Overview

Dataset statistics

Number of variables14
Number of observations137
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory15.8 KiB
Average record size in memory118.0 B

Variable types

Categorical7
Numeric3
DateTime1
Text3

Dataset

Description광주교통공사 1호선 역사 인근 500m 이내의 약국에 대한 데이터로 역명, 역까지의 거리(m), 약국에 대한 상세 정보를 제공합니다.
Author광주교통공사
URLhttps://www.data.go.kr/data/15109339/fileData.do

Alerts

상세영업상태코드 has constant value ""Constant
상세영업상태명 has constant value ""Constant
영업상태구분코드 has constant value ""Constant
영업상태명 has constant value ""Constant
위도 is highly overall correlated with 문화노선도명High correlation
경도 is highly overall correlated with 문화노선도명High correlation
문화노선도명 is highly overall correlated with 위도 and 1 other fieldsHigh correlation
데이터갱신일자 is highly overall correlated with 데이터갱신구분High correlation
데이터갱신구분 is highly overall correlated with 데이터갱신일자High correlation

Reproduction

Analysis started2023-12-13 00:40:29.701245
Analysis finished2023-12-13 00:40:31.183193
Duration1.48 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

문화노선도명
Categorical

HIGH CORRELATION 

Distinct17
Distinct (%)12.4%
Missing0
Missing (%)0.0%
Memory size1.2 KiB
문화전당(구도청)
23 
남광주
20 
금남로4가
15 
상무
11 
학동증심사입구
9 
Other values (12)
59 

Length

Max length12
Median length7
Mean length4.7007299
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row운천
2nd row문화전당(구도청)
3rd row문화전당(구도청)
4th row농성
5th row남광주

Common Values

ValueCountFrequency (%)
문화전당(구도청) 23
16.8%
남광주 20
14.6%
금남로4가 15
10.9%
상무 11
8.0%
학동증심사입구 9
 
6.6%
돌고개 8
 
5.8%
금남로5가 7
 
5.1%
화정 7
 
5.1%
송정공원 6
 
4.4%
운천 6
 
4.4%
Other values (7) 25
18.2%

Length

2023-12-13T09:40:31.239045image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
문화전당(구도청 23
16.8%
남광주 20
14.6%
금남로4가 15
10.9%
상무 11
8.0%
학동증심사입구 9
 
6.6%
돌고개 8
 
5.8%
금남로5가 7
 
5.1%
화정 7
 
5.1%
광주송정역 6
 
4.4%
송정공원 6
 
4.4%
Other values (7) 25
18.2%

거리
Real number (ℝ)

Distinct136
Distinct (%)99.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean321.67331
Minimum43.265
Maximum498.112
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.3 KiB
2023-12-13T09:40:31.330217image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum43.265
5-th percentile83.2318
Q1218.315
median346.413
Q3436.858
95-th percentile492.2338
Maximum498.112
Range454.847
Interquartile range (IQR)218.543

Descriptive statistics

Standard deviation131.56525
Coefficient of variation (CV)0.4090027
Kurtosis-0.97496233
Mean321.67331
Median Absolute Deviation (MAD)106.114
Skewness-0.44769206
Sum44069.243
Variance17309.416
MonotonicityNot monotonic
2023-12-13T09:40:31.433441image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
384.164 2
 
1.5%
53.774 1
 
0.7%
450.386 1
 
0.7%
362.845 1
 
0.7%
396.981 1
 
0.7%
181.184 1
 
0.7%
138.751 1
 
0.7%
495.097 1
 
0.7%
418.822 1
 
0.7%
489.929 1
 
0.7%
Other values (126) 126
92.0%
ValueCountFrequency (%)
43.265 1
0.7%
50.201 1
0.7%
53.774 1
0.7%
56.725 1
0.7%
68.485 1
0.7%
69.858 1
0.7%
81.771 1
0.7%
83.597 1
0.7%
85.679 1
0.7%
88.481 1
0.7%
ValueCountFrequency (%)
498.112 1
0.7%
497.195 1
0.7%
497.142 1
0.7%
496.651 1
0.7%
495.483 1
0.7%
495.097 1
0.7%
494.773 1
0.7%
491.599 1
0.7%
491.219 1
0.7%
489.929 1
0.7%

