시061-659-41442021-06-30
7여수여객자동차(주)종합자가정비공장1전라남도 여수시 좌수영로 531(둔덕동)<NA>34.770964127.6931311996-10-30896.01<NA><NA><NA><NA><NA>061-653-3333전라남도 여수시061-659-41442021-06-30
8르노삼성자동차지정정비코너 학동점3전라남도 여수시 쌍봉로 139(학동)<NA>34.765621127.671091997-02-05252.261<NA><NA><NA><NA><NA>061-682-3166전라남도 여수시061-659-41442021-06-30
9만도상사3전라남도 여수시 좌수영로 170(연등동)<NA>34.7553127.7260981997-05-28188.171<NA><NA><NA>9:0021:00061-642-7101전라남도 여수시061-659-41442021-06-30
자동차정비업체명자동차정비업체종류소재지도로명주소소재지지번주소위도경도사업등록일자면적영업상태폐업일자휴업시작일자휴업종료일자운영시작시각운영종료시각전화번호관리기관명관리기관전화번호데이터기준일자
221태영타이어3전라남도 여수시 주동2길 4(주삼동)<NA>34.787663127.6515532019-07-11850.561<NA><NA><NA>9:0018:00061-681-5599전라남도 여수시061-659-41442021-06-30
222마루모터스3전라남도 여수시 충민로 135(덕충동)<NA>34.754417127.7324982019-11-12126.361<NA><NA><NA>9:0021:00061-652-1252전라남도 여수시061-659-41442021-06-30
223뉴월드 전문정비3전라남도 여수시 여문문화1길 84(여서동)<NA>34.749758127.7002222020-01-0329.471<NA><NA><NA>8:0019:00<NA>전라남도 여수시061-659-41442021-06-30
224여수시도시관리공단 청소차량 정비소3전라남도 여수시 신월로 284-1(웅천동)<NA><NA><NA>2020-03-11101.031<NA><NA><NA>9:0021:00061-662-8242전라남도 여수시061-659-41442021-06-30
225금호타이어 여천대리점3전라남도 여수시 쌍봉로 125<NA>34.765714127.6697352020-04-28164.821<NA><NA><NA>9:0021:00061-683-1144전라남도 여수시061-659-41442021-06-30
226한국자동차공업사2전라남도 여수시 시청로 238(여천동)<NA>34.782967127.6629152020-05-14129.01<NA><NA><NA>9:0021:00<NA>전라남도 여수시061-659-41442021-06-30
227남여수종합서비스기아오토큐 주식회사1전라남도 여수시 소라면 소호관기로 143<NA><NA><NA>2020-10-202387.971<NA><NA><NA>8:0021:00061-692-8285전라남도 여수시061-659-41442021-06-30
228동화카밧데리3전라남도 여수시 여수산단1로 194<NA>34.820819127.640762020-10-20194.351<NA><NA><NA>8:0021:00061-685-7249전라남도 여수시061-659-41442021-06-30
229쌍봉자동차정비3전라남도 여수시 새터로 13(신기동)<NA>34.758028127.674622021-03-1867.51<NA><NA><NA>9:0021:00061-685-7171전라남도 여수시061-659-41442021-06-30
230둔덕오름자동차공업사1전라남도 여수시 좌수영로 644(둔덕동)<NA>34.781085127.6961072021-03-18372.881<NA><NA><NA>9:0021:00061-653-5660전라남도 여수시061-659-41442021-06-30