Overview

Dataset statistics

Number of variables4
Number of observations90
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory3.0 KiB
Average record size in memory34.5 B

Variable types

Numeric1
Text1
Categorical1
DateTime1

Dataset

Description인천광역시 중구 관내에 위치한 구민게시판에 대한 데이터 입니다.파일명 인천광역시_중구_ 구민게시판파일내용 연번, 설치장소명, 용도구분 등
Author인천광역시 중구
URLhttps://data.incheon.go.kr/findData/publicDataDetail?dataId=15086261&srcSe=7661IVAWM27C61E190

Alerts

데이터기준일 has constant value ""Constant
연번 is highly overall correlated with 용도구분High correlation
용도구분 is highly overall correlated with 연번High correlation
연번 has unique valuesUnique
설치장소명 has unique valuesUnique

Reproduction

Analysis started2024-01-28 11:30:54.158276
Analysis finished2024-01-28 11:30:54.483730
Duration0.33 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

연번
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct90
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean45.5
Minimum1
Maximum90
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size942.0 B
2024-01-28T20:30:54.541214image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile5.45
Q123.25
median45.5
Q367.75
95-th percentile85.55
Maximum90
Range89
Interquartile range (IQR)44.5

Descriptive statistics

Standard deviation26.124701
Coefficient of variation (CV)0.57416925
Kurtosis-1.2
Mean45.5
Median Absolute Deviation (MAD)22.5
Skewness0
Sum4095
Variance682.5
MonotonicityStrictly increasing
2024-01-28T20:30:54.661997image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1 1
 
1.1%
69 1
 
1.1%
67 1
 
1.1%
66 1
 
1.1%
65 1
 
1.1%
64 1
 
1.1%
63 1
 
1.1%
62 1
 
1.1%
61 1
 
1.1%
60 1
 
1.1%
Other values (80) 80
88.9%
ValueCountFrequency (%)
1 1
1.1%
2 1
1.1%
3 1
1.1%
4 1
1.1%
5 1
1.1%
6 1
1.1%
7 1
1.1%
8 1
1.1%
9 1
1.1%
10 1
1.1%
ValueCountFrequency (%)
90 1
1.1%
89 1
1.1%
88 1
1.1%
87 1
1.1%
86 1
1.1%
85 1
1.1%
84 1
1.1%
83 1
1.1%
82 1
1.1%
81 1
1.1%

설치장소명
Text

UNIQUE 

Distinct90
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size852.0 B
2024-01-28T20:30:54.892629image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length24
Median length16
Mean length10.2
Min length4

Characters and Unicode

Total characters918
Distinct characters154
Distinct categories7 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique90 ?
Unique (%)100.0%

Sample

1st row남경포브APT앞
2nd row월미공원 앞
3rd row동인천 화평철교앞(구 중구문화원)
4th row배다리사거리 전철 담장
5th row전동교회 앞
ValueCountFrequency (%)
앞 23
 
10.6%
2 16
 
7.3%
1 16
 
7.3%
행정복지센터 14
 
6.4%
옆 10
 
4.6%
3 5
 
2.3%
입구 4
 
1.8%
수도권 3
 
1.4%
초입 3
 
1.4%
제2순환고속도로(인천-김포 3
 
1.4%
Other values (87) 121
55.5%
2024-01-28T20:30:55.249081image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
128
 
13.9%
앞 30
 
3.3%
동 29
 
3.2%
리 24
 
2.6%
1 24
 
2.6%
거 23
 
2.5%
2 22
 
2.4%
정 20
 
2.2%
사 20
 
2.2%
터 18
 
2.0%
Other values (144) 580
63.2%

Most occurring categories

ValueCountFrequency (%)
Other Letter 689
75.1%
Space Separator 128
 
13.9%
Decimal Number 63
 
6.9%
Open Punctuation 12
 
1.3%
Close Punctuation 12
 
1.3%
Dash Punctuation 7
 
0.8%
Uppercase Letter 7
 
0.8%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
앞 30
 
4.4%
동 29
 
4.2%
리 24
 
3.5%
거 23
 
3.3%
정 20
 
2.9%
사 20
 
2.9%
터 18
 
2.6%
지 17
 
2.5%
센 17
 
2.5%
원 16
 
2.3%
Other values (127) 475
68.9%
Decimal Number
ValueCountFrequency (%)
1 24
38.1%
2 22
34.9%
3 9
 