인허가일자
Date

Distinct114
Distinct (%)83.2%
Missing0
Missing (%)0.0%
Memory size1.2 KiB
Minimum1970-05-04 00:00:00
Maximum2022-03-17 00:00:00
2023-12-13T09:40:31.539597image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T09:40:31.647952image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

사업장명
Text

Distinct111
Distinct (%)81.0%
Missing0
Missing (%)0.0%
Memory size1.2 KiB
2023-12-13T09:40:31.873941image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length10
Median length9
Mean length5.2335766
Min length3

Characters and Unicode

Total characters717
Distinct characters147
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

Unique87 ?
Unique (%)63.5%

Sample

1st row운천종로약국
2nd row송현약국
3rd row튼튼한 약국
4th row광주보령약국
5th row남광주 종로약국
ValueCountFrequency (%)
약국 7
 
4.7%
무등산약국 3
 
2.0%
대성약국 3
 
2.0%
하나로누가약국 2
 
1.4%
로뎀약국 2
 
1.4%
호남온누리약국 2
 
1.4%
한미약국 2
 
1.4%
프린스 2
 
1.4%
건강샘약국 2
 
1.4%
광산약국 2
 
1.4%
Other values (106) 121
81.8%
2023-12-13T09:40:32.210137image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
국 139
19.4%
약 137
 
19.1%
로 16
 
2.2%
리 14
 
2.0%
광 13
 
1.8%
한 12
 
1.7%
11
 
1.5%
동 10
 
1.4%
누 10
 
1.4%
종 9
 
1.3%
Other values (137) 346
48.3%

Most occurring categories

ValueCountFrequency (%)
Other Letter 700
97.6%
Space Separator 11
 
1.5%
Decimal Number 6
 
0.8%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
국 139
19.9%
약 137
19.6%
로 16
 
2.3%
리 14
 
2.0%
광 13
 
1.9%
한 12
 
1.7%
동 10
 
1.4%
누 10
 
1.4%
종 9
 
1.3%
남 8
 
1.1%
Other values (132) 332
47.4%
Decimal Number
ValueCountFrequency (%)
5 3
50.0%
3 1
 
16.7%
6 1
 
16.7%
1 1
 
16.7%
Space Separator
ValueCountFrequency (%)
11
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 700
97.6%
Common 17
 
2.4%

Most frequent character per script

Hangul
ValueCountFrequency (%)
국 139
19.9%
약 137
19.6%
로 16
 
2.3%
리 14
 
2.0%
광 13
 
1.9%
한 12
 
1.7%
동 10
 
1.4%
누 10
 
1.4%
종 9
 
1.3%
남 8
 
1.1%
Other values (132) 332
47.4%
Common
ValueCountFrequency (%)
11
64.7%
5 3
 
17.6%
3 1
 
5.9%
6 1
 
5.9%
1 1
 
5.9%

Most occurring blocks

ValueCountFrequency (%)
Hangul 700
97.6%
ASCII 17
 
2.4%

Most frequent character per block

Hangul
ValueCountFrequency (%)
국 139
19.9%
약 137
19.6%
로 16
 
2.3%
리 14
 
2.0%
광 13
 
1.9%
한 12
 
1.7%
동 10
 
1.4%
누 10
 
1.4%
종 9
 
1.3%
남 8
 
1.1%
Other values (132) 332
47.4%
ASCII
ValueCountFrequency (%)
11
64.7%
5 3
 
17.6%
3 1
 
5.9%
6 1
 
5.9%
1 1
 
5.9%

상세영업상태코드
Categorical

CONSTANT 

Distinct1
Distinct (%)0.7%
Missing0
Missing (%)0.0%
Memory size1.2 KiB
13
137 

Length

Max length2
Median length2
Mean length2
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row13
2nd row13
3rd row13
4th row13
5th row13

Common Values

ValueCountFrequency (%)
13 137
100.0%

Length

2023-12-13T09:40:32.320826image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T09:40:32.396044image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
13 137
100.0%

상세영업상태명
Categorical

CONSTANT 

Distinct1
Distinct (%)0.7%
Missing0
Missing (%)0.0%
Memory size1.2 KiB
영업중
137 

Length

Max length3
Median length3
Mean length3
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
영업중 137
100.0%

Length

2023-12-13T09:40:32.471647image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T09:40:32.539549image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
영업중 137
100.0%

위도
Real number (ℝ)

