Overview

Dataset statistics

Number of variables18
Number of observations30
Missing cells121
Missing cells (%)22.4%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory4.6 KiB
Average record size in memory156.4 B

Variable types

Text5
Categorical2
DateTime3
Unsupported4
Numeric4

Dataset

Description전라남도 곡성군 자동차 정비업체 현황(도로명주소, 정비업소유형, 영업상태, 면적, 전화번호 등을 제공하는 데이터)
Author전라남도 곡성군
URLhttps://www.data.go.kr/data/15025247/fileData.do

Alerts

영업상태명 has constant value ""Constant
데이터기준일자 has constant value ""Constant
소재지면적 is highly overall correlated with 정비업유형High correlation
우편번호 is highly overall correlated with 경도High correlation
경도 is highly overall correlated with 우편번호High correlation
정비업유형 is highly overall correlated with 소재지면적High correlation
정비업유형 is highly imbalanced (64.7%)Imbalance
폐업일자 has 30 (100.0%) missing valuesMissing
휴업시작일자 has 30 (100.0%) missing valuesMissing
휴업종료일자 has 30 (100.0%) missing valuesMissing
재개업일자 has 30 (100.0%) missing valuesMissing
전화번호 has 1 (3.3%) missing valuesMissing
사업장명 has unique valuesUnique
지번주소 has unique valuesUnique
도로명주소 has unique valuesUnique
소재지면적 has unique valuesUnique
인허가번호 has unique valuesUnique
위도 has unique valuesUnique
경도 has unique valuesUnique
폐업일자 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
재개업일자 is an unsupported type, check if it needs cleaning or further analysisUnsupported

Reproduction

Analysis started2023-12-12 23:21:51.236326
Analysis finished2023-12-12 23:21:53.545743
Duration2.31 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

사업장명
Text

UNIQUE 

Distinct30
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size372.0 B
2023-12-13T08:21:53.711924image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length13
Median length10.5
Mean length8.0333333
Min length5

Characters and Unicode

Total characters241
Distinct characters72
Distinct categories4 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique30 ?
Unique (%)100.0%

Sample

1st row삼성자동차정비공업사
2nd row옥과1급자동차정비
3rd row대신자동차부분정비공업사
4th row고향부분정비공업사
5th row오산자동차공업사
ValueCountFrequency (%)
카센타 2
 
5.6%
삼성자동차정비공업사 1
 
2.8%
현대자동차옥과점 1
 
2.8%
금정종합자동차서비스 1
 
2.8%
한국타이어 1
 
2.8%
곡성톨게이트 1
 
2.8%
카센터 1
 
2.8%
전종수 1
 
2.8%
곡성점 1
 
2.8%
엄지카공업사 1
 
2.8%
Other values (25) 25
69.4%
2023-12-13T08:21:54.046479image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
16
 
6.6%
12
 
5.0%
12
 
5.0%
12
 
5.0%
12
 
5.0%
11
 
4.6%
11
 
4.6%
11
 
4.6%
11
 
4.6%
11
 
4.6%
Other values (62) 122
50.6%

Most occurring categories

ValueCountFrequency (%)
Other Letter 232
96.3%
Space Separator 6
 
2.5%
Uppercase Letter 2
 
0.8%
Decimal Number 1
 
0.4%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
16
 
6.9%
12
 
5.2%
12
 
5.2%
12
 
5.2%
12
 
5.2%
11
 
4.7%
11
 
4.7%
11
 
4.7%
11
 
4.7%
11
 
4.7%
Other values (58) 113
48.7%
Uppercase Letter
ValueCountFrequency (%)
M 1
50.0%
G 1
50.0%
Space Separator
ValueCountFrequency (%)
6
100.0%
Decimal Number
ValueCountFrequency (%)
1 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 232
96.3%
Common 7
 
2.9%
Latin 2
 
0.8%

Most frequent character per script

Hangul
ValueCountFrequency (%)
16
 
6.9%
12
 
5.2%
12
 
5.2%
12
 
5.2%
12
 
5.2%
11
 
4.7%
11
 
4.7%
11
 
4.7%
11
 
4.7%
11
 
4.7%
Other values (58) 113
48.7%
Common
ValueCountFrequency (%)
6
85.7%
1 1
 
14.3%
Latin
ValueCountFrequency (%)
M 1
50.0%
G 1
50.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 232
96.3%
ASCII 9
 
