Overview

Dataset statistics

Number of variables7
Number of observations218
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory12.5 KiB
Average record size in memory58.6 B

Variable types

Categorical2
Text2
Numeric2
DateTime1

Dataset

Description대구광역시 달서구_실내공기질 관리대상시설_20230110
Author대구광역시 달서구
URLhttp://data.daegu.go.kr/open/data/dataView.do?dataSetId=15073506&dataSetDetailId=150735061e192f779fc9f&provdMethod=FILE

Alerts

자료 기준일자 has constant value ""Constant
경도 is highly overall correlated with 행정동High correlation
위도 is highly overall correlated with 행정동High correlation
행정동 is highly overall correlated with 경도 and 1 other fieldsHigh correlation

Reproduction

Analysis started2024-04-21 02:35:18.379960
Analysis finished2024-04-21 02:35:20.027163
Duration1.65 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

시설구분
Categorical

Distinct15
Distinct (%)6.9%
Missing0
Missing (%)0.0%
Memory size1.8 KiB
어린이집
52 
의료기관
46 
PC영업시설
39 
실내주차장
24 
지하역사
15 
Other values (10)
42 

Length

Max length9
Median length4
Mean length4.7247706
Min length2

Unique

Unique4 ?
Unique (%)1.8%

Sample

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

Common Values

ValueCountFrequency (%)
어린이집 52
23.9%
의료기관 46
21.1%
PC영업시설 39
17.9%
실내주차장 24
11.0%
지하역사 15
 
6.9%
노인요양시설 14
 
6.4%
산후조리원 7
 
3.2%
대규모점포 6
 
2.8%
목욕장 4
 
1.8%
실내어린이놀이시설 4
 
1.8%
Other values (5) 7
 
3.2%

Length

2024-04-21T11:35:20.157594image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
어린이집 52
23.9%
의료기관 46
21.1%
pc영업시설 39
17.9%
실내주차장 24
11.0%
지하역사 15
 
6.9%
노인요양시설 14
 
6.4%
산후조리원 7
 
3.2%
대규모점포 6
 
2.8%
목욕장 4
 
1.8%
실내어린이놀이시설 4
 
1.8%
Other values (5) 7
 
3.2%

시설명
Text

Distinct214
Distinct (%)98.2%
Missing0
Missing (%)0.0%
Memory size1.8 KiB
2024-04-21T11:35:20.890970image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length19
Median length15
Mean length7.2201835
Min length3

Characters and Unicode

Total characters1574
Distinct characters287
Distinct categories9 ?
Distinct scripts3 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique210 ?
Unique (%)96.3%

Sample

1st row먼스PC방
2nd row왓썹PC방
3rd row캐슬PC방
4th row앤유PC 대천점
5th row런PC방
ValueCountFrequency (%)
앤유pc 5
 
1.9%
홈플러스 4
 
1.5%
앤유pc방 4
 
1.5%
상인점 4
 
1.5%
성서점 3
 
1.1%
계명대학교 3
 
1.1%
롯데백화점(주 2
 
0.7%
pc방 2
 
0.7%
롯데시네마 2
 
0.7%
성서 2
 
0.7%
Other values (229) 238
88.5%
2024-04-21T11:35:21.968513image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
이 72
 
4.6%
원 71
 
4.5%
린 57
 
3.6%
어 54
 
3.4%
집 52
 
3.3%
51
 
3.2%
병 46
 
2.9%
대 36
 
2.3%
P 35
 
2.2%
C 35
 
2.2%
Other values (277) 1065
67.7%

Most occurring categories

ValueCountFrequency (%)
Other Letter 1411
89.6%
Uppercase Letter 87
 
5.5%
Space Separator 51
 
3.2%
Open Punctuation 9
 
0.6%
Close Punctuation 9
 
0.6%
Lowercase Letter 4
 
0.3%
Other Symbol 1
 
0.1%
Decimal Number 1
 
0.1%
Other Punctuation 1
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
이 72
 
5.1%
원 71
 
5.0%
린 57
 
4.0%
어 54
 
3.8%
집 52
 
3.7%
병 46
 
3.3%
대 36
 
2.6%
점 31
 
2.2%
방 30
 
2.1%
성 30
 
2.1%
Other values (251) 932
66.1%
Uppercase Letter
ValueCountFrequency (%)
P 35
40.2%
C 35
40.2%
O 2
 
