Overview

Dataset statistics

Number of variables12
Number of observations21
Missing cells1
Missing cells (%)0.4%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory2.2 KiB
Average record size in memory106.3 B

Variable types

Numeric3
Text3
Categorical6

Dataset

Description영천시 강우량 시설의 장소명, 소재지도로명주소, 수량, 설치시설구분, 좌표, 관리기관명, 관리기관전화번호 등 데이터를 제공합니다.
Author경상북도 영천시
URLhttps://www.data.go.kr/data/15110249/fileData.do

Alerts

수량 has constant value ""Constant
관리기관명 has constant value ""Constant
관리기관전화번호 has constant value ""Constant
담당부서명 has constant value ""Constant
데이터기준일자 has constant value ""Constant
소재지도로명주소 has 1 (4.8%) missing valuesMissing
연번 has unique valuesUnique
장소명 has unique valuesUnique
소재지지번주소 has unique valuesUnique
좌표정보(X) has unique valuesUnique
좌표정보(Y) has unique valuesUnique

Reproduction

Analysis started2023-12-16 15:21:58.178628
Analysis finished2023-12-16 15:22:05.109008
Duration6.93 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
2023-12-16T15:22:05.333708image/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
2023-12-16T15:22:06.124820image/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%

장소명
Text

UNIQUE 

Distinct21
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size300.0 B
2023-12-16T15:22:07.275702image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length8
Median length6
Mean length5.952381
Min length4

Characters and Unicode

Total characters125
Distinct characters54
Distinct categories3 ?
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 row영천시청
2nd row청통면사무소
3rd row신녕면사무소
4th row화산면사무소
5th row고경면사무소
ValueCountFrequency (%)
영천시청 1
 
4.2%
청통면사무소 1
 
4.2%
신녕면 1
 
4.2%
경로당 1
 
4.2%
범어동 1
 
4.2%
직천리회관 1
 
4.2%
천문대 1
 
4.2%
보현산 1
 
4.2%
상리노인정 1
 
4.2%
덕정리마을회관 1
 
4.2%
Other values (14) 14
58.3%
2023-12-16T15:22:09.433641image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
소 11
 
8.8%
면 11
 
8.8%
사 11
 
8.8%
무 11
 
8.8%
천 4
 
3.2%
리 4
 
3.2%
경 4
 
3.2%
로 3
 
2.4%
3
 
2.4%
당 3
 
2.4%
Other values (44) 60
48.0%

Most occurring categories

ValueCountFrequency (%)
Other Letter 121
96.8%
Space Separator 3
 
2.4%
Decimal Number 1
 
0.8%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
소 11
 
9.1%
면 11
 
9.1%
사 11
 
9.1%
무 11
 
9.1%
천 4
 
3.3%
리 4
 
3.3%
경 4
 
3.3%
로 3
 
2.5%
당 3
 
2.5%
관 3
 
2.5%
Other values (42) 56
46.3%
Space Separator
ValueCountFrequency (%)
3
100.0%
Decimal Number
ValueCountFrequency (%)
2 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 121
96.8%
Common 4
 
3.2%

Most frequent character per script

Hangul
ValueCountFrequency (%)
소 11
 
9.1%
면 11
 
9.1%
사 11
 
9.1%
무 11
 
9.1%
천 4
 
3.3%
리 4
 
3.3%
경 4
 
3.3%
로 3
 
2.5%
당 3
 
2.5%
관 3
 
2.5%
Other values (42) 56
46.3%
Common
ValueCountFrequency (%)
3
75.0%
2 1
 
25.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 121
96.8%
ASCII 4
 
3.2%

Most frequent character per block

Hangul
ValueCountFrequency (%)
소 11
 
9.1%
면 11
 
9.1%
사 11
 
9.1%
무 11
 
9.1%
천 4
 
3.3%
리 4
 
3.3%
경 4
 
3.3%
로 3
 
2.5%
당 3
 
2.5%
관 3
 
2.5%
Other values (42) 56
46.3%
ASCII
ValueCountFrequency (%)
3
75.0%
2 1
 
25.0%

소재지도로명주소
Text

MISSING 

Distinct20
Distinct (%)100.0%
Missing1
Missing (%)4.8%
Memory size300.0 B
2023-12-16T15:22:10.294366image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length46
Median length34.5
Mean length30.85
Min length18

