Overview

Dataset statistics

Number of variables6
Number of observations353
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory17.4 KiB
Average record size in memory50.4 B

Variable types

Numeric2
Text2
Categorical2

Dataset

Description대구광역시 달서구 내 사업장 폐기물 배출자 현황에 대한 내용 및 정보가 담겨있음. (좌표, 상호, 주소, 담당부서, 기준일자)
URLhttps://www.data.go.kr/data/15060192/fileData.do

Alerts

담당부서 has constant value ""Constant
기준일자 has constant value ""Constant
상호 has unique valuesUnique

Reproduction

Analysis started2023-12-12 14:25:00.931172
Analysis finished2023-12-12 14:25:01.829826
Duration0.9 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

위도
Real number (ℝ)

Distinct340
Distinct (%)96.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean35.837273
Minimum35.802888
Maximum35.865476
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size3.2 KiB
2023-12-12T23:25:01.906938image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum35.802888
5-th percentile35.816302
Q135.82865
median35.838058
Q335.847217
95-th percentile35.855097
Maximum35.865476
Range0.06258831
Interquartile range (IQR)0.01856732

Descriptive statistics

Standard deviation0.012599223
Coefficient of variation (CV)0.00035156758
Kurtosis-0.38950768
Mean35.837273
Median Absolute Deviation (MAD)0.00931298
Skewness-0.29929136
Sum12650.557
Variance0.00015874043
MonotonicityNot monotonic
2023-12-12T23:25:02.094594image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
35.83416564 3
 
0.8%
35.82076831 2
 
0.6%
35.83081152 2
 
0.6%
35.84547899 2
 
0.6%
35.8501251 2
 
0.6%
35.85215632 2
 
0.6%
35.83112494 2
 
0.6%
35.84099142 2
 
0.6%
35.84697122 2
 
0.6%
35.83317022 2
 
0.6%
Other values (330) 332
94.1%
ValueCountFrequency (%)
35.80288797 1
0.3%
35.80323492 1
0.3%
35.80527804 1
0.3%
35.80560062 1
0.3%
35.80606469 1
0.3%
35.80724093 1
0.3%
35.80724278 1
0.3%
35.81009792 1
0.3%
35.8105786 1
0.3%
35.8110469 1
0.3%
ValueCountFrequency (%)
35.86547628 1
0.3%
35.86231162 1
0.3%
35.86174911 1
0.3%
35.86141536 1
0.3%
35.86138023 1
0.3%
35.86129482 1
0.3%
35.86108125 1
0.3%
35.8606118 1
0.3%
35.86041167 1
0.3%
35.86040246 1
0.3%

경도
Real number (ℝ)

Distinct339
Distinct (%)96.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean128.5143
Minimum128.473
Maximum128.5742
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size3.2 KiB
2023-12-12T23:25:02.261669image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum128.473
5-th percentile128.48159
Q1128.4993
median128.50936
Q3128.52811
95-th percentile128.55716
Maximum128.5742
Range0.1011984
Interquartile range (IQR)0.0288122

Descriptive statistics

Standard deviation0.022057889
Coefficient of variation (CV)0.00017163762
Kurtosis-0.13128242
Mean128.5143
Median Absolute Deviation (MAD)0.0126221
Skewness0.62872798
Sum45365.55
Variance0.00048655047
MonotonicityNot monotonic
2023-12-12T23:25:02.422975image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
128.5086179 3
 
