Overview

Dataset statistics

Number of variables11
Number of observations271
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory24.5 KiB
Average record size in memory92.5 B

Variable types

Numeric3
Categorical5
Text2
DateTime1

Dataset

Description대구광역시_중구_폐형광등 및 폐건전지 분리수거함 현황_20230801
Author대구광역시 중구
URLhttp://data.daegu.go.kr/open/data/dataView.do?dataSetId=15041732&dataSetDetailId=1504173219bbbc8a45d72&provdMethod=FILE

Alerts

시도명 has constant value ""Constant
시군구명 has constant value ""Constant
데이터기준일 has constant value ""Constant
수거품목 is highly overall correlated with 연번 and 1 other fieldsHigh correlation
설치년도 is highly overall correlated with 연번 and 1 other fieldsHigh correlation
연번 is highly overall correlated with 설치년도 and 1 other fieldsHigh correlation
경도 is highly overall correlated with 행정동High correlation
행정동 is highly overall correlated with 경도High correlation
연번 has unique valuesUnique

Reproduction

Analysis started2023-12-10 18:27:32.203426
Analysis finished2023-12-10 18:27:35.083037
Duration2.88 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

연번
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct271
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean136
Minimum1
Maximum271
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size2.5 KiB
2023-12-11T03:27:35.229491image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile14.5
Q168.5
median136
Q3203.5
95-th percentile257.5
Maximum271
Range270
Interquartile range (IQR)135

Descriptive statistics

Standard deviation78.375166
Coefficient of variation (CV)0.57628799
Kurtosis-1.2
Mean136
Median Absolute Deviation (MAD)68
Skewness0
Sum36856
Variance6142.6667
MonotonicityStrictly increasing
2023-12-11T03:27:35.482510image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1 1
 
0.4%
180 1
 
0.4%
186 1
 
0.4%
185 1
 
0.4%
184 1
 
0.4%
183 1
 
0.4%
182 1
 
0.4%
181 1
 
0.4%
179 1
 
0.4%
2 1
 
0.4%
Other values (261) 261
96.3%
ValueCountFrequency (%)
1 1
0.4%
2 1
0.4%
3 1
0.4%
4 1
0.4%
5 1
0.4%
6 1
0.4%
7 1
0.4%
8 1
0.4%
9 1
0.4%
10 1
0.4%
ValueCountFrequency (%)
271 1
0.4%
270 1
0.4%
269 1
0.4%
268 1
0.4%
267 1
0.4%
266 1
0.4%
265 1
0.4%
264 1
0.4%
263 1
0.4%
262 1
0.4%

시도명
Categorical

CONSTANT 

Distinct1
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Memory size2.2 KiB
대구광역시
271 

Length

Max length5
Median length5
Mean length5
Min length5

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
대구광역시 271
100.0%

Length

2023-12-11T03:27:35.718718image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T03:27:35.872749image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
대구광역시 271
100.0%

시군구명
Categorical

CONSTANT 

Distinct1
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Memory size2.2 KiB
중구
271 

Length

Max length2
Median length2
Mean length2
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
중구 271
100.0%

Length

2023-12-11T03:27:36.033921image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T03:27:36.197325image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
중구 271
100.0%

행정동
Categorical

HIGH CORRELATION 

Distinct13
Distinct (%)4.8%
Missing0
Missing (%)0.0%
Memory size2.2 KiB
삼덕동
61 
동인동
54 
성내1동
33 
남산1동
25 
대봉1동
21 
Other values (8)
77 

Length

Max length4
Median length4
Mean length3.5350554
Min length3

Unique

Unique1 ?
Unique (%)0.4%

Sample

1st row성내1동
2nd row동인동
3rd row성내2동
4th row동인동
5th row대신동

Common Values

ValueCountFrequency (%)
삼덕동 61
22.5%
동인동 54
19.9%
성내1동 33
12.2%
남산1동 25
9.2%
대봉1동 21
 
