Overview

Dataset statistics

Number of variables9
Number of observations45
Missing cells52
Missing cells (%)12.8%
Duplicate rows1
Duplicate rows (%)2.2%
Total size in memory3.3 KiB
Average record size in memory75.9 B

Variable types

Numeric1
Categorical6
Text1
DateTime1

Dataset

Description인천광역시 중구 내의 공공 급경사지 현황입니다.인천 중구의 급경사지 지번주소, 용도, 구조, 유형, 관리주체 등을 확인 할 수 있습니다.
Author인천광역시 중구
URLhttps://data.incheon.go.kr/findData/publicDataDetail?dataId=15121206&srcSe=7661IVAWM27C61E190

Alerts

데이터기준일자 has constant value ""Constant
Dataset has 1 (2.2%) duplicate rowsDuplicates
관리주체 is highly overall correlated with 번호 and 1 other fieldsHigh correlation
용도 is highly overall correlated with 유형High correlation
구조 is highly overall correlated with 유형High correlation
안전등급 is highly overall correlated with 유형High correlation
유형 is highly overall correlated with 번호 and 5 other fieldsHigh correlation
동 is highly overall correlated with 유형High correlation
번호 is highly overall correlated with 유형 and 1 other fieldsHigh correlation
번호 has 17 (37.8%) missing valuesMissing
지번주소 has 18 (40.0%) missing valuesMissing
데이터기준일자 has 17 (37.8%) missing valuesMissing

Reproduction

Analysis started2024-01-28 12:15:36.248749
Analysis finished2024-01-28 12:15:37.050944
Duration0.8 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

번호
Real number (ℝ)

HIGH CORRELATION  MISSING 

Distinct28
Distinct (%)100.0%
Missing17
Missing (%)37.8%
Infinite0
Infinite (%)0.0%
Mean15.107143
Minimum1
Maximum45
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size537.0 B
2024-01-28T21:15:37.105762image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile2.35
Q17.75
median14.5
Q321.25
95-th percentile26.65
Maximum45
Range44
Interquartile range (IQR)13.5

Descriptive statistics

Standard deviation9.7461836
Coefficient of variation (CV)0.64513745
Kurtosis1.7075038
Mean15.107143
Median Absolute Deviation (MAD)7
Skewness0.91487409
Sum423
Variance94.988095
MonotonicityStrictly increasing
2024-01-28T21:15:37.206256image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=28)
ValueCountFrequency (%)
16 1
 
2.2%
45 1
 
2.2%
27 1
 
2.2%
26 1
 
2.2%
25 1
 
2.2%
24 1
 
2.2%
23 1
 
2.2%
22 1
 
2.2%
21 1
 
2.2%
20 1
 
2.2%
Other values (18) 18
40.0%
(Missing) 17
37.8%
ValueCountFrequency (%)
1 1
2.2%
2 1
2.2%
3 1
2.2%
4 1
2.2%
5 1
2.2%
6 1
2.2%
7 1
2.2%
8 1
2.2%
9 1
2.2%
10 1
2.2%
ValueCountFrequency (%)
45 1
2.2%
27 1
2.2%
26 1
2.2%
25 1
2.2%
24 1
2.2%
23 1
2.2%
22 1
2.2%
21 1
2.2%
20 1
2.2%
19 1
2.2%

동
Categorical

HIGH CORRELATION 

Distinct11
Distinct (%)24.4%
Missing0
Missing (%)0.0%
Memory size492.0 B
<NA>
17 
도원동
6 
송월동
5 
운북동
5 
전동
4 
Other values (6)
8 

Length

Max length4
Median length3
Mean length3.2666667
Min length2

Unique

Unique5 ?
Unique (%)11.1%

Sample

1st row전동
2nd row전동
3rd row전동
4th row도원동
5th row도원동

Common Values

ValueCountFrequency (%)
<NA> 17
37.8%
도원동 6
 
13.3%
송월동 5
 
11.1%
운북동 5
 
11.1%
전동 4
 
8.9%
운남동 3
 
6.7%
북성동 1
 
2.2%
중산동 1
 
2.2%
남북동 1
 
2.2%
답동 1
 
2.2%

Length

2024-01-28T21:15:37.312386image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
na 17
37.8%
도원동 6
 