HIGH CORRELATION 

Distinct115
Distinct (%)83.9%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean35.145402
Minimum35.1202
Maximum35.155925
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.3 KiB
2023-12-13T09:40:32.620789image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum35.1202
5-th percentile35.131372
Q135.141578
median35.146656
Q335.151685
95-th percentile35.154019
Maximum35.155925
Range0.0357257
Interquartile range (IQR)0.0101072

Descriptive statistics

Standard deviation0.007423597
Coefficient of variation (CV)0.00021122527
Kurtosis0.82451681
Mean35.145402
Median Absolute Deviation (MAD)0.0050285
Skewness-0.9588513
Sum4814.92
Variance5.5109793 × 10-5
MonotonicityNot monotonic
2023-12-13T09:40:32.732469image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
35.1516849 2
 
1.5%
35.1526226 2
 
1.5%
35.1427999 2
 
1.5%
35.1527683 2
 
1.5%
35.1533344 2
 
1.5%
35.1422042 2
 
1.5%
35.1339978 2
 
1.5%
35.1539058 2
 
1.5%
35.1427763 2
 
1.5%
35.1425636 2
 
1.5%
Other values (105) 117
85.4%
ValueCountFrequency (%)
35.1201997 1
0.7%
35.1218033 1
0.7%
35.1235357 1
0.7%
35.1295539 1
0.7%
35.1299044 1
0.7%
35.1302692 1
0.7%
35.1309491 1
0.7%
35.1314774 1
0.7%
35.1322279 1
0.7%
35.1325293 1
0.7%
ValueCountFrequency (%)
35.1559254 1
0.7%
35.1553768 1
0.7%
35.1548319 1
0.7%
35.1541212 1
0.7%
35.1540264 2
1.5%
35.1540192 2
1.5%
35.1539177 2
1.5%
35.1539058 2
1.5%
35.1538789 1
0.7%
35.1534533 1
0.7%

경도
Real number (ℝ)

HIGH CORRELATION 

Distinct115
Distinct (%)83.9%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean126.89137
Minimum126.789
Maximum126.93334
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.3 KiB
2023-12-13T09:40:32.845759image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum126.789
5-th percentile126.79486
Q1126.8691
median126.91342
Q3126.92077
95-th percentile126.92926
Maximum126.93334
Range0.1443423
Interquartile range (IQR)0.0516644

Descriptive statistics

Standard deviation0.041849959
Coefficient of variation (CV)0.00032980933
Kurtosis0.47396049
Mean126.89137
Median Absolute Deviation (MAD)0.0125471
Skewness-1.267885
Sum17384.118
Variance0.001751419
MonotonicityNot monotonic
2023-12-13T09:40:32.967505image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
126.9126502 2
 
1.5%
126.9132355 2
 
1.5%
126.920996 2
 
1.5%
126.9134212 2
 
1.5%
126.8813447 2
 
1.5%
126.9201064 2
 
1.5%
126.789001 2
 
1.5%
126.9157414 2
 
1.5%
126.9207811 2
 
1.5%
126.9198134 2
 
1.5%
Other values (105) 117
85.4%
ValueCountFrequency (%)
126.789001 2
1.5%
126.7911698 1
0.7%
126.7919483 1
0.7%
126.7925784 1
0.7%
126.7941173 1
0.7%
126.7946738 1
0.7%
126.7949016 1
0.7%
126.7950331 1
0.7%
126.7951132 1
0.7%
126.7951398 1
0.7%
ValueCountFrequency (%)
126.9333433 1
0.7%
126.9326438 1
0.7%
126.9325026 1
0.7%
126.9322943 1
0.7%
126.9300844 1
0.7%
126.9294984 1
0.7%
126.9293305 1
0.7%
126.9292434 1
0.7%
126.9287047 1
0.7%
126.9283432 1
0.7%

관리번호
Text

Distinct116
Distinct (%)84.7%
Missing0
Missing (%)0.0%
Memory size1.2 KiB
2023-12-13T09:40:33.166384image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length25
Median length25
Mean length25
Min length25

Characters and Unicode

Total characters3425
Distinct characters14
Distinct categories2 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique95 ?
Unique (%)69.3%

Sample

1st rowPHMD120163600020084000015
2nd rowPHMD120203590019084000002
3rd rowPHMD120213590019084000003
4th rowPHMD120003600020084000001
5th rowPHMD120113590019084000008
ValueCountFrequency (%)
phmd120183620020084000020 2
 
