Overview

Dataset statistics

Number of variables8
Number of observations23
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory1.6 KiB
Average record size in memory71.7 B

Variable types

Numeric2
Text2
Categorical4

Dataset

Description대구광역시 달서구 내 폐형광등 및 폐건전지 분리수거함 현황에 대한 내용 및 정보가 담겨있음. (좌표, 주소, 세부위치, 동명, 유형)
URLhttps://www.data.go.kr/data/15041695/fileData.do

Alerts

세부위치 has constant value ""Constant
설치_유형 has constant value ""Constant
담당부서 has constant value ""Constant
기준일자 has constant value ""Constant
위도 has unique valuesUnique
경도 has unique valuesUnique
설치_주소 has unique valuesUnique
동명 has unique valuesUnique

Reproduction

Analysis started2023-12-12 11:21:56.614257
Analysis finished2023-12-12 11:21:57.704255
Duration1.09 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

위도
Real number (ℝ)

UNIQUE 

Distinct23
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean35.836508
Minimum35.807483
Maximum35.858966
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size339.0 B
2023-12-12T20:21:57.793751image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum35.807483
5-th percentile35.810285
Q135.818402
median35.840611
Q335.853671
95-th percentile35.858251
Maximum35.858966
Range0.05148334
Interquartile range (IQR)0.0352693

Descriptive statistics

Standard deviation0.01804806
Coefficient of variation (CV)0.00050362218
Kurtosis-1.465046
Mean35.836508
Median Absolute Deviation (MAD)0.01517612
Skewness-0.28596596
Sum824.23969
Variance0.00032573249
MonotonicityNot monotonic
2023-12-12T20:21:57.977706image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=23)
ValueCountFrequency (%)
35.84061122 1
 
4.3%
35.85569114 1
 
4.3%
35.83443829 1
 
4.3%
35.83278631 1
 
4.3%
35.82922897 1
 
4.3%
35.80748297 1
 
4.3%
35.81006963 1
 
4.3%
35.81255741 1
 
4.3%
35.81426653 1
 
4.3%
35.81729245 1
 
4.3%
Other values (13) 13
56.5%
ValueCountFrequency (%)
35.80748297 1
4.3%
35.81006963 1
4.3%
35.81222021 1
4.3%
35.81255741 1
4.3%
35.81426653 1
4.3%
35.81729245 1
4.3%
35.81951189 1
4.3%
35.82922897 1
4.3%
35.83095298 1
4.3%
35.83278631 1
4.3%
ValueCountFrequency (%)
35.85896631 1
4.3%
35.85843068 1
4.3%
35.85663686 1
4.3%
35.85580334 1
4.3%
35.85578734 1
4.3%
35.85569114 1
4.3%
35.8516518 1
4.3%
35.8510266 1
4.3%
35.84994411 1
4.3%
35.84332056 1
4.3%

경도
Real number (ℝ)

UNIQUE 

Distinct23
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean128.53427
Minimum128.49883
Maximum128.5722
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size339.0 B
2023-12-12T20:21:58.123687image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum128.49883
5-th percentile128.50181
Q1128.52291
median128.53625
Q3128.54529
95-th percentile128.5546
Maximum128.5722
Range0.0733626
Interquartile range (IQR)0.0223815

Descriptive statistics

Standard deviation0.017823918
Coefficient of variation (CV)0.00013867054
Kurtosis0.037992258
Mean128.53427
Median Absolute Deviation (MAD)0.0132648
Skewness-0.22695419
Sum2956.2883
Variance0.00031769204
MonotonicityNot monotonic
2023-12-12T20:21:58.316424image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=23)
ValueCountFrequency (%)
128.5531478 1
 
4.3%
128.5721965 1
 
4.3%
128.5410399 1
 
4.3%
128.5455779 1
 
4.3%
128.554762 1
 
4.3%
128.5321927 1
 
4.3%
128.5502023 1
 
4.3%
128.5362546 1
 
4.3%
128.5450082 1
 
4.3%
128.5140186 1
 
4.3%
Other values (13) 13
56.5%
ValueCountFrequency (%)
128.4988339 1
4.3%
128.500829 1
4.3%
128.5106562 1
4.3%
128.5140186 1
4.3%
128.5228075 1
4.3%
128.5228333 1
4.3%
128.5229898 1
4.3%
128.5282767 1
4.3%
128.5300194 1
4.3%
128.5312265 1
4.3%
ValueCountFrequency (%)
128.5721965 1
4.3%
128.554762 1
4.3%
128.5531478 1
4.3%
128.5502901 1
4.3%
128.5502023 1
4.3%
128.5455779 1
4.3%
128.5450082 1
4.3%
128.5431658 1
4.3%
128.5421825 1
4.3%
128.5410399 1
4.3%

설치_주소
Text

UNIQUE 

Distinct23
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size316.0 B
2023-12-12T20:21:58.650385image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length23
Median length22
Mean length18.130435
Min length16

Characters and Unicode

Total characters417
Distinct characters57
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