7.7%
남산3동 19
 
7.0%
성내2동 16
 
5.9%
남산4동 14
 
5.2%
대신동 10
 
3.7%
성내3동 8
 
3.0%
Other values (3) 10
 
3.7%

Length

2023-12-11T03:27:36.358974image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
삼덕동 61
22.5%
동인동 54
19.9%
성내1동 33
12.2%
남산1동 25
9.2%
대봉1동 21
 
7.7%
남산3동 19
 
7.0%
성내2동 16
 
5.9%
남산4동 14
 
5.2%
대신동 10
 
3.7%
성내3동 8
 
3.0%
Other values (3) 10
 
3.7%

설치위치(주택명)
Text

Distinct269
Distinct (%)99.3%
Missing0
Missing (%)0.0%
Memory size2.2 KiB
2023-12-11T03:27:36.846035image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length16
Median length14
Mean length5.1143911
Min length1

Characters and Unicode

Total characters1386
Distinct characters271
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

Unique267 ?
Unique (%)98.5%

Sample

1st row봉산뜨란채
2nd row삼정그린코아
3rd row동산
4th row삼승슈퍼타워
5th row광명
ValueCountFrequency (%)
유치원 11
 
3.5%
빌 5
 
1.6%
대구 5
 
1.6%
이 2
 
0.6%
미 2
 
0.6%
프린스빌 2
 
0.6%
카 2
 
0.6%
스카이빌 2
 
0.6%
노블레스 1
 
0.3%
청운하이츠 1
 
0.3%
Other values (281) 281
89.5%
2023-12-11T03:27:37.607511image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
빌 83
 
6.0%
이 74
 
5.3%
스 51
 
3.7%
45
 
3.2%
린 43
 
3.1%
아 40
 
2.9%
어 37
 
2.7%
집 37
 
2.7%
하 35
 
2.5%
트 30
 
2.2%
Other values (261) 911
65.7%

Most occurring categories

ValueCountFrequency (%)
Other Letter 1319
95.2%
Space Separator 45
 
3.2%
Uppercase Letter 15
 
1.1%
Decimal Number 3
 
0.2%
Lowercase Letter 2
 
0.1%
Close Punctuation 1
 
0.1%
Open Punctuation 1
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
빌 83
 
6.3%
이 74
 
5.6%
스 51
 
3.9%
린 43
 
3.3%
아 40
 
3.0%
어 37
 
2.8%
집 37
 
2.8%
하 35
 
2.7%
트 30
 
2.3%
라 29
 
2.2%
Other values (242) 860
65.2%
Uppercase Letter
ValueCountFrequency (%)
R 2
13.3%
E 2
13.3%
T 2
13.3%
M 2
13.3%
I 1
6.7%
B 1
6.7%
O 1
6.7%
X 1
6.7%
Y 1
6.7%
C 1
6.7%
Decimal Number
ValueCountFrequency (%)
4 1
33.3%
0 1
33.3%
2 1
33.3%
Lowercase Letter
ValueCountFrequency (%)
s 1
50.0%
k 1
50.0%
Space Separator
ValueCountFrequency (%)
45
100.0%
Close Punctuation
ValueCountFrequency (%)
) 1
100.0%
Open Punctuation
ValueCountFrequency (%)
( 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 1319
95.2%
Common 50
 
3.6%
Latin 17
 
1.2%

Most frequent character per script

Hangul
ValueCountFrequency (%)
빌 83
 
6.3%
이 74
 
5.6%
스 51
 
3.9%
린 43
 
3.3%
아 40
 
3.0%
어 37
 
2.8%
집 37
 
2.8%
하 35
 
2.7%
트 30
 
2.3%
라 29
 
2.2%
Other values (242) 860
65.2%
Latin
ValueCountFrequency (%)
R 2
11.8%
E 2
11.8%
T 2
11.8%
M 2
11.8%
I 1
 