Characters and Unicode

Total characters617
Distinct characters85
Distinct categories7 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique20 ?
Unique (%)100.0%

Sample

1st row경상북도 영천시 시청로 16 (문외동, 영천시청)
2nd row경상북도 영천시 청통면 금송로 978 (청통면, 청통면사무소)
3rd row경상북도 영천시 신녕면 화성중앙길 30 (신녕면, 신녕면사무소)
4th row경상북도 영천시 화산면 연지길 16 (화산면, 화산면사무소)
5th row경상북도 영천시 고경면 호국로 1065-23 (고경면, 6.25참전유공자고경면분회)
ValueCountFrequency (%)
경상북도 20
 
15.6%
영천시 20
 
15.6%
화북면 4
 
3.1%
금호읍 4
 
3.1%
청통면 4
 
3.1%
북안면 4
 
3.1%
임고면 4
 
3.1%
대창면 3
 
2.3%
고경면 3
 
2.3%
화산면 2
 
1.6%
Other values (54) 60
46.9%
2023-12-16T15:22:11.813815image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
108
 
17.5%
면 36
 
5.8%
북 32
 
5.2%
경 27
 
4.4%
시 22
 
3.6%
상 21
 
3.4%
영 21
 
3.4%
천 21
 
3.4%
1 20
 
3.2%
도 20
 
3.2%
Other values (75) 289
46.8%

Most occurring categories

ValueCountFrequency (%)
Other Letter 382
61.9%
Space Separator 108
 
17.5%
Decimal Number 74
 
12.0%
Open Punctuation 17
 
2.8%
Close Punctuation 17
 
2.8%
Other Punctuation 13
 
2.1%
Dash Punctuation 6
 
1.0%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
면 36
 
9.4%
북 32
 
8.4%
경 27
 
7.1%
시 22
 
5.8%
상 21
 
5.5%
영 21
 
5.5%
천 21
 
5.5%
도 20
 
5.2%
로 16
 
4.2%
화 13
 
3.4%
Other values (59) 153
40.1%
Decimal Number
ValueCountFrequency (%)
1 20
27.0%
3 9
12.2%
5 8
 
10.8%
9 7
 
9.5%
6 7
 
9.5%
7 6
 
8.1%
2 6
 
8.1%
4 5
 
6.8%
0 4
 
5.4%
8 2
 
2.7%
Other Punctuation
ValueCountFrequency (%)
, 12
92.3%
. 1
 
7.7%
Space Separator
ValueCountFrequency (%)
108
100.0%
Open Punctuation
ValueCountFrequency (%)
( 17
100.0%
Close Punctuation
ValueCountFrequency (%)
) 17
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 6
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 382
61.9%
Common 235
38.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
면 36
 
9.4%
북 32
 
8.4%
경 27
 
7.1%
시 22
 
5.8%
상 21
 
5.5%
영 21
 
5.5%
천 21
 
5.5%
도 20
 
5.2%
로 16
 
4.2%
화 13
 
3.4%
Other values (59) 153
40.1%
Common
ValueCountFrequency (%)
108
46.0%
1 20
 
8.5%
( 17
 
7.2%
) 17
 
7.2%
, 12
 
5.1%
3 9
 
3.8%
5 8
 
3.4%
9 7
 
3.0%
6 7
 
3.0%
7 6
 
2.6%
Other values (6) 24
 
10.2%

Most occurring blocks

ValueCountFrequency (%)
Hangul 382
61.9%
ASCII 235
38.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
108
46.0%
1 20
 
8.5%
( 17
 
7.2%
) 17
 
7.2%
, 12
 
5.1%
3 9
 
3.8%
5 8
 
3.4%
9 7
 
3.0%
6 7
 
3.0%
7 6
 
2.6%
Other values (6) 24
 
10.2%
Hangul
ValueCountFrequency (%)
면 36
 
9.4%
북 32
 
8.4%
경 27
 
7.1%
시 22
 
5.8%
상 21
 
5.5%
영 21
 
5.5%
천 21
 
5.5%
도 20
 
5.2%
로 16
 
4.2%
화 13
 
3.4%
Other values (59) 153
40.1%

소재지지번주소
Text

UNIQUE 

Distinct21
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size300.0 B
2023-12-16T15:22:12.621377image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length23
Median length22
Mean length21.047619
Min length15