13.3%
송월동 5
 
11.1%
운북동 5
 
11.1%
전동 4
 
8.9%
운남동 3
 
6.7%
북성동 1
 
2.2%
중산동 1
 
2.2%
남북동 1
 
2.2%
답동 1
 
2.2%

지번주소
Text

MISSING 

Distinct23
Distinct (%)85.2%
Missing18
Missing (%)40.0%
Memory size492.0 B
2024-01-28T21:15:37.478919image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length20
Median length19
Mean length18.037037
Min length14

Characters and Unicode

Total characters487
Distinct characters33
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

Unique21 ?
Unique (%)77.8%

Sample

1st row인천광역시 중구 전동 26
2nd row인천광역시 중구 전동 26
3rd row인천광역시 중구 전동 34-70
4th row인천광역시 중구 도원동 12-73
5th row인천광역시 중구 도원동 12-73
ValueCountFrequency (%)
인천광역시 27
25.0%
중구 27
25.0%
도원동 6
 
5.6%
운북동 5
 
4.6%
12-73 4
 
3.7%
전동 4
 
3.7%
송월동3가 3
 
2.8%
운남동 3
 
2.8%
26 2
 
1.9%
산128-43 1
 
0.9%
Other values (26) 26
24.1%
2024-01-28T21:15:37.764056image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
81
16.6%
중 28
 
5.7%
인 27
 
5.5%
동 27
 
5.5%
광 27
 
5.5%
역 27
 
5.5%
시 27
 
5.5%
구 27
 
5.5%
천 27
 
5.5%
- 23
 
4.7%
Other values (23) 166
34.1%

Most occurring categories

ValueCountFrequency (%)
Other Letter 274
56.3%
Decimal Number 109
 
22.4%
Space Separator 81
 
16.6%
Dash Punctuation 23
 
4.7%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
중 28
10.2%
인 27
9.9%
동 27
9.9%
광 27
9.9%
역 27
9.9%
시 27
9.9%
구 27
9.9%
천 27
9.9%
운 8
 
2.9%
북 7
 
2.6%
Other values (11) 42
15.3%
Decimal Number
ValueCountFrequency (%)
1 22
20.2%
2 18
16.5%
3 17
15.6%
5 14
12.8%
7 9
8.3%
4 8
 
7.3%
8 6
 
5.5%
6 6
 
5.5%
0 5
 
4.6%
9 4
 
3.7%
Space Separator
ValueCountFrequency (%)
81
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 23
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 274
56.3%
Common 213
43.7%

Most frequent character per script

Hangul
ValueCountFrequency (%)
중 28
10.2%
인 27
9.9%
동 27
9.9%
광 27
9.9%
역 27
9.9%
시 27
9.9%
구 27
9.9%
천 27
9.9%
운 8
 
2.9%
북 7
 
2.6%
Other values (11) 42
15.3%
Common
ValueCountFrequency (%)
81
38.0%
- 23
 
10.8%
1 22
 
10.3%
2 18
 
8.5%
3 17
 
8.0%
5 14
 
6.6%
7 9
 
4.2%
4 8
 
3.8%
8 6
 
2.8%
6 6
 
2.8%
Other values (2) 9
 
4.2%

Most occurring blocks

ValueCountFrequency (%)
Hangul 274
56.3%
ASCII 213
43.7%

Most frequent character per block

ASCII
ValueCountFrequency (%)
81
38.0%
- 23
 
10.8%
1 22
 
10.3%
2 18
 
8.5%
3 17
 
8.0%
5 14
 
6.6%
7 9
 
4.2%
4 8
 
3.8%
8 6
 
2.8%
6 6
 
2.8%
Other values (2) 9
 
4.2%
Hangul
ValueCountFrequency (%)
중 28
10.2%
인 27
9.9%
동 27
9.9%
광 27
9.9%
역 27
9.9%
시 27
9.9%
구 27
9.9%
천 27
9.9%
운 8
 