5.9%
B 1
 
5.9%
O 1
 
5.9%
X 1
 
5.9%
s 1
 
5.9%
k 1
 
5.9%
Other values (3) 3
17.6%
Common
ValueCountFrequency (%)
45
90.0%
4 1
 
2.0%
0 1
 
2.0%
) 1
 
2.0%
2 1
 
2.0%
( 1
 
2.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 1319
95.2%
ASCII 67
 
4.8%

Most frequent character per block

Hangul
ValueCountFrequency (%)
빌 83
 
6.3%
이 74
 
5.6%
스 51
 
3.9%
린 43
 
3.3%
아 40
 
3.0%
어 37
 
2.8%
집 37
 
2.8%
하 35
 
2.7%
트 30
 
2.3%
라 29
 
2.2%
Other values (242) 860
65.2%
ASCII
ValueCountFrequency (%)
45
67.2%
R 2
 
3.0%
E 2
 
3.0%
T 2
 
3.0%
M 2
 
3.0%
I 1
 
1.5%
4 1
 
1.5%
0 1
 
1.5%
B 1
 
1.5%
O 1
 
1.5%
Other values (9) 9
 
13.4%

설치주소
Text

Distinct270
Distinct (%)99.6%
Missing0
Missing (%)0.0%
Memory size2.2 KiB
2023-12-11T03:27:38.045543image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length50
Median length47
Mean length22.391144
Min length15

Characters and Unicode

Total characters6068
Distinct characters137
Distinct categories8 ?
Distinct scripts2 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique269 ?
Unique (%)99.3%

Sample

1st row대구광역시 중구 봉산문화길 69(봉산동 봉산뜨란채아파트)
2nd row대구광역시 중구 동덕로30길 53(동인동 동인동삼정그린코아아파트)
3rd row대구광역시 중구 달구벌대로 2035(동산동 동산아파트)
4th row대구광역시 중구 신암로 6(동인동1가 삼승슈퍼타워)
5th row대구광역시 중구 큰장로 74(대신동 광명아파트)
ValueCountFrequency (%)
대구광역시 271
22.6%
중구 270
22.5%
남산동 18
 
1.5%
달구벌대로 16
 
1.3%
국채보상로 15
 
1.3%
동덕로 13
 
1.1%
달구벌대로447길 10
 
0.8%
경상감영길 10
 
0.8%
달구벌대로445길 10
 
0.8%
국채보상로150길 8
 
0.7%
Other values (354) 557
46.5%
2023-12-11T03:27:38.771945image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
972
16.0%
구 588
 
9.7%
대 355
 
5.9%
중 289
 
4.8%
시 274
 
4.5%
광 272
 
4.5%
역 271
 
4.5%
1 255
 
4.2%
로 236
 
3.9%
길 193
 
3.2%
Other values (127) 2363
38.9%

Most occurring categories

ValueCountFrequency (%)
Other Letter 3540
58.3%
Decimal Number 1297
 
21.4%
Space Separator 972
 
16.0%
Dash Punctuation 141
 
2.3%
Open Punctuation 58
 
1.0%
Close Punctuation 58
 
1.0%
Math Symbol 1
 
< 0.1%
Other Punctuation 1
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
구 588
16.6%
대 355
10.0%
중 289
 
8.2%
시 274
 
7.7%
광 272
 
7.7%
역 271
 
7.7%
로 236
 
6.7%
길 193
 
5.5%
동 142
 
4.0%
산 76
 
2.1%
Other values (111) 844
23.8%
Decimal Number
ValueCountFrequency (%)
1 255
19.7%
2 180
13.9%
4 174
13.4%
3 136
10.5%
5 109
8.4%
0 104
8.0%
6 103
7.9%
7 97
 
7.5%
8 85
 
6.6%
9 54
 
4.2%
Space Separator
ValueCountFrequency (%)
972
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 141
100.0%
Open Punctuation
ValueCountFrequency (%)
( 58
100.0%
Close Punctuation
ValueCountFrequency (%)
) 58
100.0%
Math Symbol
ValueCountFrequency (%)
~ 1
100.0%
Other Punctuation
ValueCountFrequency (%)
· 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 3540
58.3%
Common 2528
41.7%

