Overview

Dataset statistics

Number of variables5
Number of observations21
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory1.0 KiB
Average record size in memory49.3 B

Variable types

Numeric3
Text1
Categorical1

Dataset

Description남동구 기관별 옥외광고물 클린봉사단에 대한 연번, 기관명, 등록인원, 2022년 예산, 데이터기준일 등을 제공합니다.
Author인천광역시 남동구
URLhttps://data.incheon.go.kr/findData/publicDataDetail?dataId=15086148&srcSe=7661IVAWM27C61E190

Alerts

데이터기준일 has constant value ""Constant
등록인원 is highly overall correlated with 2023년 예산(천원)High correlation
2023년 예산(천원) is highly overall correlated with 등록인원High correlation
연번 has unique valuesUnique
기관명 has unique valuesUnique
등록인원 has 1 (4.8%) zerosZeros
2023년 예산(천원) has 1 (4.8%) zerosZeros

Reproduction

Analysis started2024-04-17 10:55:11.527182
Analysis finished2024-04-17 10:55:12.313357
Duration0.79 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

연번
Real number (ℝ)

UNIQUE 

Distinct21
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean11
Minimum1
Maximum21
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size321.0 B
2024-04-17T19:55:12.356724image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile2
Q16
median11
Q316
95-th percentile20
Maximum21
Range20
Interquartile range (IQR)10

Descriptive statistics

Standard deviation6.2048368
Coefficient of variation (CV)0.56407607
Kurtosis-1.2
Mean11
Median Absolute Deviation (MAD)5
Skewness0
Sum231
Variance38.5
MonotonicityStrictly increasing
2024-04-17T19:55:12.446401image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=21)
ValueCountFrequency (%)
1 1
 
4.8%
2 1
 
4.8%
21 1
 
4.8%
20 1
 
4.8%
19 1
 
4.8%
18 1
 
4.8%
17 1
 
4.8%
16 1
 
4.8%
15 1
 
4.8%
14 1
 
4.8%
Other values (11) 11
52.4%
ValueCountFrequency (%)
1 1
4.8%
2 1
4.8%
3 1
4.8%
4 1
4.8%
5 1
4.8%
6 1
4.8%
7 1
4.8%
8 1
4.8%
9 1
4.8%
10 1
4.8%
ValueCountFrequency (%)
21 1
4.8%
20 1
4.8%
19 1
4.8%
18 1
4.8%
17 1
4.8%
16 1
4.8%
15 1
4.8%
14 1
4.8%
13 1
4.8%
12 1
4.8%

기관명
Text

UNIQUE 

Distinct21
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size300.0 B
2024-04-17T19:55:12.597580image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length5
Median length4
Mean length4.1904762
Min length4

Characters and Unicode

Total characters88
Distinct characters29
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

Unique21 ?
Unique (%)100.0%

Sample

1st row구월1동
2nd row구월2동
3rd row구월3동
4th row구월4동
5th row간석1동
ValueCountFrequency (%)
구월1동 1
 
4.8%
만수4동 1
 
4.8%
논현고잔동 1
 
4.8%
논현2동 1
 
4.8%
논현1동 1
 
4.8%
남촌도림동 1
 
4.8%
서창2동 1
 
4.8%
장수서창동 1
 
4.8%
만수6동 1
 
4.8%
만수5동 1
 
4.8%
Other values (11) 11
52.4%
2024-04-17T19:55:12.850745image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
동 20
22.7%
수 7
 
8.0%
만 6
 
6.8%
2 5
 
5.7%
구 4
 
4.5%
월 4
 
4.5%
1 4
 
4.5%
간 4
 
4.5%
석 4
 
4.5%
3 3
 
3.4%
Other values (19) 27
30.7%

Most occurring categories

ValueCountFrequency (%)
Other Letter 71
80.7%
Decimal Number 17
 
19.3%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
동 20
28.2%
수 7
 
9.9%
만 6
 
8.5%
구 4
 
5.6%
월 4
 
5.6%
간 4
 
5.6%
석 4
 
5.6%
현 3
 
4.2%
논 3
 
4.2%
창 2
 
2.8%
Other values (13) 14
19.7%
Decimal Number
ValueCountFrequency (%)
2 5
29.4%
1 4
23.5%
3 3
17.6%
4 3
17.6%
6 1
 
5.9%
5 1
 
5.9%

Most occurring scripts

ValueCountFrequency (%)
Hangul 71
80.7%
Common 17
 
19.3%

Most frequent character per script

Hangul
ValueCountFrequency (%)
동 20
28.2%
수 7
 
9.9%
만 6
 
8.5%
구 4
 
5.6%
월 4
 
5.6%
간 4
 
5.6%
석 4
 
5.6%
현 3
 
4.2%
논 3
 
4.2%
창 2
 
2.8%
Other values (13) 14
19.7%
Common
ValueCountFrequency (%)
2 5
29.4%
1 4
23.5%
3 3
17.6%
4 3
17.6%
6 1
 
5.9%
5 1
 
5.9%

Most occurring blocks

ValueCountFrequency (%)
Hangul 71
80.7%
ASCII 17
 
19.3%

Most frequent character per block

Hangul
ValueCountFrequency (%)
동 20
28.2%
수 7
 
9.9%
만 6
 
8.5%
구 4
 
5.6%
월 4
 
5.6%
간 4
 
5.6%
석 4
 
5.6%
현 3
 
4.2%
논 3
 
4.2%
창 2
 
2.8%
Other values (13) 14
19.7%
ASCII
ValueCountFrequency (%)
2 5
29.4%
1 4
23.5%
3 3
17.6%
4 3
17.6%
6 1
 