1.5%
phmd120003600020084000001 2
 
1.5%
phmd120193590019084000010 2
 
1.5%
phmd120053590019084000002 2
 
1.5%
phmd120043590019084000007 2
 
1.5%
phmd120183590019084000004 2
 
1.5%
phmd120223590019084000003 2
 
1.5%
phmd120063600020084000006 2
 
1.5%
phmd120033590019084000001 2
 
1.5%
phmd120013590019084000008 2
 
1.5%
Other values (106) 117
85.4%
2023-12-13T09:40:33.464309image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 1354
39.5%
1 365
 
10.7%
2 235
 
6.9%
9 197
 
5.8%
3 181
 
5.3%
4 169
 
4.9%
8 165
 
4.8%
P 137
 
4.0%
H 137
 
4.0%
M 137
 
4.0%
Other values (4) 348
 
10.2%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 2877
84.0%
Uppercase Letter 548
 
16.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 1354
47.1%
1 365
 
12.7%
2 235
 
8.2%
9 197
 
6.8%
3 181
 
6.3%
4 169
 
5.9%
8 165
 
5.7%
5 92
 
3.2%
6 91
 
3.2%
7 28
 
1.0%
Uppercase Letter
ValueCountFrequency (%)
P 137
25.0%
H 137
25.0%
M 137
25.0%
D 137
25.0%

Most occurring scripts

ValueCountFrequency (%)
Common 2877
84.0%
Latin 548
 
16.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 1354
47.1%
1 365
 
12.7%
2 235
 
8.2%
9 197
 
6.8%
3 181
 
6.3%
4 169
 
5.9%
8 165
 
5.7%
5 92
 
3.2%
6 91
 
3.2%
7 28
 
1.0%
Latin
ValueCountFrequency (%)
P 137
25.0%
H 137
25.0%
M 137
25.0%
D 137
25.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 3425
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 1354
39.5%
1 365
 
10.7%
2 235
 
6.9%
9 197
 
5.8%
3 181
 
5.3%
4 169
 
4.9%
8 165
 
4.8%
P 137
 
4.0%
H 137
 
4.0%
M 137
 
4.0%
Other values (4) 348
 
10.2%

도로명전체주소
Text

Distinct116
Distinct (%)84.7%
Missing0
Missing (%)0.0%
Memory size1.2 KiB
2023-12-13T09:40:33.763270image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length54
Median length32
Mean length25.240876
Min length19

Characters and Unicode

Total characters3458
Distinct characters126
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

Unique95 ?
Unique (%)69.3%

Sample

1st row광주광역시 서구 상무대로 880, 1층 (쌍촌동)
2nd row광주광역시 동구 백서로 133 (금동)
3rd row광주광역시 동구 제봉로 57, 1층 (남동)
4th row광주광역시 서구 상무대로1080번길 1, 1층 (화정동)
5th row광주광역시 동구 제봉로 12 (학동)
ValueCountFrequency (%)
광주광역시 137
 
18.1%
동구 76
 
10.0%
1층 49
 
6.5%
서구 41
 
5.4%
학동 24
 
3.2%
제봉로 18
 
2.4%
백서로 15
 
2.0%
광산구 14
 
1.8%
치평동 14
 
1.8%
상무대로 13
 
1.7%
Other values (196) 358
47.2%
2023-12-13T09:40:34.157683image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
624
18.0%
광 291
 
8.4%
동 203
 
5.9%
1 169
 
4.9%
로 148
 
4.3%
구 142
 
4.1%
시 140
 
4.0%
주 138
 
4.0%
( 137
 
4.0%
) 137
 
4.0%
Other values (116) 1329
38.4%

Most occurring categories

ValueCountFrequency (%)
Other Letter 1953
56.5%
Space Separator 624
 
18.0%
Decimal Number 508
 
14.7%
Open Punctuation 137
 
4.0%
Close Punctuation 137
 
4.0%
Other Punctuation 65
 
1.9%
Dash Punctuation 20
 
0.6%
Uppercase Letter 8
 
0.2%
Lowercase Letter 6
 
0.2%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
광 291
14.9%
동 203
 
10.4%
로 148
 
7.6%
구 142
 
7.3%
시 140
 
7.2%
주 138
 
7.1%
역 137
 
7.0%
서 64
 
3.3%
층 53
 
2.7%
남 40
 
2.0%
Other values (87) 597
30.6%
Decimal Number
ValueCountFrequency (%)
1 169
33.3%
2 57
 