3.7%

Most frequent character per block

Hangul
ValueCountFrequency (%)
16
 
6.9%
12
 
5.2%
12
 
5.2%
12
 
5.2%
12
 
5.2%
11
 
4.7%
11
 
4.7%
11
 
4.7%
11
 
4.7%
11
 
4.7%
Other values (58) 113
48.7%
ASCII
ValueCountFrequency (%)
6
66.7%
M 1
 
11.1%
G 1
 
11.1%
1 1
 
11.1%

지번주소
Text

UNIQUE 

Distinct30
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size372.0 B
2023-12-13T08:21:54.250369image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length23
Median length22
Mean length21.733333
Min length19

Characters and Unicode

Total characters652
Distinct characters47
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

Unique30 ?
Unique (%)100.0%

Sample

1st row전라남도 곡성군 오곡면 오지리 1321
2nd row전라남도 곡성군 오산면 운곡리 19
3rd row전라남도 곡성군 곡성읍 읍내리 688-2
4th row전라남도 곡성군 곡성읍 죽동리 43-5
5th row전라남도 곡성군 오산면 연화리 57-2
ValueCountFrequency (%)
전라남도 30
20.0%
곡성군 30
20.0%
곡성읍 12
 
8.0%
읍내리 10
 
6.7%
옥과면 5
 
3.3%
삼기면 3
 
2.0%
오산면 3
 
2.0%
괴소리 3
 
2.0%
입면 3
 
2.0%
석곡면 2
 
1.3%
Other values (41) 49
32.7%
2023-12-13T08:21:54.598665image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
120
18.4%
50
 
7.7%
42
 
6.4%
32
 
4.9%
30
 
4.6%
30
 
4.6%
30
 
4.6%
30
 
4.6%
30
 
4.6%
- 27
 
4.1%
Other values (37) 231
35.4%

Most occurring categories

ValueCountFrequency (%)
Other Letter 387
59.4%
Space Separator 120
 
18.4%
Decimal Number 118
 
18.1%
Dash Punctuation 27
 
4.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
50
12.9%
42
10.9%
32
8.3%
30
7.8%
30
7.8%
30
7.8%
30
7.8%
30
7.8%
22
 
5.7%
18
 
4.7%
Other values (25) 73
18.9%
Decimal Number
ValueCountFrequency (%)
1 27
22.9%
3 14
11.9%
2 14
11.9%
5 13
11.0%
4 11
9.3%
8 11
9.3%
9 9
 
7.6%
0 8
 
6.8%
7 6
 
5.1%
6 5
 
4.2%
Space Separator
ValueCountFrequency (%)
120
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 27
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 387
59.4%
Common 265
40.6%

Most frequent character per script

Hangul
ValueCountFrequency (%)
50
12.9%
42
10.9%
32
8.3%
30
7.8%
30
7.8%
30
7.8%
30
7.8%
30
7.8%
22
 
5.7%
18
 
4.7%
Other values (25) 73
18.9%
Common
ValueCountFrequency (%)
120
45.3%
- 27
 
10.2%
1 27
 
10.2%
3 14
 
5.3%
2 14
 
5.3%
5 13
 
4.9%
4 11
 
4.2%
8 11
 
4.2%
9 9
 
3.4%
0 8
 
3.0%
Other values (2) 11
 
4.2%

Most occurring blocks

ValueCountFrequency (%)
Hangul 387
59.4%
ASCII 265
40.6%

Most frequent character per block

ASCII
ValueCountFrequency (%)
120
45.3%
- 27
 
10.2%
1 27
 
10.2%
3 14
 
5.3%
2 14
 
5.3%
5 13
 
4.9%
4 11
 
4.2%
8 11
 
4.2%
9 9
 
3.4%
0 8
 
3.0%
Other values (2) 11
 
4.2%
Hangul
ValueCountFrequency (%)
50
12.9%
42
10.9%
32
8.3%
30
7.8%
30
7.8%
30
7.8%
30
7.8%
30
7.8%
22
 
5.7%
18
 
4.7%
Other values (25) 73
18.9%

도로명주소
Text

UNIQUE 

Distinct30
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size372.0 B
2023-12-13T08:21:54.798465image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length24
Median length22
Mean length19.833333
Min length16