2.3%
G 2
 
2.3%
B 2
 
2.3%
Y 1
 
1.1%
V 1
 
1.1%
D 1
 
1.1%
A 1
 
1.1%
U 1
 
1.1%
Other values (6) 6
 
6.9%
Lowercase Letter
ValueCountFrequency (%)
n 1
25.0%
e 1
25.0%
f 1
25.0%
a 1
25.0%
Space Separator
ValueCountFrequency (%)
51
100.0%
Open Punctuation
ValueCountFrequency (%)
( 9
100.0%
Close Punctuation
ValueCountFrequency (%)
) 9
100.0%
Other Symbol
ValueCountFrequency (%)
㈜ 1
100.0%
Decimal Number
ValueCountFrequency (%)
5 1
100.0%
Other Punctuation
ValueCountFrequency (%)
' 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 1412
89.7%
Latin 91
 
5.8%
Common 71
 
4.5%

Most frequent character per script

Hangul
ValueCountFrequency (%)
이 72
 
5.1%
원 71
 
5.0%
린 57
 
4.0%
어 54
 
3.8%
집 52
 
3.7%
병 46
 
3.3%
대 36
 
2.5%
점 31
 
2.2%
방 30
 
2.1%
성 30
 
2.1%
Other values (252) 933
66.1%
Latin
ValueCountFrequency (%)
P 35
38.5%
C 35
38.5%
O 2
 
2.2%
G 2
 
2.2%
B 2
 
2.2%
Y 1
 
1.1%
n 1
 
1.1%
V 1
 
1.1%
D 1
 
1.1%
A 1
 
1.1%
Other values (10) 10
 
11.0%
Common
ValueCountFrequency (%)
51
71.8%
( 9
 
12.7%
) 9
 
12.7%
5 1
 
1.4%
' 1
 
1.4%

Most occurring blocks

ValueCountFrequency (%)
Hangul 1411
89.6%
ASCII 162
 
10.3%
None 1
 
0.1%

Most frequent character per block

Hangul
ValueCountFrequency (%)
이 72
 
5.1%
원 71
 
5.0%
린 57
 
4.0%
어 54
 
3.8%
집 52
 
3.7%
병 46
 
3.3%
대 36
 
2.6%
점 31
 
2.2%
방 30
 
2.1%
성 30
 
2.1%
Other values (251) 932
66.1%
ASCII
ValueCountFrequency (%)
51
31.5%
P 35
21.6%
C 35
21.6%
( 9
 
5.6%
) 9
 
5.6%
O 2
 
1.2%
G 2
 
1.2%
B 2
 
1.2%
Y 1
 
0.6%
n 1
 
0.6%
Other values (15) 15
 
9.3%
None
ValueCountFrequency (%)
㈜ 1
100.0%

주소
Text

Distinct211
Distinct (%)96.8%
Missing0
Missing (%)0.0%
Memory size1.8 KiB
2024-04-21T11:35:22.993615image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length48
Median length39
Mean length25.256881
Min length16

Characters and Unicode

Total characters5506
Distinct characters121
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

Unique204 ?
Unique (%)93.6%

Sample

1st row대구광역시 달서구 죽전4길 91, 4층 (감삼동)
2nd row대구광역시 달서구 달구벌대로 1516, 5층 (감삼동)
3rd row대구광역시 달서구 달구벌대로 1601, 2층 (감삼동)
4th row대구광역시 달서구 조암남로26길 29, 3층 (대천동)
5th row대구광역시 달서구 한실로 91
ValueCountFrequency (%)
대구광역시 218
19.4%
달서구 217
19.4%
월배로 32
 
2.9%
달구벌대로 25
 
2.2%
진천동 24
 
2.1%
상인동 21
 
1.9%
이곡동 19
 
1.7%
송현동 18
 
1.6%
두류동 15
 
1.3%
월성동 14
 
1.2%
Other values (322) 518
46.2%
2024-04-21T11:35:24.278493image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
906
 