Unique23 ?
Unique (%)100.0%

Sample

1st row대구광역시 달서구 야외음악당로 38
2nd row대구광역시 달서구 두류길 141-8
3rd row대구광역시 달서구 야외음악당로39길 24
4th row대구광역시 달서구 당산로 37-14
5th row대구광역시 달서구 당산로 176
ValueCountFrequency (%)
대구광역시 23
25.0%
달서구 23
25.0%
당산로 2
 
2.2%
선원로 2
 
2.2%
176 2
 
2.2%
27 1
 
1.1%
진천로9길 1
 
1.1%
33 1
 
1.1%
조암로 1
 
1.1%
175 1
 
1.1%
Other values (35) 35
38.0%
2023-12-12T20:21:59.196796image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
69
16.5%
구 48
 
11.5%
대 25
 
6.0%
달 24
 
5.8%
서 24
 
5.8%
역 23
 
5.5%
시 23
 
5.5%
광 23
 
5.5%
로 21
 
5.0%
1 12
 
2.9%
Other values (47) 125
30.0%

Most occurring categories

ValueCountFrequency (%)
Other Letter 272
65.2%
Decimal Number 72
 
17.3%
Space Separator 69
 
16.5%
Dash Punctuation 4
 
1.0%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
구 48
17.6%
대 25
9.2%
달 24
8.8%
서 24
8.8%
역 23
8.5%
시 23
8.5%
광 23
8.5%
로 21
7.7%
길 8
 
2.9%
당 4
 
1.5%
Other values (35) 49
18.0%
Decimal Number
ValueCountFrequency (%)
1 12
16.7%
7 12
16.7%
2 10
13.9%
3 9
12.5%
6 7
9.7%
4 6
8.3%
8 5
6.9%
0 4
 
5.6%
9 4
 
5.6%
5 3
 
4.2%
Space Separator
ValueCountFrequency (%)
69
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 4
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 272
65.2%
Common 145
34.8%

Most frequent character per script

Hangul
ValueCountFrequency (%)
구 48
17.6%
대 25
9.2%
달 24
8.8%
서 24
8.8%
역 23
8.5%
시 23
8.5%
광 23
8.5%
로 21
7.7%
길 8
 
2.9%
당 4
 
1.5%
Other values (35) 49
18.0%
Common
ValueCountFrequency (%)
69
47.6%
1 12
 
8.3%
7 12
 
8.3%
2 10
 
6.9%
3 9
 
6.2%
6 7
 
4.8%
4 6
 
4.1%
8 5
 
3.4%
0 4
 
2.8%
9 4
 
2.8%
Other values (2) 7
 
4.8%

Most occurring blocks

ValueCountFrequency (%)
Hangul 272
65.2%
ASCII 145
34.8%

Most frequent character per block

ASCII
ValueCountFrequency (%)
69
47.6%
1 12
 
8.3%
7 12
 
8.3%
2 10
 
6.9%
3 9
 
6.2%
6 7
 
4.8%
4 6
 
4.1%
8 5
 
3.4%
0 4
 
2.8%
9 4
 
2.8%
Other values (2) 7
 
4.8%
Hangul
ValueCountFrequency (%)
구 48
17.6%
대 25
9.2%
달 24
8.8%
서 24
8.8%
역 23
8.5%
시 23
8.5%
광 23
8.5%
로 21
7.7%
길 8
 
2.9%
당 4
 
1.5%
Other values (35) 49
18.0%

세부위치
Categorical

CONSTANT 

Distinct1
Distinct (%)4.3%
Missing0
Missing (%)0.0%
Memory size316.0 B
행정복지센터 내
23 

Length

Max length8
Median length8
Mean length8
Min length8

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row행정복지센터 내
2nd row행정복지센터 내
3rd row행정복지센터 내
4th row행정복지센터 내
5th row행정복지센터 내

Common Values

ValueCountFrequency (%)
행정복지센터 내 23
100.0%

Length

2023-12-12T20:21:59.402202image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T20:21:59.531700image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
행정복지센터 23
50.0%
내 23
50.0%

동명
Text

UNIQUE 

Distinct23
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size316.0 B
2023-12-12T20:21:59.758251image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length6
Median length4
Mean length3.6086957
Min length2

Characters and Unicode

Total characters83
Distinct characters32
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

Unique23 ?
Unique (%)100.0%

Sample

1st row성당동
2nd row두류1.2동
3rd row두류3동
4th row본리동
5th row감삼동
ValueCountFrequency (%)
성당동 1
 
4.3%
월성1동 1
 
4.3%
송현2동 1
 
4.3%
송현1동 1
 
4.3%
도원동 1
 
4.3%
상인3동 1
 
4.3%
상인2동 1
 
4.3%
상인1동 1
 
4.3%
유천동 1
 
4.3%
진천동 1
 
4.3%
Other values (13) 13
56.5%
2023-12-12T20:22:00.310278image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
동 23
27.7%
1 6
 