11.2%
4 50
 
9.8%
3 45
 
8.9%
0 37
 
7.3%
5 36
 
7.1%
7 36
 
7.1%
6 34
 
6.7%
8 24
 
4.7%
9 20
 
3.9%
Uppercase Letter
ValueCountFrequency (%)
W 1
12.5%
B 1
12.5%
S 1
12.5%
K 1
12.5%
C 1
12.5%
V 1
12.5%
I 1
12.5%
E 1
12.5%
Lowercase Letter
ValueCountFrequency (%)
n 1
16.7%
e 1
16.7%
t 1
16.7%
a 1
16.7%
r 1
16.7%
l 1
16.7%
Space Separator
ValueCountFrequency (%)
624
100.0%
Open Punctuation
ValueCountFrequency (%)
( 137
100.0%
Close Punctuation
ValueCountFrequency (%)
) 137
100.0%
Other Punctuation
ValueCountFrequency (%)
, 65
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 20
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 1953
56.5%
Common 1491
43.1%
Latin 14
 
0.4%

Most frequent character per script

Hangul
ValueCountFrequency (%)
광 291
14.9%
동 203
 
10.4%
로 148
 
7.6%
구 142
 
7.3%
시 140
 
7.2%
주 138
 
7.1%
역 137
 
7.0%
서 64
 
3.3%
층 53
 
2.7%
남 40
 
2.0%
Other values (87) 597
30.6%
Common
ValueCountFrequency (%)
624
41.9%
1 169
 
11.3%
( 137
 
9.2%
) 137
 
9.2%
, 65
 
4.4%
2 57
 
3.8%
4 50
 
3.4%
3 45
 
3.0%
0 37
 
2.5%
5 36
 
2.4%
Other values (5) 134
 
9.0%
Latin
ValueCountFrequency (%)
W 1
 
7.1%
n 1
 
7.1%
B 1
 
7.1%
S 1
 
7.1%
K 1
 
7.1%
e 1
 
7.1%
C 1
 
7.1%
t 1
 
7.1%
V 1
 
7.1%
I 1
 
7.1%
Other values (4) 4
28.6%

Most occurring blocks

ValueCountFrequency (%)
Hangul 1953
56.5%
ASCII 1505
43.5%

Most frequent character per block

ASCII
ValueCountFrequency (%)
624
41.5%
1 169
 
11.2%
( 137
 
9.1%
) 137
 
9.1%
, 65
 
4.3%
2 57
 
3.8%
4 50
 
3.3%
3 45
 
3.0%
0 37
 
2.5%
5 36
 
2.4%
Other values (19) 148
 
9.8%
Hangul
ValueCountFrequency (%)
광 291
14.9%
동 203
 
10.4%
로 148
 
7.6%
구 142
 
7.3%
시 140
 
7.2%
주 138
 
7.1%
역 137
 
7.0%
서 64
 
3.3%
층 53
 
2.7%
남 40
 
2.0%
Other values (87) 597
30.6%

영업상태구분코드
Categorical

CONSTANT 

Distinct1
Distinct (%)0.7%
Missing0
Missing (%)0.0%
Memory size1.2 KiB
1
137 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row1
2nd row1
3rd row1
4th row1
5th row1

Common Values

ValueCountFrequency (%)
1 137
100.0%

Length

2023-12-13T09:40:34.267192image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T09:40:34.336112image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
1 137
100.0%

영업상태명
Categorical

CONSTANT 

Distinct1
Distinct (%)0.7%
Missing0
Missing (%)0.0%
Memory size1.2 KiB
영업/정상
137 

Length

Max length5
Median length5
Mean length5
Min length5

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row영업/정상
2nd row영업/정상
3rd row영업/정상
4th row영업/정상
5th row영업/정상

Common Values

ValueCountFrequency (%)
영업/정상 137
100.0%

Length

2023-12-13T09:40:34.416558image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T09:40:34.487573image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
영업/정상 137
100.0%

데이터갱신일자
Categorical

HIGH CORRELATION 

Distinct41
Distinct (%)29.9%
Missing0
Missing (%)0.0%
Memory size1.2 KiB
2018-08-31 23:59:00.0
87 
2022-03-10 02:40:00.0
 