Characters and Unicode

Total characters442
Distinct characters61
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 (%)100.0%

Sample

1st row경상북도 영천시 문외동 27
2nd row경상북도 영천시 청통면 치일리 14-1
3rd row경상북도 영천시 신녕면 화성리 419
4th row경상북도 영천시 화산면 유성리 1289
5th row경상북도 영천시 고경면 해선리 309-2
ValueCountFrequency (%)
경상북도 21
20.4%
영천시 21
20.4%
고경면 2
 
1.9%
화북면 2
 
1.9%
대창면 2
 
1.9%
북안면 2
 
1.9%
임고면 2
 
1.9%
549-1 2
 
1.9%
금호읍 2
 
1.9%
청통면 2
 
1.9%
Other values (44) 45
43.7%
2023-12-16T15:22:14.499991image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
82
18.6%
북 25
 
5.7%
천 24
 
5.4%
경 23
 
5.2%
상 22
 
5.0%
도 21
 
4.8%
영 21
 
4.8%
시 21
 
4.8%
리 19
 
4.3%
1 18
 
4.1%
Other values (51) 166
37.6%

Most occurring categories

ValueCountFrequency (%)
Other Letter 266
60.2%
Space Separator 82
 
18.6%
Decimal Number 79
 
17.9%
Dash Punctuation 15
 
3.4%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
북 25
 
9.4%
천 24
 
9.0%
경 23
 
8.6%
상 22
 
8.3%
도 21
 
7.9%
영 21
 
7.9%
시 21
 
7.9%
리 19
 
7.1%
면 17
 
6.4%
화 5
 
1.9%
Other values (39) 68
25.6%
Decimal Number
ValueCountFrequency (%)
1 18
22.8%
7 10
12.7%
2 9
11.4%
4 8
10.1%
3 8
10.1%
9 7
 
8.9%
6 6
 
7.6%
5 6
 
7.6%
0 4
 
5.1%
8 3
 
3.8%
Space Separator
ValueCountFrequency (%)
82
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 15
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 266
60.2%
Common 176
39.8%

Most frequent character per script

Hangul
ValueCountFrequency (%)
북 25
 
9.4%
천 24
 
9.0%
경 23
 
8.6%
상 22
 
8.3%
도 21
 
7.9%
영 21
 
7.9%
시 21
 
7.9%
리 19
 
7.1%
면 17
 
6.4%
화 5
 
1.9%
Other values (39) 68
25.6%
Common
ValueCountFrequency (%)
82
46.6%
1 18
 
10.2%
- 15
 
8.5%
7 10
 
5.7%
2 9
 
5.1%
4 8
 
4.5%
3 8
 
4.5%
9 7
 
4.0%
6 6
 
3.4%
5 6
 
3.4%
Other values (2) 7
 
4.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 266
60.2%
ASCII 176
39.8%

Most frequent character per block

ASCII
ValueCountFrequency (%)
82
46.6%
1 18
 
10.2%
- 15
 
8.5%
7 10
 
5.7%
2 9
 
5.1%
4 8
 
4.5%
3 8
 
4.5%
9 7
 
4.0%
6 6
 
3.4%
5 6
 
3.4%
Other values (2) 7
 
4.0%
Hangul
ValueCountFrequency (%)
북 25
 
9.4%
천 24
 
9.0%
경 23
 
8.6%
상 22
 
8.3%
도 21
 
7.9%
영 21
 
7.9%
시 21
 
7.9%
리 19
 
7.1%
면 17
 
6.4%
화 5
 
1.9%
Other values (39) 68
25.6%

수량
Categorical

CONSTANT 

Distinct1
Distinct (%)4.8%
Missing0
Missing (%)0.0%
Memory size300.0 B
1
21 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row1
2nd row1
3rd row1
4th row1
5th row1

Common Values

ValueCountFrequency (%)
1 21
100.0%

Length

2023-12-16T15:22:15.537661image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-16T15:22:16.288940image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
1 21
100.0%

설치시설구분
Categorical

Distinct4
Distinct (%)19.0%
Missing0
Missing (%)0.0%
Memory size300.0 B
관공서
12 
복지시설
7 
관광
 
