Overview

Dataset statistics

Number of variables15
Number of observations306
Missing cells340
Missing cells (%)7.4%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory37.5 KiB
Average record size in memory125.4 B

Variable types

Numeric5
Categorical4
Text5
DateTime1

Dataset

Description대전광역시 서구 폐의약품 수거함 비치 현황에 대한 데이터입니다.- 서구청, 23개동행정복지센터, 서구보건소(지소포함)
Author대전광역시 서구
URLhttps://www.data.go.kr/data/15077806/fileData.do

Alerts

데이터기준일자 has constant value ""Constant
비고 is highly overall correlated with 순번 and 7 other fieldsHigh correlation
행정동명 is highly overall correlated with 행정동코드 and 5 other fieldsHigh correlation
법정동명 is highly overall correlated with 행정동코드 and 5 other fieldsHigh correlation
수거장소구분명 is highly overall correlated with 순번 and 1 other fieldsHigh correlation
순번 is highly overall correlated with 수거장소구분명 and 1 other fieldsHigh correlation
행정동코드 is highly overall correlated with 법정동코드 and 3 other fieldsHigh correlation
법정동코드 is highly overall correlated with 행정동코드 and 3 other fieldsHigh correlation
위도 is highly overall correlated with 행정동명 and 2 other fieldsHigh correlation
경도 is highly overall correlated with 행정동명 and 2 other fieldsHigh correlation
수거장소구분명 is highly imbalanced (53.1%)Imbalance
비고 is highly imbalanced (55.9%)Imbalance
개설자명 has 45 (14.7%) missing valuesMissing
전화번호 has 289 (94.4%) missing valuesMissing
순번 has unique valuesUnique

Reproduction

Analysis started2024-03-15 02:21:14.367291
Analysis finished2024-03-15 02:21:23.994664
Duration9.63 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

순번
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct306
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean153.5
Minimum1
Maximum306
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size2.8 KiB
2024-03-15T11:21:24.213449image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile16.25
Q177.25
median153.5
Q3229.75
95-th percentile290.75
Maximum306
Range305
Interquartile range (IQR)152.5

Descriptive statistics

Standard deviation88.478811
Coefficient of variation (CV)0.57640919
Kurtosis-1.2
Mean153.5
Median Absolute Deviation (MAD)76.5
Skewness0
Sum46971
Variance7828.5
MonotonicityStrictly increasing
2024-03-15T11:21:24.675817image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1 1
 
0.3%
203 1
 
0.3%
210 1
 
0.3%
209 1
 
0.3%
208 1
 
0.3%
207 1
 
0.3%
206 1
 
0.3%
205 1
 
0.3%
204 1
 
0.3%
202 1
 
0.3%
Other values (296) 296
96.7%
ValueCountFrequency (%)
1 1
0.3%
2 1
0.3%
3 1
0.3%
4 1
0.3%
5 1
0.3%
6 1
0.3%
7 1
0.3%
8 1
0.3%
9 1
0.3%
10 1
0.3%
ValueCountFrequency (%)
306 1
0.3%
305 1
0.3%
304 1
0.3%
303 1
0.3%
302 1
0.3%
301 1
0.3%
300 1
0.3%
299 1
0.3%
298 1
0.3%
297 1
0.3%

수거장소구분명
Categorical

HIGH CORRELATION  IMBALANCE 

Distinct3
Distinct (%)1.0%
Missing0
Missing (%)0.0%
Memory size2.5 KiB
약국
261 
행정복지센터,보건소
28 
복지관,성당,체육시설,기타
 
17

Length

Max length14
Median length2
Mean length3.3986928
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
약국 261
85.3%
행정복지센터,보건소 28
 
9.2%
복지관,성당,체육시설,기타 17
 
5.6%

Length

2024-03-15T11:21:25.123716image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-15T11:21:25.465336image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
약국 261
85.3%
행정복지센터,보건소 28
 
9.2%
복지관,성당,체육시설,기타 17
 
5.6%

수거장소명
Text

Distinct297
Distinct (%)97.1%
Missing0
Missing (%)0.0%
Memory size2.5 KiB
2024-03-15T11:21:26.368645image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length10
Median length9
Mean length5.624183
Min length3

Characters and Unicode

Total characters1721
Distinct characters232
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

Unique289 ?
Unique (%)94.4%

Sample

1st row건강약국
2nd row가장약국
3rd row가장태평양약국
4th row갈마드림약국
5th row갈마약국
ValueCountFrequency (%)
성당 7
 
2.2%
탄방우리약국 3
 
1.0%
누리약국 2
 
0.6%
더좋은약국 2
 
0.6%
메디팜우리약국 2
 
0.6%
연합약국 2
 
0.6%
새봄약국 2
 
0.6%
선사프라임약국 2
 
0.6%
탄방대한약국 2
 
0.6%
이화약국 1
 
0.3%
Other values (289) 289
92.0%
2024-03-15T11:21:27.759624image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
국 263
 
15.3%
약 262
 
15.2%
지 44
 
2.6%
정 40
 
2.3%
리 37
 
2.1%
동 36
 
2.1%
복 36
 
2.1%
행 28
 
1.6%
센 25
 
1.5%
터 24
 
1.4%
Other values (222) 926
53.8%

Most occurring categories

ValueCountFrequency (%)
Other Letter 1693
98.4%
Decimal Number 20
 
1.2%
Space Separator 8
 
0.5%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
국 263
 
15.5%
약 262
 
15.5%
지 44
 
2.6%
정 40
 
2.4%
리 37
 
2.2%
동 36
 
2.1%
복 36
 
2.1%
행 28
 
1.7%
센 25
 
1.5%
터 24
 
1.4%
Other values (216) 898
53.0%
Decimal Number
ValueCountFrequency (%)
2 6
30.0%
1 6
30.0%
3 4
20.0%
5 2
 
