Overview

Dataset statistics

Number of variables6
Number of observations177
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory8.8 KiB
Average record size in memory50.7 B

Variable types

Categorical1
Text2
Numeric2
DateTime1

Dataset

Description대구광역시 북구_실내공기질관리대상시설_20230711
Author대구광역시 북구
URLhttp://data.daegu.go.kr/open/data/dataView.do?dataSetId=15006299&dataSetDetailId=150062991b415a181aab4&provdMethod=FILE

Alerts

데이터기준일자 has constant value ""Constant

Reproduction

Analysis started2023-12-10 18:26:31.565982
Analysis finished2023-12-10 18:26:33.093535
Duration1.53 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

시설군
Categorical

Distinct16
Distinct (%)9.0%
Missing0
Missing (%)0.0%
Memory size1.5 KiB
어린이집
41 
의료기관
38 
실내주차장
33 
인터넷컴퓨터게임시설제공업
19 
대규모점포
16 
Other values (11)
30 

Length

Max length13
Median length9
Mean length5.4067797
Min length3

Unique

Unique3 ?
Unique (%)1.7%

Sample

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

Common Values

ValueCountFrequency (%)
어린이집 41
23.2%
의료기관 38
21.5%
실내주차장 33
18.6%
인터넷컴퓨터게임시설제공업 19
10.7%
대규모점포 16
 
9.0%
노인요양시설 9
 
5.1%
산후조리원 4
 
2.3%
영화관 4
 
2.3%
도서관 2
 
1.1%
박물관 2
 
1.1%
Other values (6) 9
 
5.1%

Length

2023-12-11T03:26:33.230529image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
어린이집 41
23.0%
의료기관 38
21.3%
실내주차장 33
18.5%
인터넷컴퓨터게임시설제공업 19
10.7%
대규모점포 16
 
9.0%
노인요양시설 9
 
5.1%
산후조리원 4
 
2.2%
영화관 4
 
2.2%
지하역사 2
 
1.1%
실내어린이놀이시설 2
 
1.1%
Other values (7) 10
 
5.6%

시설명
Text

Distinct160
Distinct (%)90.4%
Missing0
Missing (%)0.0%
Memory size1.5 KiB
2023-12-11T03:26:33.620664image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length21
Median length17
Mean length7.6497175
Min length3

Characters and Unicode

Total characters1354
Distinct characters270
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

Unique144 ?
Unique (%)81.4%

Sample

1st row늘봄요양원
2nd row대경장기요양기관
3rd row복음실버타운
4th row새볕실버빌
5th row효성실버타운
ValueCountFrequency (%)
칠곡경북대학교병원 4
 
1.8%
㈜엑스코 3
 
1.4%
칠성점 2
 
0.9%
로즈마리병원 2
 
0.9%
k병원 2
 
0.9%
어린이집 2
 
0.9%
의료법인효민의료재단 2
 
0.9%
의료법인 2
 
0.9%
pc방 2
 
0.9%
동아백화점 2
 
0.9%
Other values (173) 194
89.4%
2023-12-11T03:26:34.378792image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
원 52
 
3.8%
이 51
 
3.8%
병 43
 
3.2%
린 43
 
3.2%
어 42
 
3.1%
집 41
 
3.0%
40
 
3.0%
대 36
 
2.7%
구 26
 
1.9%
C 22
 
1.6%
Other values (260) 958
70.8%

Most occurring categories

ValueCountFrequency (%)
Other Letter 1194
88.2%
Uppercase Letter 52
 
3.8%
Space Separator 40
 
3.0%
Close Punctuation 18
 
1.3%
Open Punctuation 18
 
1.3%
Lowercase Letter 14
 
1.0%
Other Symbol 8
 
0.6%
Decimal Number 7
 
0.5%
Dash Punctuation 3
 
0.2%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
원 52
 
4.4%
이 51
 
4.3%
병 43
 
3.6%
린 43
 
3.6%
어 42
 
3.5%
집 41
 
3.4%
대 36
 
3.0%
구 26
 
2.2%
관 19
 
1.6%
점 19
 
1.6%
Other values (233) 822
68.8%
Lowercase Letter
ValueCountFrequency (%)
e 2
14.3%
b 2
14.3%
u 1
7.1%
o 1
7.1%
c 1
7.1%
p 1
7.1%
n 1
7.1%
a 1
7.1%
r 1
7.1%
t 1
7.1%
Other values (2) 2
14.3%
Uppercase Letter
ValueCountFrequency (%)
C 22
42.3%
P 18
34.6%
K 3
 