Most frequent character per script

Hangul
ValueCountFrequency (%)
구 588
16.6%
대 355
10.0%
중 289
 
8.2%
시 274
 
7.7%
광 272
 
7.7%
역 271
 
7.7%
로 236
 
6.7%
길 193
 
5.5%
동 142
 
4.0%
산 76
 
2.1%
Other values (111) 844
23.8%
Common
ValueCountFrequency (%)
972
38.4%
1 255
 
10.1%
2 180
 
7.1%
4 174
 
6.9%
- 141
 
5.6%
3 136
 
5.4%
5 109
 
4.3%
0 104
 
4.1%
6 103
 
4.1%
7 97
 
3.8%
Other values (6) 257
 
10.2%

Most occurring blocks

ValueCountFrequency (%)
Hangul 3540
58.3%
ASCII 2527
41.6%
None 1
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
972
38.5%
1 255
 
10.1%
2 180
 
7.1%
4 174
 
6.9%
- 141
 
5.6%
3 136
 
5.4%
5 109
 
4.3%
0 104
 
4.1%
6 103
 
4.1%
7 97
 
3.8%
Other values (5) 256
 
10.1%
Hangul
ValueCountFrequency (%)
구 588
16.6%
대 355
10.0%
중 289
 
8.2%
시 274
 
7.7%
광 272
 
7.7%
역 271
 
7.7%
로 236
 
6.7%
길 193
 
5.5%
동 142
 
4.0%
산 76
 
2.1%
Other values (111) 844
23.8%
None
ValueCountFrequency (%)
· 1
100.0%

위도
Real number (ℝ)

Distinct255
Distinct (%)94.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean35.865168
Minimum35.855786
Maximum35.876599
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size2.5 KiB
2023-12-11T03:27:39.027552image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum35.855786
5-th percentile35.857447
Q135.861502
median35.864827
Q335.869519
95-th percentile35.872954
Maximum35.876599
Range0.02081395
Interquartile range (IQR)0.008017185

Descriptive statistics

Standard deviation0.0047994085
Coefficient of variation (CV)0.00013381809
Kurtosis-0.95460488
Mean35.865168
Median Absolute Deviation (MAD)0.00396985
Skewness0.083785278
Sum9719.4607
Variance2.3034322 × 10-5
MonotonicityNot monotonic
2023-12-11T03:27:39.314135image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
35.86757123 3
 
1.1%
35.87060685 3
 
1.1%
35.86286312 2
 
0.7%
35.87017977 2
 
0.7%
35.86808071 2
 
0.7%
35.87157184 2
 
0.7%
35.86588044 2
 
0.7%
35.85951706 2
 
0.7%
35.86404141 2
 
0.7%
35.86932314 2
 
0.7%
Other values (245) 249
91.9%
ValueCountFrequency (%)
35.8557855 1
0.4%
35.85591231 1
0.4%
35.85627084 1
0.4%
35.85682095 1
0.4%
35.85684433 1
0.4%
35.85692339 1
0.4%
35.85696943 2
0.7%
35.8571379 1
0.4%
35.85716868 1
0.4%
35.85717477 1
0.4%
ValueCountFrequency (%)
35.87659945 1
0.4%
35.87425825 1
0.4%
35.87357195 1
0.4%
35.87349687 1
0.4%
35.87346273 1
0.4%
35.87343016 1
0.4%
35.87338827 1
0.4%
35.87330207 1
0.4%
35.87324665 1
0.4%
35.87322796 1
0.4%

경도
Real number (ℝ)

HIGH CORRELATION 

Distinct255
Distinct (%)94.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean128.59788
Minimum128.57506
Maximum128.6126
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size2.5 KiB
2023-12-11T03:27:39.595160image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum128.57506
5-th percentile128.57923
Q1128.59169
median128.60024
Q3128.60586
95-th percentile128.61028
Maximum128.6126
Range0.0375356
Interquartile range (IQR)0.01417005

Descriptive statistics

Standard deviation0.0097888542
Coefficient of variation (CV)7.6119873 × 10-5
Kurtosis-0.74251344
Mean128.59788
Median Absolute Deviation (MAD)0.0067484
Skewness-0.6030052
Sum34850.025
Variance9.5821666 × 10-5
MonotonicityNot monotonic
2023-12-11T03:27:39.879923image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
128.6068862 3
 
