Overview

Dataset statistics

Number of variables7
Number of observations10000
Missing cells29979
Missing cells (%)42.8%
Duplicate rows1
Duplicate rows (%)< 0.1%
Total size in memory634.8 KiB
Average record size in memory65.0 B

Variable types

Text2
Categorical4
DateTime1

Dataset

Description경상남도 의령군의 제설함 정보를 제공하는 데이터 입니다. 제설함이 설치된 설치장소(설치구역), 소재지 주소, 제설함 수, 염화칼슘 비치량, 관리기관명과 전화번호 정보를 제공합니다.
Author경상남도 의령군
URLhttps://www.data.go.kr/data/15099440/fileData.do

Alerts

데이터기준일 has constant value ""Constant
Dataset has 1 (< 0.1%) duplicate rowsDuplicates
관리기관명 is highly overall correlated with 제설함 수 and 2 other fieldsHigh correlation
관리기관 전화번호 is highly overall correlated with 제설함 수 and 2 other fieldsHigh correlation
염화칼슘 비치량 is highly overall correlated with 제설함 수 and 2 other fieldsHigh correlation
제설함 수 is highly overall correlated with 염화칼슘 비치량 and 2 other fieldsHigh correlation
제설함 수 is highly imbalanced (99.2%)Imbalance
염화칼슘 비치량 is highly imbalanced (99.2%)Imbalance
관리기관명 is highly imbalanced (99.2%)Imbalance
관리기관 전화번호 is highly imbalanced (99.2%)Imbalance
설치장소명(설치구역) has 9993 (99.9%) missing valuesMissing
소재지 주소 has 9993 (99.9%) missing valuesMissing
데이터기준일 has 9993 (99.9%) missing valuesMissing

Reproduction

Analysis started2024-03-14 13:30:48.203415
Analysis finished2024-03-14 13:30:50.023092
Duration1.82 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

설치장소명(설치구역)
Text

MISSING 

Distinct7
Distinct (%)100.0%
Missing9993
Missing (%)99.9%
Memory size156.2 KiB
2024-03-14T22:30:50.460156image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length22
Median length21
Mean length19.571429
Min length18

Characters and Unicode

Total characters137
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

Unique7 ?
Unique (%)100.0%

Sample

1st row경상남도 의령군 유곡면 오목리산24
2nd row경상남도 의령군 정곡면 중교리1547-8
3rd row경상남도 의령군 의령읍 중리813
4th row경상남도 의령군 유곡면 오목리59
5th row경상남도 의령군 봉수면 신현리257-2
ValueCountFrequency (%)
경상남도 7
24.1%
의령군 7
24.1%
유곡면 3
10.3%
의령읍 2
 
6.9%
오목리산24 1
 
3.4%
정곡면 1
 
3.4%
중교리1547-8 1
 
3.4%
중리813 1
 
3.4%
오목리59 1
 
3.4%
봉수면 1
 
3.4%
Other values (4) 4
13.8%
2024-03-14T22:30:51.536842image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
22
16.1%
의 9
 
6.6%
령 9
 
6.6%
경 7
 
5.1%
리 7
 
5.1%
남 7
 
5.1%
도 7
 
5.1%
군 7
 
5.1%
상 7
 
5.1%
면 5
 
3.6%
Other values (23) 50
36.5%

Most occurring categories

ValueCountFrequency (%)
Other Letter 90
65.7%
Space Separator 22
 
16.1%
Decimal Number 22
 
16.1%
Dash Punctuation 3
 
2.2%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
의 9
10.0%
령 9
10.0%
경 7
 
7.8%
리 7
 
7.8%
남 7
 
7.8%
도 7
 
7.8%
군 7
 
7.8%
상 7
 
7.8%
면 5
 
5.6%
곡 4
 
4.4%
Other values (12) 21
23.3%
Decimal Number
ValueCountFrequency (%)
1 4
18.2%
2 4
18.2%
5 4
18.2%
9 2
9.1%
8 2
9.1%
4 2
9.1%
7 2
9.1%
3 1
 
4.5%
0 1
 
4.5%
Space Separator
ValueCountFrequency (%)
22
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 3
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 90
65.7%
Common 47
34.3%