1
다리
 
1

Length

Max length4
Median length3
Mean length3.2380952
Min length2

Unique

Unique2 ?
Unique (%)9.5%

Sample

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

Common Values

ValueCountFrequency (%)
관공서 12
57.1%
복지시설 7
33.3%
관광 1
 
4.8%
다리 1
 
4.8%

Length

2023-12-16T15:22:17.176707image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-16T15:22:17.948464image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
관공서 12
57.1%
복지시설 7
33.3%
관광 1
 
4.8%
다리 1
 
4.8%

좌표정보(X)
Real number (ℝ)

UNIQUE 

Distinct21
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean35.971217
Minimum35.52291
Maximum36.164258
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size321.0 B
2023-12-16T15:22:18.626324image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum35.52291
5-th percentile35.851199
Q135.915464
median36.001592
Q336.0553
95-th percentile36.108225
Maximum36.164258
Range0.6413477
Interquartile range (IQR)0.1398359

Descriptive statistics

Standard deviation0.13217422
Coefficient of variation (CV)0.0036744439
Kurtosis5.9869336
Mean35.971217
Median Absolute Deviation (MAD)0.0648659
Skewness-1.9307647
Sum755.39557
Variance0.017470025
MonotonicityNot monotonic
2023-12-16T15:22:19.141702image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=21)
ValueCountFrequency (%)
35.9732063 1
 
4.8%
35.99212 1
 
4.8%
36.0553 1
 
4.8%
35.52291 1
 
4.8%
35.874698 1
 
4.8%
36.1642577 1
 
4.8%
35.8511993 1
 
4.8%
35.9367265 1
 
4.8%
36.0569364 1
 
4.8%
36.0177489 1
 
4.8%
Other values (11) 11
52.4%
ValueCountFrequency (%)
35.52291 1
4.8%
35.8511993 1
4.8%
35.874698 1
4.8%
35.8758394 1
4.8%
35.8920444 1
4.8%
35.9154641 1
4.8%
35.9331099 1
4.8%
35.9367265 1
4.8%
35.9732063 1
4.8%
35.99212 1
4.8%
ValueCountFrequency (%)
36.1642577 1
4.8%
36.1082254 1
4.8%
36.0784542 1
4.8%
36.0591369 1
4.8%
36.0569364 1
4.8%
36.0553 1
4.8%
36.0452616 1
4.8%
36.0209686 1
4.8%
36.0203672 1
4.8%
36.0177489 1
4.8%

좌표정보(Y)
Real number (ℝ)

UNIQUE 

Distinct21
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean128.91643
Minimum128.57414
Maximum129.1117
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size321.0 B
2023-12-16T15:22:19.793292image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum128.57414
5-th percentile128.77716
Q1128.85233
median128.92031
Q3128.9917
95-th percentile129.10749
Maximum129.1117
Range0.5375567
Interquartile range (IQR)0.1393688

Descriptive statistics

Standard deviation0.12431884
Coefficient of variation (CV)0.00096433664
Kurtosis1.5822629
Mean128.91643
Median Absolute Deviation (MAD)0.071393
Skewness-0.82091553
Sum2707.245
Variance0.015455173
MonotonicityNot monotonic
2023-12-16T15:22:20.426539image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=21)
ValueCountFrequency (%)
128.9386614 1
 
4.8%
128.8230037 1
 
4.8%
128.7924 1
 
4.8%
128.57414 1
 
4.8%
128.9615173 1
 
4.8%
128.9765805 1
 
4.8%
128.9917022 1
 
4.8%
129.1074919 1
 
4.8%
129.1116967 1
 
4.8%
128.7771625 1
 
4.8%
Other values (11) 11
52.4%
ValueCountFrequency (%)
128.57414 1
4.8%
128.7771625 1
4.8%
128.7895551 1
4.8%
128.7924 1
4.8%
128.8230037 1
4.8%
128.8523334 1
4.8%
128.8775713 1
4.8%
128.8891681 1
4.8%
128.8948561 1
4.8%
128.9195924 1
4.8%
ValueCountFrequency (%)
129.1116967 1
4.8%
129.1074919 1
4.8%
129.0457223 1
4.8%
129.0185535 1
4.8%
129.009184 1
4.8%
128.9917022 1
4.8%
128.9765805 1
4.8%
128.9737931 1
4.8%
128.9615173 1
4.8%
128.9386614 1
4.8%

