Overview

Dataset statistics

Number of variables5
Number of observations45
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory1.9 KiB
Average record size in memory43.9 B

Variable types

Categorical3
Text1
Numeric1

Dataset

Description서울특별시 광진구 모래주머니 배치현황(지역구분, 행정동, 위치, 배치수량 등)으로 수방 및 제설 소모품 구비 현황과 관련한 데이터
Author서울특별시 광진구
URLhttps://www.data.go.kr/data/15041576/fileData.do

Alerts

비고 is highly overall correlated with 배치수량 and 1 other fieldsHigh correlation
구분 is highly overall correlated with 비고High correlation
배치수량 is highly overall correlated with 비고High correlation
위치 has unique valuesUnique

Reproduction

Analysis started2023-12-12 05:28:43.378621
Analysis finished2023-12-12 05:28:43.972289
Duration0.59 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

구분
Categorical

HIGH CORRELATION 

Distinct2
Distinct (%)4.4%
Missing0
Missing (%)0.0%
Memory size492.0 B
취약지역
30 
동 주민센터
15 

Length

Max length6
Median length4
Mean length4.6666667
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
취약지역 30
66.7%
동 주민센터 15
33.3%

Length

2023-12-12T14:28:44.087688image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T14:28:44.250128image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
취약지역 30
50.0%
동 15
25.0%
주민센터 15
25.0%

행정동
Categorical

Distinct18
Distinct (%)40.0%
Missing0
Missing (%)0.0%
Memory size492.0 B
능 동
6 
중곡 4동
5 
군자동
4 
자양 4동
4 
중곡 1동
3 
Other values (13)
23 

Length

Max length5
Median length5
Mean length4.3777778
Min length3

Unique

Unique7 ?
Unique (%)15.6%

Sample

1st row중곡 1동
2nd row중곡 1동
3rd row중곡 2동
4th row중곡 2동
5th row중곡 4동

Common Values

ValueCountFrequency (%)
능 동 6
13.3%
중곡 4동 5
11.1%
군자동 4
8.9%
자양 4동 4
8.9%
중곡 1동 3
 
6.7%
중곡 2동 3
 
6.7%
구의 2동 3
 
6.7%
구의 3동 3
 
6.7%
자양 1동 3
 
6.7%
광장동 2
 
4.4%
Other values (8) 9
20.0%

Length

2023-12-12T14:28:44.393624image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
중곡 12
14.1%
4동 9
10.6%
동 9
10.6%
자양 9
10.6%
구의 7
8.2%
1동 7
8.2%
2동 7
8.2%
능 6
7.1%
3동 5
5.9%
군자동 4
 
4.7%
Other values (8) 10
11.8%

위치
Text

UNIQUE 

Distinct45
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size492.0 B
2023-12-12T14:28:44.683515image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length22
Median length21
Mean length18.888889
Min length15

Characters and Unicode

Total characters850
Distinct characters49
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

Unique45 ?
Unique (%)100.0%

Sample

1st row서울특별시 광진구 중곡1동 612-8
2nd row서울특별시 광진구 중곡1동 648-15
3rd row서울특별시 광진구 중곡2동 40-14
4th row서울특별시 광진구 중곡2동 157-8
5th row서울특별시 광진구 중곡4동 58-17
ValueCountFrequency (%)
광진구 45
24.6%
서울특별시 30
16.4%
서울시 15
 
8.2%
능동 5
 
2.7%
중곡4동 4
 
2.2%
자양4동 3
 
1.6%
군자동 3
 
1.6%
능동로 2
 
1.1%
광장동 2
 
1.1%
구의3동 2
 
1.1%
Other values (64) 72
39.3%
2023-12-12T14:28:45.170503image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
144
16.9%
구 49
 