5
2019-07-03 02:21:00.0
 
2
2018-11-15 02:35:00.0
 
2
2019-03-24 02:20:00.0
 
2
Other values (36)
39 

Length

Max length21
Median length21
Mean length21
Min length21

Unique

Unique33 ?
Unique (%)24.1%

Sample

1st row2018-08-31 23:59:00.0
2nd row2022-03-10 02:40:00.0
3rd row2021-06-04 00:22:00.0
4th row2018-10-11 23:59:00.0
5th row2018-08-31 23:59:00.0

Common Values

ValueCountFrequency (%)
2018-08-31 23:59:00.0 87
63.5%
2022-03-10 02:40:00.0 5
 
3.6%
2019-07-03 02:21:00.0 2
 
1.5%
2018-11-15 02:35:00.0 2
 
1.5%
2019-03-24 02:20:00.0 2
 
1.5%
2019-01-16 02:40:00.0 2
 
1.5%
2020-11-20 02:40:00.0 2
 
1.5%
2018-10-11 23:59:00.0 2
 
1.5%
2022-02-26 02:40:00.0 1
 
0.7%
2021-06-04 00:22:00.0 1
 
0.7%
Other values (31) 31
 
22.6%

Length

2023-12-13T09:40:34.558553image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
23:59:00.0 89
32.5%
2018-08-31 87
31.8%
02:40:00.0 25
 
9.1%
00:22:00.0 6
 
2.2%
00:23:00.0 5
 
1.8%
2022-03-10 5
 
1.8%
02:20:00.0 5
 
1.8%
02:21:00.0 4
 
1.5%
02:35:00.0 3
 
1.1%
2019-01-16 3
 
1.1%
Other values (37) 42
15.3%

데이터갱신구분
Categorical

HIGH CORRELATION 

Distinct2
Distinct (%)1.5%
Missing0
Missing (%)0.0%
Memory size1.2 KiB
I
109 
U
28 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowI
2nd rowU
3rd rowI
4th rowU
5th rowI

Common Values

ValueCountFrequency (%)
I 109
79.6%
U 28
 
20.4%

Length

2023-12-13T09:40:34.665441image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T09:40:34.734894image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
i 109
79.6%
u 28
 
20.4%

Interactions

2023-12-13T09:40:30.755258image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T09:40:30.141280image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T09:40:30.546873image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T09:40:30.816638image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T09:40:30.410841image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T09:40:30.610249image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T09:40:30.886896image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T09:40:30.475061image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T09:40:30.685374image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-13T09:40:34.783393image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
문화노선도명거리위도경도데이터갱신일자데이터갱신구분
문화노선도명1.0000.3950.9020.9860.7570.241
거리0.3951.0000.4620.4000.5260.274
위도0.9020.4621.0000.6720.7000.301
경도0.9860.4000.6721.0000.7810.367
데이터갱신일자0.7570.5260.7000.7811.0001.000
데이터갱신구분0.2410.2740.3010.3671.0001.000
2023-12-13T09:40:34.860364image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
데이터갱신구분문화노선도명데이터갱신일자
데이터갱신구분1.0000.2010.843
문화노선도명0.2011.0000.270
데이터갱신일자0.8430.2701.000
2023-12-13T09:40:34.931976image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
거리위도경도문화노선도명데이터갱신일자데이터갱신구분
거리1.000-0.1610.0600.1580.1760.203
위도-0.1611.000-0.3490.6320.2900.292
경도0.060-0.3491.0000.8980.3720.269
문화노선도명0.1580.6320.8981.0000.2700.201
데이터갱신일자0.1760.2900.3720.2701.0000.843
데이터갱신구분0.2030.2920.2690.2010.8431.000

Missing values

2023-12-13T09:40:30.992098image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-13T09:40:31.130276image/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