1.1%
128.5928457 3
 
1.1%
128.5967519 2
 
0.7%
128.5825219 2
 
0.7%
128.6095034 2
 
0.7%
128.6106819 2
 
0.7%
128.5750603 2
 
0.7%
128.5880683 2
 
0.7%
128.595432 2
 
0.7%
128.6062241 2
 
0.7%
Other values (245) 249
91.9%
ValueCountFrequency (%)
128.5750603 2
0.7%
128.5759646 1
0.4%
128.5767369 1
0.4%
128.5767438 1
0.4%
128.5770834 1
0.4%
128.5773865 1
0.4%
128.5774564 1
0.4%
128.5776056 1
0.4%
128.5776368 1
0.4%
128.5787844 1
0.4%
ValueCountFrequency (%)
128.6125959 1
0.4%
128.6121383 1
0.4%
128.6118431 1
0.4%
128.6114482 1
0.4%
128.6111911 1
0.4%
128.6109818 1
0.4%
128.6108678 1
0.4%
128.6108401 1
0.4%
128.6106819 2
0.7%
128.61052 1
0.4%

설치년도
Categorical

HIGH CORRELATION 

Distinct5
Distinct (%)1.8%
Missing0
Missing (%)0.0%
Memory size2.2 KiB
2018
145 
2019
51 
2016
48 
2017
22 
2015
 
5

Length

Max length4
Median length4
Mean length4
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row2015
2nd row2015
3rd row2015
4th row2015
5th row2015

Common Values

ValueCountFrequency (%)
2018 145
53.5%
2019 51
 
18.8%
2016 48
 
17.7%
2017 22
 
8.1%
2015 5
 
1.8%

Length

2023-12-11T03:27:40.154460image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T03:27:40.394589image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2018 145
53.5%
2019 51
 
18.8%
2016 48
 
17.7%
2017 22
 
8.1%
2015 5
 
1.8%

수거품목
Categorical

HIGH CORRELATION 

Distinct3
Distinct (%)1.1%
Missing0
Missing (%)0.0%
Memory size2.2 KiB
기타 재활용+ 폐건전지
196 
폐건전지
53 
폐형광등+ 폐건전지
22 

Length

Max length12
Median length12
Mean length10.273063
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
기타 재활용+ 폐건전지 196
72.3%
폐건전지 53
 
19.6%
폐형광등+ 폐건전지 22
 
8.1%

Length

2023-12-11T03:27:40.655707image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T03:27:40.879737image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
폐건전지 271
39.6%
기타 196
28.6%
재활용 196
28.6%
폐형광등 22
 
3.2%

데이터기준일
Date

CONSTANT 

Distinct1
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Memory size2.2 KiB
Minimum2023-08-01 00:00:00
Maximum2023-08-01 00:00:00
2023-12-11T03:27:41.065414image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T03:27:41.252756image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=1)

Interactions

2023-12-11T03:27:34.038031image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T03:27:33.051033image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T03:27:33.540772image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T03:27:34.227215image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T03:27:33.202564image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T03:27:33.697056image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T03:27:34.408091image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T03:27:33.357420image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T03:27:33.852193image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-11T03:27:41.413440image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
연번행정동위도경도설치년도수거품목
연번1.0000.7050.5950.5980.9840.937
행정동0.7051.0000.7480.8580.4090.495
위도0.5950.7481.0000.6220.2470.245
경도0.5980.8580.6221.0000.4920.485
설치년도0.9840.4090.2470.4921.0001.000
수거품목0.9370.4950.2450.4851.0001.000
2023-12-11T03:27:41.616416image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
행정동수거품목설치년도
행정동1.0000.3170.232
수거품목0.3171.0000.996
설치년도0.2320.9961.000
2023-12-11T03:27:42.214351image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
연번위도경도행정동설치년도수거품목
연번1.000-0.1380.1320.3860.7960.884
위도-0.1381.0000.2940.4280.1030.148
경도0.1320.2941.0000.5820.2300.339
행정동0.3860.4280.5821.0000.2320.317
설치년도0.7960.1030.2300.2321.0000.996
수거품목0.8840.1480.3390.3170.9961.000