5.8%
N 2
 
3.8%
M 2
 
3.8%
G 2
 
3.8%
V 2
 
3.8%
D 1
 
1.9%
Decimal Number
ValueCountFrequency (%)
2 4
57.1%
1 3
42.9%
Space Separator
ValueCountFrequency (%)
40
100.0%
Close Punctuation
ValueCountFrequency (%)
) 18
100.0%
Open Punctuation
ValueCountFrequency (%)
( 18
100.0%
Other Symbol
ValueCountFrequency (%)
㈜ 8
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 3
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 1202
88.8%
Common 86
 
6.4%
Latin 66
 
4.9%

Most frequent character per script

Hangul
ValueCountFrequency (%)
원 52
 
4.3%
이 51
 
4.2%
병 43
 
3.6%
린 43
 
3.6%
어 42
 
3.5%
집 41
 
3.4%
대 36
 
3.0%
구 26
 
2.2%
관 19
 
1.6%
점 19
 
1.6%
Other values (234) 830
69.1%
Latin
ValueCountFrequency (%)
C 22
33.3%
P 18
27.3%
K 3
 
4.5%
N 2
 
3.0%
M 2
 
3.0%
G 2
 
3.0%
V 2
 
3.0%
e 2
 
3.0%
b 2
 
3.0%
u 1
 
1.5%
Other values (10) 10
15.2%
Common
ValueCountFrequency (%)
40
46.5%
) 18
20.9%
( 18
20.9%
2 4
 
4.7%
- 3
 
3.5%
1 3
 
3.5%

Most occurring blocks

ValueCountFrequency (%)
Hangul 1194
88.2%
ASCII 152
 
11.2%
None 8
 
0.6%

Most frequent character per block

Hangul
ValueCountFrequency (%)
원 52
 
4.4%
이 51
 
4.3%
병 43
 
3.6%
린 43
 
3.6%
어 42
 
3.5%
집 41
 
3.4%
대 36
 
3.0%
구 26
 
2.2%
관 19
 
1.6%
점 19
 
1.6%
Other values (233) 822
68.8%
ASCII
ValueCountFrequency (%)
40
26.3%
C 22
14.5%
) 18
11.8%
( 18
11.8%
P 18
11.8%
2 4
 
2.6%
- 3
 
2.0%
1 3
 
2.0%
K 3
 
2.0%
N 2
 
1.3%
Other values (16) 21
13.8%
None
ValueCountFrequency (%)
㈜ 8
100.0%

소재지도로명주소
Text

Distinct154
Distinct (%)87.0%
Missing0
Missing (%)0.0%
Memory size1.5 KiB
2023-12-11T03:26:34.930910image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length34
Median length29
Mean length23.186441
Min length14

Characters and Unicode

Total characters4104
Distinct characters94
Distinct categories8 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique136 ?
Unique (%)76.8%

Sample

1st row대구광역시 북구 옥산로 17길 47-1
2nd row대구광역시 북구 칠곡중앙대로 508
3rd row대구광역시 북구 칠곡중앙대로77길 14
4th row대구광역시 북구 영송로 36-6 (태전동)
5th row대구광역시 북구 도남길 92-52
ValueCountFrequency (%)
북구 178
21.6%
대구광역시 177
21.5%
산격동 30
 
3.6%
칠곡중앙대로 16
 
1.9%
유통단지로 15
 
1.8%
동천동 12
 
1.5%
읍내동 10
 
1.2%
칠성동2가 10
 
1.2%
태전동 8
 
1.0%
동천로 7
 
0.9%
Other values (241) 360
43.7%
2023-12-11T03:26:35.773733image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
655
16.0%
구 359
 