2.9%
북 7
 
2.6%
Other values (11) 42
15.3%

용도
Categorical

HIGH CORRELATION 

Distinct4
Distinct (%)8.9%
Missing0
Missing (%)0.0%
Memory size492.0 B
<NA>
17 
도로
15 
기타
12 
주택
 
1

Length

Max length4
Median length2
Mean length2.7555556
Min length2

Unique

Unique1 ?
Unique (%)2.2%

Sample

1st row기타
2nd row기타
3rd row도로
4th row기타
5th row기타

Common Values

ValueCountFrequency (%)
<NA> 17
37.8%
도로 15
33.3%
기타 12
26.7%
주택 1
 
2.2%

Length

2024-01-28T21:15:37.889996image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-01-28T21:15:37.991527image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 17
37.8%
도로 15
33.3%
기타 12
26.7%
주택 1
 
2.2%

구조
Categorical

HIGH CORRELATION 

Distinct6
Distinct (%)13.3%
Missing0
Missing (%)0.0%
Memory size492.0 B
<NA>
17 
석축
9 
복합
8 
토사
5 
옹벽
3 

Length

Max length4
Median length2
Mean length2.7555556
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row복합
2nd row복합
3rd row복합
4th row옹벽
5th row암반

Common Values

ValueCountFrequency (%)
<NA> 17
37.8%
석축 9
20.0%
복합 8
17.8%
토사 5
 
11.1%
옹벽 3
 
6.7%
암반 3
 
6.7%

Length

2024-01-28T21:15:38.101292image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-01-28T21:15:38.205552image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 17
37.8%
석축 9
20.0%
복합 8
17.8%
토사 5
 
11.1%
옹벽 3
 
6.7%
암반 3
 
6.7%

유형
Categorical

HIGH CORRELATION 

Distinct2
Distinct (%)4.4%
Missing0
Missing (%)0.0%
Memory size492.0 B
인공
28 
<NA>
17 

Length

Max length4
Median length2
Mean length2.7555556
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
인공 28
62.2%
<NA> 17
37.8%

Length

2024-01-28T21:15:38.319155image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-01-28T21:15:38.419612image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
인공 28
62.2%
na 17
37.8%

관리주체
Categorical

HIGH CORRELATION 

Distinct3
Distinct (%)6.7%
Missing0
Missing (%)0.0%
Memory size492.0 B
공공
27 
<NA>
17 
민간
 
1

Length

Max length4
Median length2
Mean length2.7555556
Min length2

Unique

Unique1 ?
Unique (%)2.2%

Sample

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

Common Values

ValueCountFrequency (%)
공공 27
60.0%
<NA> 17
37.8%
민간 1
 
2.2%

Length

2024-01-28T21:15:38.521424image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-01-28T21:15:38.633412image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
공공 27
60.0%
na 17
37.8%
민간 1
 
2.2%

안전등급
Categorical

HIGH CORRELATION 

Distinct4
Distinct (%)8.9%
Missing0
Missing (%)0.0%
Memory size492.0 B
<NA>
17 
B
16 
C
10 
A
2 

Length

Max length4
Median length1
Mean length2.1333333
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 17
37.8%
B 16
35.6%
C 10
22.2%
A 2
 
4.4%

Length

2024-01-28T21:15:38.736968image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-01-28T21:15:38.825430image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 17
37.8%
b 16
35.6%
c 10
22.2%
a 2
 
4.4%

데이터기준일자
Date

CONSTANT  MISSING 

Distinct1
Distinct (%)3.6%
Missing17
Missing (%)37.8%
Memory size492.0 B
Minimum2023-08-21 00:00:00
Maximum2023-08-21 00:00:00
2024-01-28T21:15:38.906946image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-28T21:15:38.978055image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=1)