관리기관명
Categorical

CONSTANT 

Distinct1
Distinct (%)4.8%
Missing0
Missing (%)0.0%
Memory size300.0 B
경상북도 영천시청
21 

Length

Max length9
Median length9
Mean length9
Min length9

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row경상북도 영천시청
2nd row경상북도 영천시청
3rd row경상북도 영천시청
4th row경상북도 영천시청
5th row경상북도 영천시청

Common Values

ValueCountFrequency (%)
경상북도 영천시청 21
100.0%

Length

2023-12-16T15:22:20.874584image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-16T15:22:21.461044image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
경상북도 21
50.0%
영천시청 21
50.0%

관리기관전화번호
Categorical

CONSTANT 

Distinct1
Distinct (%)4.8%
Missing0
Missing (%)0.0%
Memory size300.0 B
054-330-6332
21 

Length

Max length12
Median length12
Mean length12
Min length12

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row054-330-6332
2nd row054-330-6332
3rd row054-330-6332
4th row054-330-6332
5th row054-330-6332

Common Values

ValueCountFrequency (%)
054-330-6332 21
100.0%

Length

2023-12-16T15:22:22.193221image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-16T15:22:22.649801image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
054-330-6332 21
100.0%

담당부서명
Categorical

CONSTANT 

Distinct1
Distinct (%)4.8%
Missing0
Missing (%)0.0%
Memory size300.0 B
안전재난하천과
21 

Length

Max length7
Median length7
Mean length7
Min length7

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
안전재난하천과 21
100.0%

Length

2023-12-16T15:22:23.282883image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-16T15:22:23.922208image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
안전재난하천과 21
100.0%

데이터기준일자
Categorical

CONSTANT 

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

Length

Max length10
Median length10
Mean length10
Min length10

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

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

Length

2023-12-16T15:22:24.405891image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-16T15:22:24.857437image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2023-12-12 21
100.0%

Interactions

2023-12-16T15:22:01.978660image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-16T15:21:59.274715image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-16T15:22:00.594823image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-16T15:22:02.534039image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-16T15:21:59.709539image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-16T15:22:01.047680image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-16T15:22:02.952767image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-16T15:22:00.120394image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-16T15:22:01.472660image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-16T15:22:25.352465image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
연번장소명소재지도로명주소소재지지번주소설치시설구분좌표정보(X)좌표정보(Y)
연번1.0001.0001.0001.0000.6710.0000.808
장소명1.0001.0001.0001.0001.0001.0001.000
소재지도로명주소1.0001.0001.0001.0001.0001.0001.000
소재지지번주소1.0001.0001.0001.0001.0001.0001.000
설치시설구분0.6711.0001.0001.0001.0000.4570.458
좌표정보(X)0.0001.0001.0001.0000.4571.0000.000
좌표정보(Y)0.8081.0001.0001.0000.4580.0001.000
2023-12-16T15:22:25.821200image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
연번좌표정보(X)좌표정보(Y)설치시설구분
연번1.000-0.1520.0090.393
좌표정보(X)-0.1521.0000.0840.269
좌표정보(Y)0.0090.0841.0000.218
설치시설구분0.3930.2690.2181.000

Missing values

2023-12-16T15:22:03.581393image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-16T15:22:04.802766image/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