Most frequent character per script

Hangul
ValueCountFrequency (%)
의 9
10.0%
령 9
10.0%
경 7
 
7.8%
리 7
 
7.8%
남 7
 
7.8%
도 7
 
7.8%
군 7
 
7.8%
상 7
 
7.8%
면 5
 
5.6%
곡 4
 
4.4%
Other values (12) 21
23.3%
Common
ValueCountFrequency (%)
22
46.8%
1 4
 
8.5%
2 4
 
8.5%
5 4
 
8.5%
- 3
 
6.4%
9 2
 
4.3%
8 2
 
4.3%
4 2
 
4.3%
7 2
 
4.3%
3 1
 
2.1%

Most occurring blocks

ValueCountFrequency (%)
Hangul 90
65.7%
ASCII 47
34.3%

Most frequent character per block

ASCII
ValueCountFrequency (%)
22
46.8%
1 4
 
8.5%
2 4
 
8.5%
5 4
 
8.5%
- 3
 
6.4%
9 2
 
4.3%
8 2
 
4.3%
4 2
 
4.3%
7 2
 
4.3%
3 1
 
2.1%
Hangul
ValueCountFrequency (%)
의 9
10.0%
령 9
10.0%
경 7
 
7.8%
리 7
 
7.8%
남 7
 
7.8%
도 7
 
7.8%
군 7
 
7.8%
상 7
 
7.8%
면 5
 
5.6%
곡 4
 
4.4%
Other values (12) 21
23.3%

소재지 주소
Text

MISSING 

Distinct7
Distinct (%)100.0%
Missing9993
Missing (%)99.9%
Memory size156.2 KiB
2024-03-14T22:30:52.140018image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length13
Median length12
Mean length10.571429
Min length9

Characters and Unicode

Total characters74
Distinct characters28
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

Unique7 ?
Unique (%)100.0%

Sample

1st row유곡면 오목리산24
2nd row정곡면 중교리1547-8
3rd row의령읍 중리813
4th row유곡면 오목리59
5th row봉수면 신현리257-2
ValueCountFrequency (%)
유곡면 3
20.0%
의령읍 2
13.3%
오목리산24 1
 
6.7%
정곡면 1
 
6.7%
중교리1547-8 1
 
6.7%
중리813 1
 
6.7%
오목리59 1
 
6.7%
봉수면 1
 
6.7%
신현리257-2 1
 
6.7%
중리 1
 
6.7%
Other values (2) 2
13.3%
2024-03-14T22:30:53.114086image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
8
 
10.8%
리 7
 
9.5%
면 5
 
6.8%
5 4
 
5.4%
곡 4
 
5.4%
1 4
 
5.4%
2 4
 
5.4%
중 3
 
4.1%
- 3
 
4.1%
유 3
 
4.1%
Other values (18) 29
39.2%

Most occurring categories

ValueCountFrequency (%)
Other Letter 41
55.4%
Decimal Number 22
29.7%
Space Separator 8
 
10.8%
Dash Punctuation 3
 
4.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
리 7
17.1%
면 5
12.2%
곡 4
9.8%
중 3
7.3%
유 3
7.3%
목 3
7.3%
오 3
7.3%
령 2
 
4.9%
의 2
 
4.9%
읍 2
 
4.9%
Other values (7) 7
17.1%
Decimal Number
ValueCountFrequency (%)
5 4
18.2%
1 4
18.2%
2 4
18.2%
7 2
9.1%
8 2
9.1%
4 2
9.1%
9 2
9.1%
3 1
 
4.5%
0 1
 
4.5%
Space Separator
ValueCountFrequency (%)
8
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 3
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 41
55.4%
Common 33
44.6%

Most frequent character per script

Hangul
ValueCountFrequency (%)
리 7
17.1%
면 5
12.2%
곡 4
9.8%
중 3
7.3%
유 3
7.3%
목 3
7.3%
오 3
7.3%
령 2
 
4.9%
의 2
 
4.9%
읍 2
 
4.9%
Other values (7) 7
17.1%
Common
ValueCountFrequency (%)
8
24.2%
5 4
12.1%
1 4
12.1%
2 4
12.1%
- 3
 
9.1%
7 2
 
6.1%
8 2
 
6.1%
4 2
 
6.1%
9 2
 
6.1%
3 1
 
3.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 41
55.4%
ASCII 33
44.6%

Most frequent character per block

ASCII
ValueCountFrequency (%)
8
24.2%
5 4
12.1%
1 4
12.1%
2 4
12.1%
- 3
 
9.1%
7 2
 
6.1%
8 2
 
6.1%
4 2
 
6.1%
9 2
 
6.1%
3 1
 
3.0%
Hangul
ValueCountFrequency (%)
리 7
17.1%
면 5
12.2%
곡 4
9.8%
중 3
7.3%
유 3
7.3%
목 3
7.3%
오 3
7.3%
령 2
 
4.9%
의 2
 
4.9%
읍 2
 
4.9%
Other values (7) 7
17.1%

제설함 수
Categorical

HIGH CORRELATION  IMBALANCE 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
<NA>
9993 
1
 