0.8%
128.5363099 2
 
0.6%
128.5003284 2
 
0.6%
128.4798079 2
 
0.6%
128.5301312 2
 
0.6%
128.5087731 2
 
0.6%
128.5434966 2
 
0.6%
128.5462195 2
 
0.6%
128.5058498 2
 
0.6%
128.5616278 2
 
0.6%
Other values (329) 332
94.1%
ValueCountFrequency (%)
128.4730044 1
0.3%
128.4736813 1
0.3%
128.4740314 1
0.3%
128.4740481 1
0.3%
128.4742935 1
0.3%
128.4753851 1
0.3%
128.4756417 1
0.3%
128.4759867 1
0.3%
128.4776987 1
0.3%
128.4791065 1
0.3%
ValueCountFrequency (%)
128.5742028 1
0.3%
128.5737212 1
0.3%
128.5732847 1
0.3%
128.5731899 1
0.3%
128.5725682 1
0.3%
128.5721578 1
0.3%
128.5668815 1
0.3%
128.5636973 1
0.3%
128.5616278 2
0.6%
128.5615885 1
0.3%

상호
Text

UNIQUE 

Distinct353
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size2.9 KiB
2023-12-12T23:25:02.693934image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length26
Median length16
Mean length7.6770538
Min length2

Characters and Unicode

Total characters2710
Distinct characters335
Distinct categories8 ?
Distinct scripts3 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique353 ?
Unique (%)100.0%

Sample

1st row(주)대한실업
2nd row계명대학교
3rd row대호프라스틱
4th row삼화식품공사
5th row(주)금복주
ValueCountFrequency (%)
주식회사 16
 
3.8%
대구공장 3
 
0.7%
의료법인 3
 
0.7%
대구광역시 2
 
0.5%
상가관리단 2
 
0.5%
대영알앤티 2
 
0.5%
대구지점 2
 
0.5%
㈜성진포머 2
 
0.5%
대구환경공단 2
 
0.5%
라 1
 
0.2%
Other values (381) 381
91.6%
2023-12-12T23:25:03.118429image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
주 118
 
4.4%
( 100
 
3.7%
) 100
 
3.7%
대 84
 
3.1%
㈜ 65
 
2.4%
64
 
2.4%
구 57
 
2.1%
공 57
 
2.1%
성 55
 
2.0%
원 54
 
2.0%
Other values (325) 1956
72.2%

Most occurring categories

ValueCountFrequency (%)
Other Letter 2339
86.3%
Open Punctuation 100
 
3.7%
Close Punctuation 100
 
3.7%
Other Symbol 65
 
2.4%
Space Separator 64
 
2.4%
Uppercase Letter 32
 
1.2%
Decimal Number 8
 
0.3%
Other Punctuation 2
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
주 118
 
5.0%
대 84
 
3.6%
구 57
 
2.4%
공 57
 
2.4%
성 55
 
2.4%
원 54
 
2.3%
이 48
 
2.1%
스 46
 
2.0%
업 37
 
1.6%
병 36
 
1.5%
Other values (299) 1747
74.7%
Uppercase Letter
ValueCountFrequency (%)
T 6
18.8%
V 3
 
9.4%
A 3
 
9.4%
E 2
 
6.2%
H 2
 
6.2%
K 2
 
6.2%
S 2
 
6.2%
F 1
 
3.1%
D 1
 
3.1%
X 1
 
3.1%
Other values (9) 9
28.1%
Decimal Number
ValueCountFrequency (%)
2 6
75.0%
1 2
 
25.0%
Open Punctuation
ValueCountFrequency (%)
( 100
100.0%
Close Punctuation
ValueCountFrequency (%)
) 100
100.0%
Other Symbol
ValueCountFrequency (%)
㈜ 65
100.0%
Space Separator
ValueCountFrequency (%)
64
100.0%
Other Punctuation
ValueCountFrequency (%)
& 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 2404
88.7%
Common 274
 
10.1%
Latin 32
 
1.2%

Most frequent character per script

Hangul
ValueCountFrequency (%)
주 118
 
4.9%
대 84
 
3.5%
㈜ 65
 
2.7%
구 57
 
2.4%
공 57
 
2.4%
성 55
 
2.3%
원 54
 
2.2%
이 48
 
2.0%
스 46
 
1.9%
업 37
 
1.5%
Other values (300) 1783
74.2%
Latin
ValueCountFrequency (%)
T 6
18.8%
V 3
 
9.4%
A 3
 
9.4%
E 2
 
6.2%
H 2
 
6.2%
K 2
 
6.2%
S 2
 
6.2%
F 1
 
3.1%
D 1
 
3.1%
X 1
 
3.1%
Other values (9) 9
28.1%
Common
ValueCountFrequency (%)
( 100
36.5%
) 100
36.5%
64
23.4%
2 6
 