5.9%
5 1
 
5.9%

등록인원
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct17
Distinct (%)81.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean17.380952
Minimum0
Maximum46
Zeros1
Zeros (%)4.8%
Negative0
Negative (%)0.0%
Memory size321.0 B
2024-04-17T19:55:12.943095image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile1
Q110
median16
Q320
95-th percentile44
Maximum46
Range46
Interquartile range (IQR)10

Descriptive statistics

Standard deviation12.03111
Coefficient of variation (CV)0.69220088
Kurtosis1.119307
Mean17.380952
Median Absolute Deviation (MAD)6
Skewness1.005075
Sum365
Variance144.74762
MonotonicityNot monotonic
2024-04-17T19:55:13.032040image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=17)
ValueCountFrequency (%)
20 3
14.3%
13 2
 
9.5%
18 2
 
9.5%
15 1
 
4.8%
16 1
 
4.8%
0 1
 
4.8%
22 1
 
4.8%
6 1
 
4.8%
10 1
 
4.8%
12 1
 
4.8%
Other values (7) 7
33.3%
ValueCountFrequency (%)
0 1
4.8%
1 1
4.8%
5 1
4.8%
6 1
4.8%
9 1
4.8%
10 1
4.8%
12 1
4.8%
13 2
9.5%
15 1
4.8%
16 1
4.8%
ValueCountFrequency (%)
46 1
 
4.8%
44 1
 
4.8%
32 1
 
4.8%
25 1
 
4.8%
22 1
 
4.8%
20 3
14.3%
18 2
9.5%
16 1
 
4.8%
15 1
 
4.8%
13 2
9.5%

2023년 예산(천원)
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct16
Distinct (%)76.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean5319.0476
Minimum0
Maximum10800
Zeros1
Zeros (%)4.8%
Negative0
Negative (%)0.0%
Memory size321.0 B
2024-04-17T19:55:13.126088image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile300
Q12500
median5000
Q39000
95-th percentile10000
Maximum10800
Range10800
Interquartile range (IQR)6500

Descriptive statistics

Standard deviation3777.912
Coefficient of variation (CV)0.71026098
Kurtosis-1.691246
Mean5319.0476
Median Absolute Deviation (MAD)3800
Skewness-0.0059031088
Sum111700
Variance14272619
MonotonicityNot monotonic
2024-04-17T19:55:13.213534image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=16)
ValueCountFrequency (%)
2500 3
14.3%
9500 2
 
9.5%
300 2
 
9.5%
9000 2
 
9.5%
0 1
 
4.8%
6700 1
 
4.8%
10800 1
 
4.8%
1500 1
 
4.8%
8000 1
 
4.8%
3700 1
 
4.8%
Other values (6) 6
28.6%
ValueCountFrequency (%)
0 1
 
4.8%
300 2
9.5%
1200 1
 
4.8%
1500 1
 
4.8%
2500 3
14.3%
3000 1
 
4.8%
3700 1
 
4.8%
5000 1
 
4.8%
6700 1
 
4.8%
7400 1
 
4.8%
ValueCountFrequency (%)
10800 1
4.8%
10000 1
4.8%
9500 2
9.5%
9300 1
4.8%
9000 2
9.5%
8000 1
4.8%
7400 1
4.8%
6700 1
4.8%
5000 1
4.8%
3700 1
4.8%

데이터기준일
Categorical

CONSTANT 

Distinct1
Distinct (%)4.8%
Missing0
Missing (%)0.0%
Memory size300.0 B
2023-05-12
21 

Length

Max length10
Median length10
Mean length10
Min length10

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row2023-05-12
2nd row2023-05-12
3rd row2023-05-12
4th row2023-05-12
5th row2023-05-12

Common Values

ValueCountFrequency (%)
2023-05-12 21
100.0%

Length

2024-04-17T19:55:13.304424image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T19:55:13.380073image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2023-05-12 21
100.0%

Interactions

2024-04-17T19:55:12.008560image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T19:55:11.623402image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T19:55:11.832205image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T19:55:12.077167image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T19:55:11.708918image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T19:55:11.896720image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T19:55:12.134798image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T19:55:11.767939image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T19:55:11.949887image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-04-17T19:55:13.426944image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
연번기관명등록인원2023년 예산(천원)
연번1.0001.0000.5330.000
기관명1.0001.0001.0001.000
등록인원0.5331.0001.0000.476
2023년 예산(천원)0.0001.0000.4761.000
2024-04-17T19:55:13.498645image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
연번등록인원2023년 예산(천원)
연번1.000-0.232-0.226
등록인원-0.2321.0000.545
2023년 예산(천원)-0.2260.5451.000

Missing values

2024-04-17T19:55:12.211958image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-04-17T19:55:12.284963image/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

연번기관명등록인원2023년 예산(천원)데이터기준일
01구월1동1595002023-05-12
12구월2동46100002023-05-12
23구월3동2030002023-05-12
34구월4동112002023-05-12
45간석1동1393002023-05-12
56간석2동53002023-05-12
67간석3동1874002023-05-12
78간석4동2590002023-05-12
89만수1동4490002023-05-12
910만수2동3237002023-05-12
연번기관명등록인원2023년 예산(천원)데이터기준일
1112만수4동93002023-05-12
1213만수5동1625002023-05-12
1314만수6동1880002023-05-12
1415장수서창동1215002023-05-12
1516서창2동1025002023-05-12
1617남촌도림동695002023-05-12
1718논현1동20108002023-05-12
1819논현2동2225002023-05-12
1920논현고잔동1367002023-05-12
2021공단사업소002023-05-12