Interactions

2024-01-28T21:15:36.612233image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-01-28T21:15:39.039250image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
번호동지번주소용도구조관리주체안전등급
번호1.0000.7800.9390.5820.6371.0000.480
동0.7801.0001.0000.4770.8180.0000.725
지번주소0.9391.0001.0001.0000.6821.0000.922
용도0.5820.4771.0001.0000.3230.0000.000
구조0.6370.8180.6820.3231.0000.3610.000
관리주체1.0000.0001.0000.0000.3611.0000.000
안전등급0.4800.7250.9220.0000.0000.0001.000
2024-01-28T21:15:39.137745image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
관리주체용도구조안전등급유형동
관리주체1.0000.0000.4080.0001.0000.000
용도0.0001.0000.2370.0001.0000.255
구조0.4080.2371.0000.0001.0000.409
안전등급0.0000.0000.0001.0001.0000.491
유형1.0001.0001.0001.0001.0001.000
동0.0000.2550.4090.4911.0001.000
2024-01-28T21:15:39.232933image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
번호동용도구조유형관리주체안전등급
번호1.0000.4990.4300.3951.0000.8990.200
동0.4991.0000.2550.4091.0000.0000.491
용도0.4300.2551.0000.2371.0000.0000.000
구조0.3950.4090.2371.0001.0000.4080.000
유형1.0001.0001.0001.0001.0001.0001.000
관리주체0.8990.0000.0000.4081.0001.0000.000
안전등급0.2000.4910.0000.0001.0000.0001.000

Missing values

2024-01-28T21:15:36.715522image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-01-28T21:15:36.823071image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Nullity matrix is a data-dense display which lets you quickly visually pick out patterns in data completion.
2024-01-28T21:15:36.953769image/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

번호동지번주소용도구조유형관리주체안전등급데이터기준일자
01전동인천광역시 중구 전동 26기타복합인공공공B2023-08-21
12전동인천광역시 중구 전동 26기타복합인공공공B2023-08-21
23전동인천광역시 중구 전동 34-70도로복합인공공공B2023-08-21
34도원동인천광역시 중구 도원동 12-73기타옹벽인공공공B2023-08-21
45도원동인천광역시 중구 도원동 12-73기타암반인공공공B2023-08-21
56도원동인천광역시 중구 도원동 12-73기타석축인공공공C2023-08-21
67도원동인천광역시 중구 도원동 12-73기타석축인공공공B2023-08-21
78도원동인천광역시 중구 도원동 12-117기타석축인공공공A2023-08-21
89도원동인천광역시 중구 도원동 12-155기타석축인공공공B2023-08-21
910북성동인천광역시 중구 북성동3가 10-4도로석축인공공공A2023-08-21
번호동지번주소용도구조유형관리주체안전등급데이터기준일자
35<NA><NA><NA><NA><NA><NA><NA><NA><NA>
36<NA><NA><NA><NA><NA><NA><NA><NA><NA>
37<NA><NA><NA><NA><NA><NA><NA><NA><NA>
38<NA><NA><NA><NA><NA><NA><NA><NA><NA>
39<NA><NA><NA><NA><NA><NA><NA><NA><NA>
40<NA><NA><NA><NA><NA><NA><NA><NA><NA>
41<NA><NA><NA><NA><NA><NA><NA><NA><NA>
42<NA><NA><NA><NA><NA><NA><NA><NA><NA>
43<NA><NA><NA><NA><NA><NA><NA><NA><NA>
4445운북동인천광역시 중구 운북동 752-109기타옹벽인공민간C2023-08-21

Duplicate rows

Most frequently occurring

번호동지번주소용도구조유형관리주체안전등급데이터기준일자# duplicates
0<NA><NA><NA><NA><NA><NA><NA><NA><NA>17