7

Length

Max length4
Median length4
Mean length3.9979
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 9993
99.9%
1 7
 
0.1%

Length

2024-03-14T22:30:53.340546image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-14T22:30:53.515584image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 9993
99.9%
1 7
 
0.1%

염화칼슘 비치량
Categorical

HIGH CORRELATION  IMBALANCE 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
<NA>
9993 
25kg 5포
 
7

Length

Max length7
Median length4
Mean length4.0021
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 9993
99.9%
25kg 5포 7
 
0.1%

Length

2024-03-14T22:30:53.843144image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-14T22:30:54.155718image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 9993
99.9%
25kg 7
 
0.1%
5포 7
 
0.1%

관리기관명
Categorical

HIGH CORRELATION  IMBALANCE 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
<NA>
9993 
의령군 건설과
 
7

Length

Max length7
Median length4
Mean length4.0021
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 9993
99.9%
의령군 건설과 7
 
0.1%

Length

2024-03-14T22:30:54.498093image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-14T22:30:54.812731image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 9993
99.9%
의령군 7
 
0.1%
건설과 7
 
0.1%

관리기관 전화번호
Categorical

HIGH CORRELATION  IMBALANCE 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
<NA>
9993 
055-570-3614
 
7

Length

Max length12
Median length4
Mean length4.0056
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 9993
99.9%
055-570-3614 7
 
0.1%

Length

2024-03-14T22:30:55.176096image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-14T22:30:55.502689image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 9993
99.9%
055-570-3614 7
 
0.1%

데이터기준일
Date

CONSTANT  MISSING 

Distinct1
Distinct (%)14.3%
Missing9993
Missing (%)99.9%
Memory size156.2 KiB
Minimum2024-03-05 00:00:00
Maximum2024-03-05 00:00:00
2024-03-14T22:30:55.760972image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T22:30:56.074030image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=1)

Correlations

2024-03-14T22:30:56.281969image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
설치장소명(설치구역)소재지 주소
설치장소명(설치구역)1.0001.000
소재지 주소1.0001.000
2024-03-14T22:30:56.521600image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
관리기관명관리기관 전화번호염화칼슘 비치량제설함 수
관리기관명1.0001.0001.0001.000
관리기관 전화번호1.0001.0001.0001.000
염화칼슘 비치량1.0001.0001.0001.000
제설함 수1.0001.0001.0001.000
2024-03-14T22:30:56.780665image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
제설함 수염화칼슘 비치량관리기관명관리기관 전화번호
제설함 수1.0001.0001.0001.000
염화칼슘 비치량1.0001.0001.0001.000
관리기관명1.0001.0001.0001.000
관리기관 전화번호1.0001.0001.0001.000

Missing values

2024-03-14T22:30:48.794945image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-03-14T22:30:49.211563image/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.
2024-03-14T22:30:49.789874image/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

설치장소명(설치구역)소재지 주소제설함 수염화칼슘 비치량관리기관명관리기관 전화번호데이터기준일
12610<NA><NA><NA><NA><NA><NA><NA>
82258<NA><NA><NA><NA><NA><NA><NA>
71677<NA><NA><NA><NA><NA><NA><NA>
78637<NA><NA><NA><NA><NA><NA><NA>
54002<NA><NA><NA><NA><NA><NA><NA>
41256<NA><NA><NA><NA><NA><NA><NA>
21765<NA><NA><NA><NA><NA><NA><NA>
3236<NA><NA><NA><NA><NA><NA><NA>
25953<NA><NA><NA><NA><NA><NA><NA>
20641<NA><NA><NA><NA><NA><NA><NA>
설치장소명(설치구역)소재지 주소제설함 수염화칼슘 비치량관리기관명관리기관 전화번호데이터기준일
80288<NA><NA><NA><NA><NA><NA><NA>
67129<NA><NA><NA><NA><NA><NA><NA>
23763<NA><NA><NA><NA><NA><NA><NA>
21865<NA><NA><NA><NA><NA><NA><NA>
15074<NA><NA><NA><NA><NA><NA><NA>
6614<NA><NA><NA><NA><NA><NA><NA>
60186<NA><NA><NA><NA><NA><NA><NA>
73190<NA><NA><NA><NA><NA><NA><NA>
4952<NA><NA><NA><NA><NA><NA><NA>
10453<NA><NA><NA><NA><NA><NA><NA>

Duplicate rows

Most frequently occurring

설치장소명(설치구역)소재지 주소제설함 수염화칼슘 비치량관리기관명관리기관 전화번호데이터기준일# duplicates
0<NA><NA><NA><NA><NA><NA><NA>9993