문화노선도명거리인허가일자사업장명상세영업상태코드상세영업상태명위도경도관리번호도로명전체주소영업상태구분코드영업상태명데이터갱신일자데이터갱신구분
0운천53.7742016-09-08운천종로약국13영업중35.15018126.858236PHMD120163600020084000015광주광역시 서구 상무대로 880, 1층 (쌍촌동)1영업/정상2018-08-31 23:59:00.0I
1문화전당(구도청)474.282020-11-12송현약국13영업중35.142349126.919816PHMD120203590019084000002광주광역시 동구 백서로 133 (금동)1영업/정상2022-03-10 02:40:00.0U
2문화전당(구도청)334.6092021-06-02튼튼한 약국13영업중35.143658126.920765PHMD120213590019084000003광주광역시 동구 제봉로 57, 1층 (남동)1영업/정상2021-06-04 00:22:00.0I
3농성367.7512000-06-05광주보령약국13영업중35.152337126.880216PHMD120003600020084000001광주광역시 서구 상무대로1080번길 1, 1층 (화정동)1영업/정상2018-10-11 23:59:00.0U
4남광주206.9452011-04-04남광주 종로약국13영업중35.140157126.922556PHMD120113590019084000008광주광역시 동구 제봉로 12 (학동)1영업/정상2018-08-31 23:59:00.0I
5문화전당(구도청)354.2891974-03-28대동약국13영업중35.143948126.917908PHMD119743590019084000001광주광역시 동구 백서로125번길 25 (금동)1영업/정상2018-08-31 23:59:00.0I
6김대중컨벤션센터(마륵)274.5822020-05-07생기약국13영업중35.145174126.843279PHMD120203600020084000007광주광역시 서구 상무공원로 9, 에이스빌딩 2층 (치평동)1영업/정상2021-01-27 02:40:00.0U
7운천386.9452018-06-04힐링온누리약국13영업중35.151215126.854532PHMD120183600020084000005광주광역시 서구 운천로 213, 1층 5호 (치평동)1영업/정상2018-08-31 23:59:00.0I
8화정229.6382000-06-05광주보령약국13영업중35.152337126.880216PHMD120003600020084000001광주광역시 서구 상무대로1080번길 1, 1층 (화정동)1영업/정상2018-10-11 23:59:00.0U
9송정공원449.0532012-10-08우리일층약국13영업중35.141456126.795033PHMD120123630020084000014광주광역시 광산구 상무대로 258 (송정동)1영업/정상2021-12-15 02:40:00.0U
문화노선도명거리인허가일자사업장명상세영업상태코드상세영업상태명위도경도관리번호도로명전체주소영업상태구분코드영업상태명데이터갱신일자데이터갱신구분
127상무429.6622018-07-26메디팜서정약국13영업중35.150056126.851155PHMD120183600020084000006광주광역시 서구 시청로 17, 아난다 빌딩 지하1층 (치평동)1영업/정상2021-05-29 02:40:00.0U
128문화전당(구도청)223.8372018-06-11안세약국13영업중35.146656126.917589PHMD120183590019084000003광주광역시 동구 충장로안길 43-1 (충장로1가)1영업/정상2018-08-31 23:59:00.0I
129금남로4가471.3062002-11-02세종온누리약국13영업중35.153221126.918843PHMD120023590019084000008광주광역시 동구 중앙로 233 (대인동)1영업/정상2018-08-31 23:59:00.0I
130남광주497.1952019-07-01호남온누리약국13영업중35.142564126.919813PHMD120193590019084000010광주광역시 동구 백서로137번길 1, 1층 (금동)1영업/정상2019-07-03 02:21:00.0I
131금남로4가346.4132001-03-28광주백제약국13영업중35.153906126.915741PHMD120013590019084000008광주광역시 동구 제봉로 200 (대인동)1영업/정상2018-08-31 23:59:00.0I
132문화전당(구도청)432.3072018-12-31하나로누가약국13영업중35.1428126.920996PHMD120183590019084000004광주광역시 동구 백서로 145 (남동)1영업/정상2019-01-16 02:40:00.0U
133남광주495.4832005-06-17프린스 약국13영업중35.142776126.920781PHMD120053590019084000002광주광역시 동구 제봉로 48 (남동)1영업/정상2018-08-31 23:59:00.0I
134돌고개429.4472008-05-21광주경희한약국13영업중35.148365126.894213PHMD120083610019084000005광주광역시 남구 경열로76번길 33-2 (월산동)1영업/정상2018-08-31 23:59:00.0I
135농성126.8952021-08-10스마일약국13영업중35.154121126.88519PHMD120213600020084000006광주광역시 서구 상무대로 1129(농성동)1영업/정상2021-08-12 00:22:00.0I
136문화전당(구도청)438.2892003-08-18뉴욕약국13영업중35.142729126.920891PHMD120033590019084000006광주광역시 동구 백서로 143 (남동)1영업/정상2018-08-31 23:59:00.0I