14.3%
7 3
 
4.8%
6 2
 
3.2%
4 1
 
1.6%
8 1
 
1.6%
5 1
 
1.6%
Uppercase Letter
ValueCountFrequency (%)
L 2
28.6%
H 2
28.6%
A 1
14.3%
T 1
14.3%
P 1
14.3%
Space Separator
ValueCountFrequency (%)
128
100.0%
Open Punctuation
ValueCountFrequency (%)
( 12
100.0%
Close Punctuation
ValueCountFrequency (%)
) 12
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 7
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 689
75.1%
Common 222
 
24.2%
Latin 7
 
0.8%

Most frequent character per script

Hangul
ValueCountFrequency (%)
앞 30
 
4.4%
동 29
 
4.2%
리 24
 
3.5%
거 23
 
3.3%
정 20
 
2.9%
사 20
 
2.9%
터 18
 
2.6%
지 17
 
2.5%
센 17
 
2.5%
원 16
 
2.3%
Other values (127) 475
68.9%
Common
ValueCountFrequency (%)
128
57.7%
1 24
 
10.8%
2 22
 
9.9%
( 12
 
5.4%
) 12
 
5.4%
3 9
 
4.1%
- 7
 
3.2%
7 3
 
1.4%
6 2
 
0.9%
4 1
 
0.5%
Other values (2) 2
 
0.9%
Latin
ValueCountFrequency (%)
L 2
28.6%
H 2
28.6%
A 1
14.3%
T 1
14.3%
P 1
14.3%

Most occurring blocks

ValueCountFrequency (%)
Hangul 689
75.1%
ASCII 229
 
24.9%

Most frequent character per block

ASCII
ValueCountFrequency (%)
128
55.9%
1 24
 
10.5%
2 22
 
9.6%
( 12
 
5.2%
) 12
 
5.2%
3 9
 
3.9%
- 7
 
3.1%
7 3
 
1.3%
L 2
 
0.9%
H 2
 
0.9%
Other values (7) 8
 
3.5%
Hangul
ValueCountFrequency (%)
앞 30
 
4.4%
동 29
 
4.2%
리 24
 
3.5%
거 23
 
3.3%
정 20
 
2.9%
사 20
 
2.9%
터 18
 
2.6%
지 17
 
2.5%
센 17
 
2.5%
원 16
 
2.3%
Other values (127) 475
68.9%

용도구분
Categorical

HIGH CORRELATION 

Distinct2
Distinct (%)2.2%
Missing0
Missing (%)0.0%
Memory size852.0 B
상업용
57 
공공용
33 

Length

Max length3
Median length3
Mean length3
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
상업용 57
63.3%
공공용 33
36.7%

Length

2024-01-28T20:30:55.356320image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-01-28T20:30:55.428686image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
상업용 57
63.3%
공공용 33
36.7%

데이터기준일
Date

CONSTANT 

Distinct1
Distinct (%)1.1%
Missing0
Missing (%)0.0%
Memory size852.0 B
Minimum2023-09-18 00:00:00
Maximum2023-09-18 00:00:00
2024-01-28T20:30:55.494664image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-28T20:30:55.559963image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=1)

Interactions

2024-01-28T20:30:54.307779image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-01-28T20:30:55.612786image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
연번설치장소명용도구분
연번1.0001.0000.868
설치장소명1.0001.0001.000
용도구분0.8681.0001.000
2024-01-28T20:30:55.677391image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
연번용도구분
연번1.0000.668
용도구분0.6681.000

Missing values

2024-01-28T20:30:54.395560image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-01-28T20:30:54.458780image/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.

Sample

연번설치장소명용도구분데이터기준일
01남경포브APT앞상업용2023-09-18
12월미공원 앞상업용2023-09-18
23동인천 화평철교앞(구 중구문화원)상업용2023-09-18
34배다리사거리 전철 담장상업용2023-09-18
45전동교회 앞상업용2023-09-18
56답동소공원(저단형)공공용2023-09-18
67답동소공원(고단형)상업용2023-09-18
78신포동 인천우체국 옆상업용2023-09-18
89수인사거리상업용2023-09-18
910수도권 제2순환고속도로(인천-김포) 초입 1상업용2023-09-18
연번설치장소명용도구분데이터기준일
8081영종LH7단지 앞상업용2023-09-18
8182송산배수지 옆상업용2023-09-18
8283송산공원 앞상업용2023-09-18
8384영종동 행정복지센터 앞공공용2023-09-18
8485영종동 행정복지센터 입구공공용2023-09-18
8586영종1동 행정복지센터 앞공공용2023-09-18
8687운서동 행정복지센터 앞공공용2023-09-18
8788용유동 행정복지센터 앞공공용2023-09-18
8889용유동 행정복지센터 뒤공공용2023-09-18
8990용유동 주민자치센터 부근공공용2023-09-18