5.8%
광 49
 
5.8%
서 45
 
5.3%
울 45
 
5.3%
시 45
 
5.3%
진 45
 
5.3%
1 37
 
4.4%
2 36
 
4.2%
동 31
 
3.6%
Other values (39) 324
38.1%

Most occurring categories

ValueCountFrequency (%)
Other Letter 479
56.4%
Decimal Number 198
23.3%
Space Separator 144
 
16.9%
Dash Punctuation 29
 
3.4%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
구 49
10.2%
광 49
10.2%
서 45
9.4%
울 45
9.4%
시 45
9.4%
진 45
9.4%
동 31
 
6.5%
특 30
 
6.3%
별 30
 
6.3%
로 18
 
3.8%
Other values (27) 92
19.2%
Decimal Number
ValueCountFrequency (%)
1 37
18.7%
2 36
18.2%
4 24
12.1%
5 22
11.1%
3 20
10.1%
6 16
8.1%
7 14
 
7.1%
8 13
 
6.6%
0 9
 
4.5%
9 7
 
3.5%
Space Separator
ValueCountFrequency (%)
144
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 29
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 479
56.4%
Common 371
43.6%

Most frequent character per script

Hangul
ValueCountFrequency (%)
구 49
10.2%
광 49
10.2%
서 45
9.4%
울 45
9.4%
시 45
9.4%
진 45
9.4%
동 31
 
6.5%
특 30
 
6.3%
별 30
 
6.3%
로 18
 
3.8%
Other values (27) 92
19.2%
Common
ValueCountFrequency (%)
144
38.8%
1 37
 
10.0%
2 36
 
9.7%
- 29
 
7.8%
4 24
 
6.5%
5 22
 
5.9%
3 20
 
5.4%
6 16
 
4.3%
7 14
 
3.8%
8 13
 
3.5%
Other values (2) 16
 
4.3%

Most occurring blocks

ValueCountFrequency (%)
Hangul 479
56.4%
ASCII 371
43.6%

Most frequent character per block

ASCII
ValueCountFrequency (%)
144
38.8%
1 37
 
10.0%
2 36
 
9.7%
- 29
 
7.8%
4 24
 
6.5%
5 22
 
5.9%
3 20
 
5.4%
6 16
 
4.3%
7 14
 
3.8%
8 13
 
3.5%
Other values (2) 16
 
4.3%
Hangul
ValueCountFrequency (%)
구 49
10.2%
광 49
10.2%
서 45
9.4%
울 45
9.4%
시 45
9.4%
진 45
9.4%
동 31
 
6.5%
특 30
 
6.3%
별 30
 
6.3%
로 18
 
3.8%
Other values (27) 92
19.2%

배치수량
Real number (ℝ)

HIGH CORRELATION 

Distinct8
Distinct (%)17.8%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean178
Minimum100
Maximum600
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size537.0 B
2023-12-12T14:28:45.339509image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum100
5-th percentile100
Q1100
median130
Q3200
95-th percentile400
Maximum600
Range500
Interquartile range (IQR)100

Descriptive statistics

Standard deviation107.77924
Coefficient of variation (CV)0.60550132
Kurtosis4.5951684
Mean178
Median Absolute Deviation (MAD)30
Skewness1.9622824
Sum8010
Variance11616.364
MonotonicityNot monotonic
2023-12-12T14:28:45.464372image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=8)
ValueCountFrequency (%)
100 21
46.7%
200 14
31.1%
400 3
 
6.7%
300 3
 
6.7%
120 1
 
2.2%
600 1
 
2.2%
160 1
 
2.2%
130 1
 
2.2%
ValueCountFrequency (%)
100 21
46.7%
120 1
 
2.2%
130 1
 
2.2%
160 1
 
2.2%
200 14
31.1%
300 3
 
6.7%
400 3
 
6.7%
600 1
 
2.2%
ValueCountFrequency (%)
600 1
 
2.2%
400 3
 
6.7%
300 3
 
6.7%
200 14
31.1%
160 1
 
2.2%
130 1
 
2.2%
120 1
 
2.2%
100 21
46.7%

비고
Categorical

HIGH CORRELATION 

Distinct6
Distinct (%)13.3%
Missing0
Missing (%)0.0%
Memory size492.0 B
<NA>
32 
2개소
9 
2개소(구의문 주차장)
 