2.2%
1 2
 
0.7%
& 2
 
0.7%

Most occurring blocks

ValueCountFrequency (%)
Hangul 2339
86.3%
ASCII 306
 
11.3%
None 65
 
2.4%

Most frequent character per block

Hangul
ValueCountFrequency (%)
주 118
 
5.0%
대 84
 
3.6%
구 57
 
2.4%
공 57
 
2.4%
성 55
 
2.4%
원 54
 
2.3%
이 48
 
2.1%
스 46
 
2.0%
업 37
 
1.6%
병 36
 
1.5%
Other values (299) 1747
74.7%
ASCII
ValueCountFrequency (%)
( 100
32.7%
) 100
32.7%
64
20.9%
2 6
 
2.0%
T 6
 
2.0%
V 3
 
1.0%
A 3
 
1.0%
E 2
 
0.7%
1 2
 
0.7%
H 2
 
0.7%
Other values (15) 18
 
5.9%
None
ValueCountFrequency (%)
㈜ 65
100.0%

주소
Text

Distinct346
Distinct (%)98.0%
Missing0
Missing (%)0.0%
Memory size2.9 KiB
2023-12-12T23:25:03.417121image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length45
Median length34
Mean length24.654391
Min length20

Characters and Unicode

Total characters8703
Distinct characters112
Distinct categories9 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique340 ?
Unique (%)96.3%

Sample

1st row대구광역시 달서구 성서로72길 82 (갈산동)
2nd row대구광역시 달서구 달구벌대로 1095 (신당동)
3rd row대구광역시 달서구 성서로71길 7 (갈산동)
4th row대구광역시 달서구 성서로 281 (갈산동)
5th row대구광역시 달서구 성서로 276 (장동)
ValueCountFrequency (%)
대구광역시 353
21.5%
달서구 353
21.5%
대천동 38
 
2.3%
갈산동 28
 
1.7%
월암동 25
 
1.5%
성서공단로 20
 
1.2%
월배로 20
 
1.2%
성서로 18
 
1.1%
달구벌대로 17
 
1.0%
장동 16
 
1.0%
Other values (433) 755
46.0%
2023-12-12T23:25:03.881459image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1290
 
14.8%
구 740
 
8.5%
서 581
 
6.7%
대 465
 
5.3%
달 407
 
4.7%
동 374
 
4.3%
역 353
 
4.1%
시 353
 
4.1%
광 353
 
4.1%
) 352
 
4.0%
Other values (102) 3435
39.5%

Most occurring categories

ValueCountFrequency (%)
Other Letter 5512
63.3%
Space Separator 1290
 
14.8%
Decimal Number 1168
 
13.4%
Close Punctuation 352
 
4.0%
Open Punctuation 352
 
4.0%
Dash Punctuation 18
 
0.2%
Connector Punctuation 7
 
0.1%
Other Punctuation 3
 
< 0.1%
Uppercase Letter 1
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
구 740
13.4%
서 581
10.5%
대 465
 
8.4%
달 407
 
7.4%
동 374
 
6.8%
역 353
 
6.4%
시 353
 
6.4%
광 353
 
6.4%
로 343
 
6.2%
성 206
 
3.7%
Other values (85) 1337
24.3%
Decimal Number
ValueCountFrequency (%)
1 207
17.7%
2 186
15.9%
3 136
11.6%
5 134
11.5%
4 119
10.2%
6 96
8.2%
0 93
8.0%
7 80
 