Characters and Unicode

Total characters595
Distinct characters53
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

Unique30 ?
Unique (%)100.0%

Sample

1st row전라남도 곡성군 오곡면 기차마을로 245
2nd row전라남도 곡성군 오산면 오산로 975
3rd row전라남도 곡성군 곡성읍 낙동원로 97
4th row전라남도 곡성군 곡성읍 곡성로 746
5th row전라남도 곡성군 오산면 오산로 968
ValueCountFrequency (%)
전라남도 30
20.1%
곡성군 30
20.1%
곡성읍 12
 
8.1%
곡성로 6
 
4.0%
옥과면 5
 
3.4%
삼기면 3
 
2.0%
오산면 3
 
2.0%
오산로 3
 
2.0%
곡순로 3
 
2.0%
대학로 2
 
1.3%
Other values (42) 52
34.9%
2023-12-13T08:21:55.156955image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
119
20.0%
58
 
9.7%
48
 
8.1%
30
 
5.0%
30
 
5.0%
30
 
5.0%
30
 
5.0%
30
 
5.0%
27
 
4.5%
19
 
3.2%
Other values (43) 174
29.2%

Most occurring categories

ValueCountFrequency (%)
Other Letter 394
66.2%
Space Separator 119
 
20.0%
Decimal Number 80
 
13.4%
Dash Punctuation 2
 
0.3%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
58
14.7%
48
12.2%
30
 
7.6%
30
 
7.6%
30
 
7.6%
30
 
7.6%
30
 
7.6%
27
 
6.9%
19
 
4.8%
12
 
3.0%
Other values (31) 80
20.3%
Decimal Number
ValueCountFrequency (%)
1 14
17.5%
8 11
13.8%
9 10
12.5%
6 10
12.5%
2 9
11.2%
7 9
11.2%
5 7
8.8%
4 4
 
5.0%
0 4
 
5.0%
3 2
 
2.5%
Space Separator
ValueCountFrequency (%)
119
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 394
66.2%
Common 201
33.8%

Most frequent character per script

Hangul
ValueCountFrequency (%)
58
14.7%
48
12.2%
30
 
7.6%
30
 
7.6%
30
 
7.6%
30
 
7.6%
30
 
7.6%
27
 
6.9%
19
 
4.8%
12
 
3.0%
Other values (31) 80
20.3%
Common
ValueCountFrequency (%)
119
59.2%
1 14
 
7.0%
8 11
 
5.5%
9 10
 
5.0%
6 10
 
5.0%
2 9
 
4.5%
7 9
 
4.5%
5 7
 
3.5%
4 4
 
2.0%
0 4
 
2.0%
Other values (2) 4
 
2.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 394
66.2%
ASCII 201
33.8%

Most frequent character per block

ASCII
ValueCountFrequency (%)
119
59.2%
1 14
 
7.0%
8 11
 
5.5%
9 10
 
5.0%
6 10
 
5.0%
2 9
 
4.5%
7 9
 
4.5%
5 7
 
3.5%
4 4
 
2.0%
0 4
 
2.0%
Other values (2) 4
 
2.0%
Hangul
ValueCountFrequency (%)
58
14.7%
48
12.2%
30
 
7.6%
30
 
7.6%
30
 
7.6%
30
 
7.6%
30
 
7.6%
27
 
6.9%
19
 
4.8%
12
 
3.0%
Other values (31) 80
20.3%

정비업유형
Categorical

HIGH CORRELATION  IMBALANCE 

Distinct2
Distinct (%)6.7%
Missing0
Missing (%)0.0%
Memory size372.0 B
전문정비업
28 
종합정비업
 
2

Length

Max length5
Median length5
Mean length5
Min length5

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row종합정비업
2nd row종합정비업
3rd row전문정비업
4th row전문정비업
5th row전문정비업

Common Values

ValueCountFrequency (%)
전문정비업 28
93.3%
종합정비업 2
 
6.7%

Length

2023-12-13T08:21:55.283215image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T08:21:55.372582image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
전문정비업 28
93.3%
종합정비업 2
 
6.7%
Distinct29
Distinct (%)96.7%
Missing0
Missing (%)0.0%
Memory size372.0 B
Minimum1986-12-26 00:00:00
Maximum2012-03-20 00:00:00
2023-12-13T08:21:55.454400image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T08:21:55.579063image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=29)