16.5%
구 473
 
8.6%
대 270
 
4.9%
달 248
 
4.5%
서 232
 
4.2%
동 223
 
4.1%
역 218
 
4.0%
시 218
 
4.0%
광 218
 
4.0%
로 194
 
3.5%
Other values (111) 2306
41.9%

Most occurring categories

ValueCountFrequency (%)
Other Letter 3288
59.7%
Space Separator 906
 
16.5%
Decimal Number 819
 
14.9%
Close Punctuation 191
 
3.5%
Open Punctuation 191
 
3.5%
Other Punctuation 70
 
1.3%
Dash Punctuation 30
 
0.5%
Math Symbol 9
 
0.2%
Uppercase Letter 2
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
구 473
14.4%
대 270
 
8.2%
달 248
 
7.5%
서 232
 
7.1%
동 223
 
6.8%
역 218
 
6.6%
시 218
 
6.6%
광 218
 
6.6%
로 194
 
5.9%
월 65
 
2.0%
Other values (93) 929
28.3%
Decimal Number
ValueCountFrequency (%)
1 186
22.7%
2 110
13.4%
4 85
10.4%
3 82
10.0%
0 70
 
8.5%
5 69
 
8.4%
6 62
 
7.6%
7 54
 
6.6%
9 53
 
6.5%
8 48
 
5.9%
Uppercase Letter
ValueCountFrequency (%)
B 1
50.0%
A 1
50.0%
Space Separator
ValueCountFrequency (%)
906
100.0%
Close Punctuation
ValueCountFrequency (%)
) 191
100.0%
Open Punctuation
ValueCountFrequency (%)
( 191
100.0%
Other Punctuation
ValueCountFrequency (%)
, 70
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 30
100.0%
Math Symbol
ValueCountFrequency (%)
~ 9
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 3288
59.7%
Common 2216
40.2%
Latin 2
 
< 0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
구 473
14.4%
대 270
 
8.2%
달 248
 
7.5%
서 232
 
7.1%
동 223
 
6.8%
역 218
 
6.6%
시 218
 
6.6%
광 218
 
6.6%
로 194
 
5.9%
월 65
 
2.0%
Other values (93) 929
28.3%
Common
ValueCountFrequency (%)
906
40.9%
) 191
 
8.6%
( 191
 
8.6%
1 186
 
8.4%
2 110
 
5.0%
4 85
 
3.8%
3 82
 
3.7%
0 70
 
3.2%
, 70
 
3.2%
5 69
 
3.1%
Other values (6) 256
 
11.6%
Latin
ValueCountFrequency (%)
B 1
50.0%
A 1
50.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 3288
59.7%
ASCII 2218
40.3%

Most frequent character per block

ASCII
ValueCountFrequency (%)
906
40.8%
) 191
 
8.6%
( 191
 
8.6%
1 186
 
8.4%
2 110
 
5.0%
4 85
 
3.8%
3 82
 
3.7%
0 70
 
3.2%
, 70
 
3.2%
5 69
 
3.1%
Other values (8) 258
 
11.6%
Hangul
ValueCountFrequency (%)
구 473
14.4%
대 270
 
8.2%
달 248
 
7.5%
서 232
 
7.1%
동 223
 
6.8%
역 218
 
6.6%
시 218
 
6.6%
광 218
 
6.6%
로 194
 
5.9%
월 65
 
2.0%
Other values (93) 929
28.3%

행정동
Categorical

HIGH CORRELATION 

Distinct29
Distinct (%)13.3%
Missing0
Missing (%)0.0%
Memory size1.8 KiB
진천동
28 
신당동
16 
감삼동
16 
월성1동
15 
송현1동
 
11
Other values (24)
132 

Length

Max length6
Median length4
Mean length3.5412844
Min length2

Unique

Unique5 ?
Unique (%)2.3%

Sample

1st row감삼동
2nd row감삼동
3rd row감삼동
4th row월성1동
5th row도원동

Common Values

ValueCountFrequency (%)
진천동 28
 
12.8%
신당동 16
 
7.3%
감삼동 16
 
7.3%
월성1동 15
 
6.9%
송현1동 11
 
5.0%
상인2동 10
 
4.6%
이곡1동 10
 
4.6%
상인1동 10
 
4.6%
용산1동 9
 
4.1%
이곡2동 9
 
4.1%
Other values (19) 84
38.5%

Length

2024-04-21T11:35:24.529603image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
진천동 28
 