6.8%
8 62
 
5.3%
9 55
 
4.7%
Space Separator
ValueCountFrequency (%)
1290
100.0%
Close Punctuation
ValueCountFrequency (%)
) 352
100.0%
Open Punctuation
ValueCountFrequency (%)
( 352
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 18
100.0%
Connector Punctuation
ValueCountFrequency (%)
_ 7
100.0%
Other Punctuation
ValueCountFrequency (%)
, 3
100.0%
Uppercase Letter
ValueCountFrequency (%)
M 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 5512
63.3%
Common 3190
36.7%
Latin 1
 
< 0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
구 740
13.4%
서 581
10.5%
대 465
 
8.4%
달 407
 
7.4%
동 374
 
6.8%
역 353
 
6.4%
시 353
 
6.4%
광 353
 
6.4%
로 343
 
6.2%
성 206
 
3.7%
Other values (85) 1337
24.3%
Common
ValueCountFrequency (%)
1290
40.4%
) 352
 
11.0%
( 352
 
11.0%
1 207
 
6.5%
2 186
 
5.8%
3 136
 
4.3%
5 134
 
4.2%
4 119
 
3.7%
6 96
 
3.0%
0 93
 
2.9%
Other values (6) 225
 
7.1%
Latin
ValueCountFrequency (%)
M 1
100.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 5512
63.3%
ASCII 3191
36.7%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1290
40.4%
) 352
 
11.0%
( 352
 
11.0%
1 207
 
6.5%
2 186
 
5.8%
3 136
 
4.3%
5 134
 
4.2%
4 119
 
3.7%
6 96
 
3.0%
0 93
 
2.9%
Other values (7) 226
 
7.1%
Hangul
ValueCountFrequency (%)
구 740
13.4%
서 581
10.5%
대 465
 
8.4%
달 407
 
7.4%
동 374
 
6.8%
역 353
 
6.4%
시 353
 
6.4%
광 353
 
6.4%
로 343
 
6.2%
성 206
 
3.7%
Other values (85) 1337
24.3%

담당부서
Categorical

CONSTANT 

Distinct1
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Memory size2.9 KiB
대구광역시 달서구 청소과
353 

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 353
100.0%

Length

2023-12-12T23:25:04.074239image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T23:25:04.206198image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
대구광역시 353
33.3%
달서구 353
33.3%
청소과 353
33.3%

기준일자
Categorical

CONSTANT 

Distinct1
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Memory size2.9 KiB
2023-03-20
353 

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 (%)
2023-03-20 353
100.0%

Length

2023-12-12T23:25:04.366839image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T23:25:04.480810image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2023-03-20 353
100.0%

Interactions

2023-12-12T23:25:01.426247image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T23:25:01.207392image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T23:25:01.536320image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T23:25:01.315819image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-12T23:25:04.543590image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
위도경도
위도1.0000.595
경도0.5951.000
2023-12-12T23:25:04.631198image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
위도경도
위도1.000-0.056
경도-0.0561.000

Missing values

2023-12-12T23:25:01.666629image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-12T23:25:01.784971image/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

위도경도상호주소담당부서기준일자
035.848832128.512343(주)대한실업대구광역시 달서구 성서로72길 82 (갈산동)대구광역시 달서구 청소과2023-03-20
135.853557128.481495계명대학교대구광역시 달서구 달구벌대로 1095 (신당동)대구광역시 달서구 청소과2023-03-20
235.849119128.506322대호프라스틱대구광역시 달서구 성서로71길 7 (갈산동)대구광역시 달서구 청소과2023-03-20
335.843126128.506195삼화식품공사대구광역시 달서구 성서로 281 (갈산동)대구광역시 달서구 청소과2023-03-20
435.841921128.507749(주)금복주대구광역시 달서구 성서로 276 (장동)대구광역시 달서구 청소과2023-03-20
535.831397128.489607한국지역난방공사대구광역시 달서구 달서대로 351 (대천동)대구광역시 달서구 청소과2023-03-20
635.823484128.495867대구환경공단 서부사업소대구광역시 달서구 달서대로 210 (대천동)대구광역시 달서구 청소과2023-03-20
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