영업상태명
Categorical

CONSTANT 

Distinct1
Distinct (%)3.3%
Missing0
Missing (%)0.0%
Memory size372.0 B
영업중
30 

Length

Max length3
Median length3
Mean length3
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
영업중 30
100.0%

Length

2023-12-13T08:21:55.719423image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T08:21:55.814375image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
영업중 30
100.0%

폐업일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing30
Missing (%)100.0%
Memory size402.0 B

휴업시작일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing30
Missing (%)100.0%
Memory size402.0 B

휴업종료일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing30
Missing (%)100.0%
Memory size402.0 B

재개업일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing30
Missing (%)100.0%
Memory size402.0 B

소재지면적
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct30
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean820.83
Minimum109
Maximum3825
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size402.0 B
2023-12-13T08:21:55.911679image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum109
5-th percentile122.795
Q1327.25
median772.2
Q3987
95-th percentile1949.35
Maximum3825
Range3716
Interquartile range (IQR)659.75

Descriptive statistics

Standard deviation744.55829
Coefficient of variation (CV)0.90707977
Kurtosis8.5861124
Mean820.83
Median Absolute Deviation (MAD)316.5
Skewness2.460597
Sum24624.9
Variance554367.05
MonotonicityNot monotonic
2023-12-13T08:21:56.312780image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=30)
ValueCountFrequency (%)
3825.0 1
 
3.3%
647.0 1
 
3.3%
632.0 1
 
3.3%
310.0 1
 
3.3%
906.0 1
 
3.3%
109.0 1
 
3.3%
379.0 1
 
3.3%
431.0 1
 
3.3%
144.0 1
 
3.3%
133.0 1
 
3.3%
Other values (20) 20
66.7%
ValueCountFrequency (%)
109.0 1
3.3%
118.7 1
3.3%
127.8 1
3.3%
133.0 1
3.3%
144.0 1
3.3%
148.4 1
3.3%
185.6 1
3.3%
310.0 1
3.3%
379.0 1
3.3%
431.0 1
3.3%
ValueCountFrequency (%)
3825.0 1
3.3%
1975.0 1
3.3%
1918.0 1
3.3%
1172.0 1
3.3%
1092.0 1
3.3%
1071.0 1
3.3%
1000.0 1
3.3%
992.0 1
3.3%
972.0 1
3.3%
963.0 1
3.3%

우편번호
Real number (ℝ)

HIGH CORRELATION 

Distinct16
Distinct (%)53.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean57527.333
Minimum57500
Maximum57560
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size402.0 B
2023-12-13T08:21:56.442276image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum57500
5-th percentile57502.9
Q157514
median57533
Q357540.75
95-th percentile57552.8
Maximum57560
Range60
Interquartile range (IQR)26.75

Descriptive statistics

Standard deviation16.764769
Coefficient of variation (CV)0.00029142266
Kurtosis-0.83413165
Mean57527.333
Median Absolute Deviation (MAD)11
Skewness0.049023795
Sum1725820
Variance281.05747
MonotonicityNot monotonic
2023-12-13T08:21:56.579573image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=16)
ValueCountFrequency (%)
57533 4
13.3%
57522 3
10.0%
57541 3
10.0%
57517 3
10.0%
57544 2
 
6.7%
57505 2
 
6.7%
57560 2
 
6.7%
57535 2
 
6.7%
57510 2
 
6.7%
57500 1
 
3.3%
Other values (6) 6
20.0%
ValueCountFrequency (%)
57500 1
 
3.3%
57502 1
 
3.3%
57504 1
 
3.3%
57505 2
6.7%
57510 2
6.7%
57513 1
 
3.3%
57517 3
10.0%
57522 3
10.0%
57533 4
13.3%
57535 2
6.7%
ValueCountFrequency (%)
57560 2
6.7%
57544 2
6.7%
57542 1
 
3.3%
57541 3
10.0%
57540 1
 
3.3%
57539 1
 
3.3%
57535 2
6.7%
57533 4
13.3%
57522 3
10.0%
57517 3
10.0%
Distinct29
Distinct (%)96.7%
Missing0
Missing (%)0.0%
Memory size372.0 B
Minimum1986-12-26 00:00:00
Maximum2012-03-20 00:00:00
2023-12-13T08:21:56.735026image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/