연번장소명소재지도로명주소소재지지번주소수량설치시설구분좌표정보(X)좌표정보(Y)관리기관명관리기관전화번호담당부서명데이터기준일자
01영천시청경상북도 영천시 시청로 16 (문외동, 영천시청)경상북도 영천시 문외동 271관공서35.973206128.938661경상북도 영천시청054-330-6332안전재난하천과2023-12-12
12청통면사무소경상북도 영천시 청통면 금송로 978 (청통면, 청통면사무소)경상북도 영천시 청통면 치일리 14-11관공서35.99212128.823004경상북도 영천시청054-330-6332안전재난하천과2023-12-12
23신녕면사무소경상북도 영천시 신녕면 화성중앙길 30 (신녕면, 신녕면사무소)경상북도 영천시 신녕면 화성리 4191관공서36.045262128.789555경상북도 영천시청054-330-6332안전재난하천과2023-12-12
34화산면사무소경상북도 영천시 화산면 연지길 16 (화산면, 화산면사무소)경상북도 영천시 화산면 유성리 12891관공서36.020367128.852333경상북도 영천시청054-330-6332안전재난하천과2023-12-12
45고경면사무소경상북도 영천시 고경면 호국로 1065-23 (고경면, 6.25참전유공자고경면분회)경상북도 영천시 고경면 해선리 309-21관공서36.001592129.045722경상북도 영천시청054-330-6332안전재난하천과2023-12-12
56자양면사무소경상북도 영천시 자양면 포은로 1631 (자양면)경상북도 영천시 자양면 성곡리 549-11관공서36.078454129.018553경상북도 영천시청054-330-6332안전재난하천과2023-12-12
67임고면사무소경상북도 영천시 임고면 포은로 491 (임고면)경상북도 영천시 임고면 양항리 616-11관공서36.020969128.973793경상북도 영천시청054-330-6332안전재난하천과2023-12-12
78북안면사무소경상북도 영천시 북안면 운북로 1995 (북안면, 북안면사무소)경상북도 영천시 북안면 고지리 549-11관공서35.915464129.009184경상북도 영천시청054-330-6332안전재난하천과2023-12-12
89대창면사무소경상북도 영천시 대창면 금박로 1057-7 (대창면)경상북도 영천시 대창면 대창리 783-11관공서35.875839128.894856경상북도 영천시청054-330-6332안전재난하천과2023-12-12
910금호읍사무소경상북도 영천시 금호읍 금호로 153 (금호읍, 금호읍사무소)경상북도 영천시 금호읍 교대리 149-21관공서35.93311128.877571경상북도 영천시청054-330-6332안전재난하천과2023-12-12
연번장소명소재지도로명주소소재지지번주소수량설치시설구분좌표정보(X)좌표정보(Y)관리기관명관리기관전화번호담당부서명데이터기준일자
1112화남면사무소경상북도 영천시 화남면 신화로 1197 (화남면, 화남면사무소)경상북도 영천시 화남면 삼창리 1023-21관공서36.059137128.889168경상북도 영천시청054-330-6332안전재난하천과2023-12-12
1213대곡2리회관경상북도 영천시 금호읍 대곡길 31-6 (금호읍, 대곡1리회관경로당)경상북도 영천시 금호읍 대곡리 6871복지시설35.892044128.920309경상북도 영천시청054-330-6332안전재난하천과2023-12-12
1314신원경로당경상북도 영천시 청통면 거조길 328 (청통면, 신원경로당)경상북도 영천시 청통면 신원리 422-31복지시설36.017749128.777163경상북도 영천시청054-330-6332안전재난하천과2023-12-12
1415수성경로당경상북도 영천시 임고면 운주로 1546-4 (임고면, 수성경로당)경상북도 영천시 임고면 수성리 916-51복지시설36.056936129.111697경상북도 영천시청054-330-6332안전재난하천과2023-12-12
1516덕정리마을회관경상북도 영천시 고경면 용담로 1522-17경상북도 영천시 고경면 덕정리 2471복지시설35.936726129.107492경상북도 영천시청054-330-6332안전재난하천과2023-12-12
1617상리노인정경상북도 영천시 북안면 운북로 1194 (북안면, 상리회관)경상북도 영천시 북안면 상리 350-11복지시설35.851199128.991702경상북도 영천시청054-330-6332안전재난하천과2023-12-12
1718보현산 천문대경상북도 영천시 화북면 정각길 475 (화북면)경상북도 영천시 화북면 정각리 73-131관광36.164258128.976581경상북도 영천시청054-330-6332안전재난하천과2023-12-12
1819직천리회관경상북도 영천시 대창면 하이브리드로 101경상북도 영천시 대창면 직천리 367-11복지시설35.874698128.961517경상북도 영천시청054-330-6332안전재난하천과2023-12-12
1920범어동 경로당경상북도 영천시 범어 2길 3-3경상북도 영천시 범어동 765-11복지시설35.52291128.57414경상북도 영천시청054-330-6332안전재난하천과2023-12-12
2021신녕면 가천지구<NA>경상북도 영천시 신녕면 가천리 177-51다리36.0553128.7924경상북도 영천시청054-330-6332안전재난하천과2023-12-12