7.2%
2 6
 
7.2%
성 3
 
3.6%
인 3
 
3.6%
상 3
 
3.6%
당 2
 
2.4%
송 2
 
2.4%
천 2
 
2.4%
월 2
 
2.4%
Other values (22) 31
37.3%

Most occurring categories

ValueCountFrequency (%)
Other Letter 68
81.9%
Decimal Number 14
 
16.9%
Other Punctuation 1
 
1.2%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
동 23
33.8%
성 3
 
4.4%
인 3
 
4.4%
상 3
 
4.4%
당 2
 
2.9%
송 2
 
2.9%
천 2
 
2.9%
월 2
 
2.9%
곡 2
 
2.9%
이 2
 
2.9%
Other values (18) 24
35.3%
Decimal Number
ValueCountFrequency (%)
1 6
42.9%
2 6
42.9%
3 2
 
14.3%
Other Punctuation
ValueCountFrequency (%)
. 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 68
81.9%
Common 15
 
18.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
동 23
33.8%
성 3
 
4.4%
인 3
 
4.4%
상 3
 
4.4%
당 2
 
2.9%
송 2
 
2.9%
천 2
 
2.9%
월 2
 
2.9%
곡 2
 
2.9%
이 2
 
2.9%
Other values (18) 24
35.3%
Common
ValueCountFrequency (%)
1 6
40.0%
2 6
40.0%
3 2
 
13.3%
. 1
 
6.7%

Most occurring blocks

ValueCountFrequency (%)
Hangul 68
81.9%
ASCII 15
 
18.1%

Most frequent character per block

Hangul
ValueCountFrequency (%)
동 23
33.8%
성 3
 
4.4%
인 3
 
4.4%
상 3
 
4.4%
당 2
 
2.9%
송 2
 
2.9%
천 2
 
2.9%
월 2
 
2.9%
곡 2
 
2.9%
이 2
 
2.9%
Other values (18) 24
35.3%
ASCII
ValueCountFrequency (%)
1 6
40.0%
2 6
40.0%
3 2
 
13.3%
. 1
 
6.7%

설치_유형
Categorical

CONSTANT 

Distinct1
Distinct (%)4.3%
Missing0
Missing (%)0.0%
Memory size316.0 B
폐형광등.폐건전지통합
23 

Length

Max length11
Median length11
Mean length11
Min length11

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row폐형광등.폐건전지통합
2nd row폐형광등.폐건전지통합
3rd row폐형광등.폐건전지통합
4th row폐형광등.폐건전지통합
5th row폐형광등.폐건전지통합

Common Values

ValueCountFrequency (%)
폐형광등.폐건전지통합 23
100.0%

Length

2023-12-12T20:22:01.018777image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T20:22:01.158630image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
폐형광등.폐건전지통합 23
100.0%

담당부서
Categorical

CONSTANT 

Distinct1
Distinct (%)4.3%
Missing0
Missing (%)0.0%
Memory size316.0 B
대구광역시 달서구 청소과
23 

Length

Max length13
Median length13
Mean length13
Min length13

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
대구광역시 달서구 청소과 23
100.0%

Length

2023-12-12T20:22:01.321104image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T20:22:01.478718image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
대구광역시 23
33.3%
달서구 23
33.3%
청소과 23
33.3%

기준일자
Categorical

CONSTANT 

Distinct1
Distinct (%)4.3%
Missing0
Missing (%)0.0%
Memory size316.0 B
2023-03-20
23 

Length

Max length10
Median length10
Mean length10
Min length10

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row2023-03-20
2nd row2023-03-20
3rd row2023-03-20
4th row2023-03-20
5th row2023-03-20

Common Values

ValueCountFrequency (%)
2023-03-20 23
100.0%

Length

2023-12-12T20:22:01.649306image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T20:22:01.876212image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2023-03-20 23
100.0%

Interactions

2023-12-12T20:21:57.146315image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T20:21:56.890388image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T20:21:57.291198image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T20:21:57.016535image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-12T20:22:02.026444image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
위도경도설치_주소동명
위도1.0000.0001.0001.000
경도0.0001.0001.0001.000
설치_주소1.0001.0001.0001.000
동명1.0001.0001.0001.000
2023-12-12T20:22:02.229821image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
위도경도
위도1.000-0.200
경도-0.2001.000

Missing values

2023-12-12T20:21:57.470089image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-12T20:21:57.632820image/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

위도경도설치_주소세부위치동명설치_유형담당부서기준일자
035.840611128.553148대구광역시 달서구 야외음악당로 38행정복지센터 내성당동폐형광등.폐건전지통합대구광역시 달서구 청소과2023-03-20
135.855691128.572196대구광역시 달서구 두류길 141-8행정복지센터 내두류1.2동폐형광등.폐건전지통합대구광역시 달서구 청소과2023-03-20
235.849944128.55029대구광역시 달서구 야외음악당로39길 24행정복지센터 내두류3동폐형광등.폐건전지통합대구광역시 달서구 청소과2023-03-20
335.841017128.543166대구광역시 달서구 당산로 37-14행정복지센터 내본리동폐형광등.폐건전지통합대구광역시 달서구 청소과2023-03-20
435.851027128.542182대구광역시 달서구 당산로 176행정복지센터 내감삼동폐형광등.폐건전지통합대구광역시 달서구 청소과2023-03-20
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