12.8%
감삼동 16
 
7.3%
신당동 16
 
7.3%
월성1동 15
 
6.9%
송현1동 11
 
5.0%
상인2동 10
 
4.6%
이곡1동 10
 
4.6%
상인1동 10
 
4.6%
용산1동 9
 
4.1%
이곡2동 9
 
4.1%
Other values (19) 84
38.5%

경도
Real number (ℝ)

HIGH CORRELATION 

Distinct202
Distinct (%)92.7%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean128.53167
Minimum128.47368
Maximum128.5742
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size2.0 KiB
2024-04-21T11:35:24.776522image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum128.47368
5-th percentile128.49263
Q1128.52148
median128.53399
Q3128.54561
95-th percentile128.55898
Maximum128.5742
Range0.1005215
Interquartile range (IQR)0.024126925

Descriptive statistics

Standard deviation0.020095784
Coefficient of variation (CV)0.00015634889
Kurtosis0.25157011
Mean128.53167
Median Absolute Deviation (MAD)0.01211735
Skewness-0.57038812
Sum28019.904
Variance0.00040384052
MonotonicityNot monotonic
2024-04-21T11:35:25.037210image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
128.5274033 3
 
1.4%
128.5561448 2
 
0.9%
128.5325527 2
 
0.9%
128.5256582 2
 
0.9%
128.5368032 2
 
0.9%
128.5295833 2
 
0.9%
128.5213207 2
 
0.9%
128.5363662 2
 
0.9%
128.5568597 2
 
0.9%
128.4801355 2
 
0.9%
Other values (192) 197
90.4%
ValueCountFrequency (%)
128.4736813 1
0.5%
128.4783481 1
0.5%
128.4788722 1
0.5%
128.4801355 2
0.9%
128.4814952 1
0.5%
128.4863475 1
0.5%
128.4893969 1
0.5%
128.4909032 1
0.5%
128.4913721 1
0.5%
128.4919782 1
0.5%
ValueCountFrequency (%)
128.5742028 1
0.5%
128.5732847 1
0.5%
128.5731899 1
0.5%
128.5725534 1
0.5%
128.5698397 1
0.5%
128.5681601 1
0.5%
128.5654398 1
0.5%
128.5609166 1
0.5%
128.5607907 1
0.5%
128.5604387 1
0.5%

위도
Real number (ℝ)

HIGH CORRELATION 

Distinct202
Distinct (%)92.7%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean35.835602
Minimum35.802888
Maximum35.862197
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size2.0 KiB
2024-04-21T11:35:25.279817image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum35.802888
5-th percentile35.808914
Q135.818351
median35.837259
Q335.852053
95-th percentile35.85783
Maximum35.862197
Range0.05930904
Interquartile range (IQR)0.03370199

Descriptive statistics

Standard deviation0.017481247
Coefficient of variation (CV)0.00048781787
Kurtosis-1.4369373
Mean35.835602
Median Absolute Deviation (MAD)0.01645535
Skewness-0.22397516
Sum7812.1613
Variance0.000305594
MonotonicityNot monotonic
2024-04-21T11:35:25.604553image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
35.84945213 3
 
1.4%
35.8370371 2
 
0.9%
35.81827935 2
 
0.9%
35.82497063 2
 
0.9%
35.85121305 2
 
0.9%
35.81608424 2
 
0.9%
35.81329928 2
 
0.9%
35.8455096 2
 
0.9%
35.85690806 2
 
0.9%
35.8538871 2
 
0.9%
Other values (192) 197
90.4%
ValueCountFrequency (%)
35.80288797 1
0.5%
35.80428973 1
0.5%
35.80455135 1
0.5%
35.80469338 2
0.9%
35.80674904 1
0.5%
35.80700234 1
0.5%
35.80702145 1
0.5%
35.80770309 1
0.5%
35.80816466 1
0.5%
35.80864887 1
0.5%
ValueCountFrequency (%)
35.86219701 1
0.5%
35.86111393 1
0.5%
35.8606118 1
0.5%
35.86015477 1
0.5%
35.85995043 1
0.5%
35.8594593 1
0.5%
35.85913345 1
0.5%
35.85887818 1
0.5%
35.85855719 1
0.5%
35.85850123 1
0.5%