Missing values

2023-12-11T03:27:34.673603image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-11T03:27:34.974964image/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

연번시도명시군구명행정동설치위치(주택명)설치주소위도경도설치년도수거품목데이터기준일
01대구광역시중구성내1동봉산뜨란채대구광역시 중구 봉산문화길 69(봉산동 봉산뜨란채아파트)35.862863128.5967522015폐건전지2023-08-01
12대구광역시중구동인동삼정그린코아대구광역시 중구 동덕로30길 53(동인동 동인동삼정그린코아아파트)35.867571128.6068862015폐건전지2023-08-01
23대구광역시중구성내2동동산대구광역시 중구 달구벌대로 2035(동산동 동산아파트)35.867071128.5860762015폐건전지2023-08-01
34대구광역시중구동인동삼승슈퍼타워대구광역시 중구 신암로 6(동인동1가 삼승슈퍼타워)35.873133128.6050792015폐건전지2023-08-01
45대구광역시중구대신동광명대구광역시 중구 큰장로 74(대신동 광명아파트)35.86588128.575062015폐건전지2023-08-01
56대구광역시중구남산4동가온어린이집대구광역시 중구 달구벌대로 1970 206동 1층(남산동 남산휴먼시아2단지)35.863195128.5805992016폐건전지2023-08-01
67대구광역시중구남산4동꿈나무어린이집대구광역시 중구 남산로7길 35 (남산동)35.858481128.5805872016폐건전지2023-08-01
78대구광역시중구남산2동남산교회어린이집대구광역시 중구 관덕정길 16 (남산동)35.865048128.5905792016폐건전지2023-08-01
89대구광역시중구남산4동누리마루어린이집대구광역시 중구 남산로1길 46-5 (남산동)35.858447128.5802432016폐건전지2023-08-01
910대구광역시중구삼덕동다람어린이집대구광역시 중구 국채보상로150길 68 (삼덕동3가)35.865471128.6104022016폐건전지2023-08-01
연번시도명시군구명행정동설치위치(주택명)설치주소위도경도설치년도수거품목데이터기준일
261262대구광역시중구성내1동팰리스빌대구광역시 중구 경상감영길 231-735.872095128.5999662019기타 재활용+ 폐건전지2023-08-01
262263대구광역시중구성내1동해피트리대구광역시 중구 교동4길 30-235.872767128.5989082019기타 재활용+ 폐건전지2023-08-01
263264대구광역시중구남산1동스카이빌대구광역시 중구 중앙대로 280-335.858237128.591792019기타 재활용+ 폐건전지2023-08-01
264265대구광역시중구남산1동지앤빌대구광역시 중구 남산로2길 10635.857261128.5886722019기타 재활용+ 폐건전지2023-08-01
265266대구광역시중구남산2동포시즌대구광역시 중구 중앙대로65길 1135.861931128.5919952019기타 재활용+ 폐건전지2023-08-01
266267대구광역시중구남산3동미석빌딩대구광역시 중구 중앙대로61길 5435.860944128.5892422019기타 재활용+ 폐건전지2023-08-01
267268대구광역시중구남산3동드림타운대구광역시 중구 남산로6길 2235.858985128.5861932019기타 재활용+ 폐건전지2023-08-01
268269대구광역시중구남산4동그랜드빌대구광역시 중구 명덕로 53-635.859336128.5770832019기타 재활용+ 폐건전지2023-08-01
269270대구광역시중구대봉1동프라자빌대구광역시 중구 동덕로8길 26-635.859411128.6057052019기타 재활용+ 폐건전지2023-08-01
270271대구광역시중구대봉1동스노우빌대구광역시 중구 동덕로8길 26-235.859412128.6055392019기타 재활용+ 폐건전지2023-08-01