8.7%
대 229
 
5.6%
동 202
 
4.9%
북 186
 
4.5%
광 177
 
4.3%
역 177
 
4.3%
시 177
 
4.3%
로 168
 
4.1%
( 156
 
3.8%
Other values (84) 1618
39.4%

Most occurring categories

ValueCountFrequency (%)
Other Letter 2474
60.3%
Space Separator 655
 
16.0%
Decimal Number 603
 
14.7%
Open Punctuation 156
 
3.8%
Close Punctuation 156
 
3.8%
Dash Punctuation 28
 
0.7%
Other Punctuation 26
 
0.6%
Math Symbol 6
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
구 359
14.5%
대 229
 
9.3%
동 202
 
8.2%
북 186
 
7.5%
광 177
 
7.2%
역 177
 
7.2%
시 177
 
7.2%
로 168
 
6.8%
산 60
 
2.4%
길 55
 
2.2%
Other values (67) 684
27.6%
Decimal Number
ValueCountFrequency (%)
1 126
20.9%
2 94
15.6%
3 72
11.9%
4 58
9.6%
0 52
8.6%
5 50
 
8.3%
7 40
 
6.6%
8 39
 
6.5%
9 37
 
6.1%
6 35
 
5.8%
Other Punctuation
ValueCountFrequency (%)
, 24
92.3%
. 2
 
7.7%
Space Separator
ValueCountFrequency (%)
655
100.0%
Open Punctuation
ValueCountFrequency (%)
( 156
100.0%
Close Punctuation
ValueCountFrequency (%)
) 156
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 28
100.0%
Math Symbol
ValueCountFrequency (%)
~ 6
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 2474
60.3%
Common 1630
39.7%

Most frequent character per script

Hangul
ValueCountFrequency (%)
구 359
14.5%
대 229
 
9.3%
동 202
 
8.2%
북 186
 
7.5%
광 177
 
7.2%
역 177
 
7.2%
시 177
 
7.2%
로 168
 
6.8%
산 60
 
2.4%
길 55
 
2.2%
Other values (67) 684
27.6%
Common
ValueCountFrequency (%)
655
40.2%
( 156
 
9.6%
) 156
 
9.6%
1 126
 
7.7%
2 94
 
5.8%
3 72
 
4.4%
4 58
 
3.6%
0 52
 
3.2%
5 50
 
3.1%
7 40
 
2.5%
Other values (7) 171
 
10.5%

Most occurring blocks

ValueCountFrequency (%)
Hangul 2474
60.3%
ASCII 1630
39.7%

Most frequent character per block

ASCII
ValueCountFrequency (%)
655
40.2%
( 156
 
9.6%
) 156
 
9.6%
1 126
 
7.7%
2 94
 
5.8%
3 72
 
4.4%
4 58
 
3.6%
0 52
 
3.2%
5 50
 
3.1%
7 40
 
2.5%
Other values (7) 171
 
10.5%
Hangul
ValueCountFrequency (%)
구 359
14.5%
대 229
 
9.3%
동 202
 
8.2%
북 186
 
7.5%
광 177
 
7.2%
역 177
 
7.2%
시 177
 
7.2%
로 168
 
6.8%
산 60
 
2.4%
길 55
 
2.2%
Other values (67) 684
27.6%

위도
Real number (ℝ)

Distinct146
Distinct (%)82.5%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean35.91279
Minimum35.875258
Maximum35.960496
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.7 KiB
2023-12-11T03:26:36.048740image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum35.875258
5-th percentile35.879807
Q135.891081
median35.90637
Q335.938742
95-th percentile35.951227
Maximum35.960496
Range0.08523849
Interquartile range (IQR)0.04766012

Descriptive statistics

Standard deviation0.024547919
Coefficient of variation (CV)0.00068354253
Kurtosis-1.3074729
Mean35.91279
Median Absolute Deviation (MAD)0.02114646
Skewness0.25303839
Sum6356.5638
Variance0.00060260035
MonotonicityNot monotonic
2023-12-11T03:26:36.347328image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
35.88522335 5
 
2.8%
35.95614888 4
 
2.3%
35.907096 3
 
1.7%
35.88901082 2
 
1.1%
35.90627781 2
 
1.1%
35.93326327 2
 
1.1%
35.89776727 2
 
1.1%
35.94321421 2
 
1.1%
35.94218512 2
 
1.1%
35.88464445 2
 
1.1%
Other values (136) 151
85.3%
ValueCountFrequency (%)
35.87525798 1
0.6%
35.875822 1
0.6%
35.87588137 2
1.1%
35.876085 1
0.6%
35.87627813 1
0.6%
35.8764813 1
0.6%
35.8773901 1
0.6%
35.87939084 1
0.6%
35.87991109 1
0.6%
35.88083435 1
0.6%
ValueCountFrequency (%)
35.96049647 1
 