자료 기준일자
Date

CONSTANT 

Distinct1
Distinct (%)0.5%
Missing0
Missing (%)0.0%
Memory size1.8 KiB
Minimum2023-01-10 00:00:00
Maximum2023-01-10 00:00:00
2024-04-21T11:35:25.857229image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T11:35:26.015009image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=1)

Interactions

2024-04-21T11:35:19.401234image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T11:35:18.973156image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T11:35:19.548979image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T11:35:19.208906image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-04-21T11:35:26.137357image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
시설구분행정동경도위도
시설구분1.0000.7130.4290.000
행정동0.7131.0000.9120.936
경도0.4290.9121.0000.661
위도0.0000.9360.6611.000
2024-04-21T11:35:26.289870image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
행정동시설구분
행정동1.0000.282
시설구분0.2821.000
2024-04-21T11:35:26.427869image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
경도위도시설구분행정동
경도1.000-0.0380.1480.598
위도-0.0381.0000.0000.661
시설구분0.1480.0001.0000.282
행정동0.5980.6610.2821.000

Missing values

2024-04-21T11:35:19.756924image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-04-21T11:35:19.951220image/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

시설구분시설명주소행정동경도위도자료 기준일자
0PC영업시설먼스PC방대구광역시 달서구 죽전4길 91, 4층 (감삼동)감삼동128.54499335.8555932023-01-10
1PC영업시설왓썹PC방대구광역시 달서구 달구벌대로 1516, 5층 (감삼동)감삼동128.53298235.8493552023-01-10
2PC영업시설캐슬PC방대구광역시 달서구 달구벌대로 1601, 2층 (감삼동)감삼동128.54165935.8521922023-01-10
3PC영업시설앤유PC 대천점대구광역시 달서구 조암남로26길 29, 3층 (대천동)월성1동128.51724635.8196712023-01-10
4PC영업시설런PC방대구광역시 달서구 한실로 91도원동128.53664935.8070212023-01-10
5PC영업시설문(MOON) PC방대구광역시 달서구 한실로 93, 2층 (도원동)도원동128.53689235.8070022023-01-10
6PC영업시설쓰리팝피씨방(두류점)대구광역시 달서구 야외음악당로39길 72, 3~4층 (두류동)두류3동128.5532835.8548612023-01-10
7PC영업시설앤유PC대구광역시 달서구 달구벌대로 1698, 5층 (두류동)두류3동128.55156635.8551572023-01-10
8PC영업시설캐슬PC대구광역시 달서구 와룡로 95, 3층 (본리동)본리동128.53643735.8412822023-01-10
9PC영업시설와써PC방 대구본리점대구광역시 달서구 장기로 167, 223동 303호 (본리동, 성당 래미안 이편한세상)본리동128.54266135.8432012023-01-10
시설구분시설명주소행정동경도위도자료 기준일자
208지하역사송현역대구광역시 달서구 송현동 950송현2동128.5490635.8370252023-01-10
209지하역사계명대역대구광역시 달서구 신당동 1034-4신당동128.49197835.8515052023-01-10
210지하역사용산역대구광역시 달서구 용산동 215-9용산1동128.52839635.8489612023-01-10
211지하역사이곡역대구광역시 달서구 용산동 707-2용산2동128.52628135.8571452023-01-10
212지하역사성서산업단지역대구광역시 달서구 이곡동 653-4이곡1동128.50724735.8517292023-01-10
213지하역사죽전역대구광역시 달서구 감삼동 338감삼동128.5386435.8445712023-01-10
214지하역사진천역대구광역시 달서구 진천동 608-4진천동128.52311735.8138862023-01-10
215지하역사월배역대구광역시 달서구 진천동 49-4진천동128.53032535.8161442023-01-10
216지하역사강창역대구광역시 달서구 호산동 102-2신당동128.47834835.8530742023-01-10
217학원윤성회계캐드컴퓨터학원대구광역시 달서구 두류공원로 248(두류동)두류동128.55944335.8558052023-01-10