1
2개소(건대입구역)
 
1
2개소(현대아파트)
 
1

Length

Max length12
Median length4
Mean length4.2888889
Min length3

Unique

Unique4 ?
Unique (%)8.9%

Sample

1st row<NA>
2nd row<NA>
3rd row<NA>
4th row<NA>
5th row<NA>

Common Values

ValueCountFrequency (%)
<NA> 32
71.1%
2개소 9
 
20.0%
2개소(구의문 주차장) 1
 
2.2%
2개소(건대입구역) 1
 
2.2%
2개소(현대아파트) 1
 
2.2%
세종초등학교 1
 
2.2%

Length

2023-12-12T14:28:45.611452image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T14:28:45.746468image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 32
69.6%
2개소 9
 
19.6%
2개소(구의문 1
 
2.2%
주차장 1
 
2.2%
2개소(건대입구역 1
 
2.2%
2개소(현대아파트 1
 
2.2%
세종초등학교 1
 
2.2%

Interactions

2023-12-12T14:28:43.643815image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-12T14:28:45.853642image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
구분행정동위치배치수량비고
구분1.0000.3611.0000.343NaN
행정동0.3611.0001.0000.6740.000
위치1.0001.0001.0001.0001.000
배치수량0.3430.6741.0001.0000.718
비고NaN0.0001.0000.7181.000
2023-12-12T14:28:45.967707image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
행정동비고구분
행정동1.0000.0000.207
비고0.0001.0001.000
구분0.2071.0001.000
2023-12-12T14:28:46.065477image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
배치수량구분행정동비고
배치수량1.0000.4020.3380.621
구분0.4021.0000.2071.000
행정동0.3380.2071.0000.000
비고0.6211.0000.0001.000

Missing values

2023-12-12T14:28:43.790236image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-12T14:28:43.923976image/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

구분행정동위치배치수량비고
0취약지역중곡 1동서울특별시 광진구 중곡1동 612-8100<NA>
1취약지역중곡 1동서울특별시 광진구 중곡1동 648-15100<NA>
2취약지역중곡 2동서울특별시 광진구 중곡2동 40-14100<NA>
3취약지역중곡 2동서울특별시 광진구 중곡2동 157-8100<NA>
4취약지역중곡 4동서울특별시 광진구 중곡4동 58-17100<NA>
5취약지역중곡 4동서울특별시 광진구 중곡4동 58-27100<NA>
6취약지역중곡 4동서울특별시 광진구 중곡4동 63-162002개소
7취약지역중곡 4동서울특별시 광진구 중곡4동 109-2100<NA>
8취약지역능 동서울특별시 광진구 능동 279-2100<NA>
9취약지역능 동서울특별시 광진구 능동 220-6100<NA>
구분행정동위치배치수량비고
35동 주민센터구의 1동서울시 광진구 광나루로36길 56200<NA>
36동 주민센터구의 2동서울시 광진구 천호대로136길 55100<NA>
37동 주민센터구의 3동서울시 광진구 강변역로 17200<NA>
38동 주민센터광 장 동서울시 광진구 광장로 52 02-450-600<NA>
39동 주민센터자양 1동서울시 광진구 자양로 13길37200<NA>
40동 주민센터자양 2동서울시 광진구 자양로 3가길 26160<NA>
41동 주민센터자양 3동서울시 광진구 뚝섬로 568130<NA>
42동 주민센터자양 4동서울시 광진구 뚝섬로 26길 58200<NA>
43동 주민센터화 양 동서울시 광진구 능동로 17길39200<NA>
44동 주민센터군 자 동서울시 광진구 군자로 151100<NA>