0.6%
35.95892855 1
 
0.6%
35.95614888 4
2.3%
35.95403868 1
 
0.6%
35.95339899 1
 
0.6%
35.95127824 1
 
0.6%
35.95121377 1
 
0.6%
35.9511185 1
 
0.6%
35.95082811 1
 
0.6%
35.95070431 1
 
0.6%

경도
Real number (ℝ)

Distinct146
Distinct (%)82.5%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean128.58175
Minimum128.51064
Maximum128.62591
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.7 KiB
2023-12-11T03:26:36.631875image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum128.51064
5-th percentile128.5445
Q1128.55774
median128.58682
Q3128.60702
95-th percentile128.6181
Maximum128.62591
Range0.1152719
Interquartile range (IQR)0.0492815

Descriptive statistics

Standard deviation0.02733121
Coefficient of variation (CV)0.00021255902
Kurtosis-1.1374093
Mean128.58175
Median Absolute Deviation (MAD)0.024463
Skewness-0.22752111
Sum22758.969
Variance0.00074699504
MonotonicityNot monotonic
2023-12-11T03:26:36.917526image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
128.5897872 5
 
2.8%
128.5652838 4
 
2.3%
128.613163 3
 
1.7%
128.6145155 2
 
1.1%
128.6096639 2
 
1.1%
128.5481089 2
 
1.1%
128.6136085 2
 
1.1%
128.5577764 2
 
1.1%
128.5638873 2
 
1.1%
128.6046687 2
 
1.1%
Other values (136) 151
85.3%
ValueCountFrequency (%)
128.5106393 1
0.6%
128.515231 1
0.6%
128.5167786 1
0.6%
128.5359228 1
0.6%
128.5411904 1
0.6%
128.5425504 1
0.6%
128.5432542 1
0.6%
128.5440776 1
0.6%
128.544441 1
0.6%
128.5445149 1
0.6%
ValueCountFrequency (%)
128.6259112 1
0.6%
128.62576 1
0.6%
128.6228357 1
0.6%
128.622297 1
0.6%
128.6216195 1
0.6%
128.6212553 1
0.6%
128.6212389 1
0.6%
128.6195792 1
0.6%
128.6180955 2
1.1%
128.6173444 1
0.6%

데이터기준일자
Date

CONSTANT 

Distinct1
Distinct (%)0.6%
Missing0
Missing (%)0.0%
Memory size1.5 KiB
Minimum2023-07-11 00:00:00
Maximum2023-07-11 00:00:00
2023-12-11T03:26:37.135144image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T03:26:37.320168image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=1)

Interactions

2023-12-11T03:26:32.383815image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T03:26:32.069111image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T03:26:32.544152image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T03:26:32.226312image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-11T03:26:37.448501image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
시설군위도경도
시설군1.0000.5240.387
위도0.5241.0000.731
경도0.3870.7311.000
2023-12-11T03:26:37.610270image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
위도경도시설군
위도1.000-0.4680.230
경도-0.4681.0000.125
시설군0.2300.1251.000

Missing values

2023-12-11T03:26:32.774380image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-11T03:26:33.015780image/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

시설군시설명소재지도로명주소위도경도데이터기준일자
0노인요양시설늘봄요양원대구광역시 북구 옥산로 17길 47-135.888614128.585772023-07-11
1노인요양시설대경장기요양기관대구광역시 북구 칠곡중앙대로 50835.940778128.5505552023-07-11
2노인요양시설복음실버타운대구광역시 북구 칠곡중앙대로77길 1435.930872128.5466962023-07-11
3노인요양시설새볕실버빌대구광역시 북구 영송로 36-6 (태전동)35.928326128.5458032023-07-11
4노인요양시설효성실버타운대구광역시 북구 도남길 92-5235.960496128.5852372023-07-11
5노인요양시설파티마홈대구광역시 북구 내곡로 12335.900982128.5167792023-07-11
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