10.0%
6 2
 
10.0%
Space Separator
ValueCountFrequency (%)
8
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 1693
98.4%
Common 28
 
1.6%

Most frequent character per script

Hangul
ValueCountFrequency (%)
국 263
 
15.5%
약 262
 
15.5%
지 44
 
2.6%
정 40
 
2.4%
리 37
 
2.2%
동 36
 
2.1%
복 36
 
2.1%
행 28
 
1.7%
센 25
 
1.5%
터 24
 
1.4%
Other values (216) 898
53.0%
Common
ValueCountFrequency (%)
8
28.6%
2 6
21.4%
1 6
21.4%
3 4
14.3%
5 2
 
7.1%
6 2
 
7.1%

Most occurring blocks

ValueCountFrequency (%)
Hangul 1693
98.4%
ASCII 28
 
1.6%

Most frequent character per block

Hangul
ValueCountFrequency (%)
국 263
 
15.5%
약 262
 
15.5%
지 44
 
2.6%
정 40
 
2.4%
리 37
 
2.2%
동 36
 
2.1%
복 36
 
2.1%
행 28
 
1.7%
센 25
 
1.5%
터 24
 
1.4%
Other values (216) 898
53.0%
ASCII
ValueCountFrequency (%)
8
28.6%
2 6
21.4%
1 6
21.4%
3 4
14.3%
5 2
 
7.1%
6 2
 
7.1%

지번주소
Text

Distinct284
Distinct (%)93.1%
Missing1
Missing (%)0.3%
Memory size2.5 KiB
2024-03-15T11:21:29.289984image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length29
Median length28
Mean length17.508197
Min length14

Characters and Unicode

Total characters5340
Distinct characters109
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

Unique265 ?
Unique (%)86.9%

Sample

1st row대전광역시 서구 가수원동 765-6
2nd row대전광역시 서구 가장동 45-9 가장크리닉
3rd row대전광역시 서구 가장동 32-23 온누리크리닉
4th row대전광역시 서구 갈마동 393-13
5th row대전광역시 서구 갈마동 261-14
ValueCountFrequency (%)
대전광역시 305
24.6%
서구 305
24.6%
둔산동 80
 
6.4%
탄방동 38
 
3.1%
관저동 38
 
3.1%
도마동 27
 
2.2%
월평동 26
 
2.1%
갈마동 16
 
1.3%
괴정동 13
 
1.0%
정림동 10
 
0.8%
Other values (307) 384
30.9%
2024-03-15T11:21:31.197874image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
939
17.6%
대 306
 
5.7%
구 306
 
5.7%
전 306
 
5.7%
광 305
 
5.7%
역 305
 
5.7%
시 305
 
5.7%
서 305
 
5.7%
동 305
 
5.7%
1 280
 
5.2%
Other values (99) 1678
31.4%

Most occurring categories

ValueCountFrequency (%)
Other Letter 3145
58.9%
Decimal Number 1144
 
21.4%
Space Separator 939
 
17.6%
Dash Punctuation 112
 
2.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
대 306
9.7%
구 306
9.7%
전 306
9.7%
광 305
9.7%
역 305
9.7%
시 305
9.7%
서 305
9.7%
동 305
9.7%
산 83
 
2.6%
둔 81
 
2.6%
Other values (87) 538
17.1%
Decimal Number
ValueCountFrequency (%)
1 280
24.5%
2 116
10.1%
3 107
 
9.4%
4 104
 
9.1%
9 101
 
8.8%
8 97
 
8.5%
5 97
 
8.5%
0 94
 
8.2%
7 75
 
6.6%
6 73
 
6.4%
Space Separator
ValueCountFrequency (%)
939
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 112
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 3145
58.9%
Common 2195
41.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
대 306
9.7%
구 306
9.7%
전 306
9.7%
광 305
9.7%
역 305
9.7%
시 305
9.7%
서 305
9.7%
동 305
9.7%
산 83
 
2.6%
둔 81
 
2.6%
Other values (87) 538
17.1%
Common
ValueCountFrequency (%)
939
42.8%
1 280
 
12.8%
2 116
 
5.3%
- 112
 
5.1%
3 107
 
4.9%
4 104
 
4.7%
9 101
 
4.6%
8 97
 
4.4%
5 97
 
4.4%
0 94
 
4.3%
Other values (2) 148
 
6.7%

Most occurring blocks

ValueCountFrequency (%)
Hangul 3145
58.9%
ASCII 2195
41.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
939
42.8%
1 280
 
12.8%
2 116
 
5.3%
- 112
 
5.1%
3 107
 
4.9%
4 104
 
4.7%
9 101
 
4.6%
8 97
 
4.4%
5 97
 
4.4%
0 94
 
4.3%
Other values (2) 148
 
6.7%
Hangul
ValueCountFrequency (%)
대 306
9.7%
구 306
9.7%
전 306
9.7%
광 305
9.7%
역 305
9.7%
시 305
9.7%
서 305
9.7%
동 305
9.7%
산 83
 
2.6%
둔 81
 
2.6%
Other values (87) 538
17.1%

도로명주소
Text

Distinct284
Distinct (%)93.1%
Missing1
Missing (%)0.3%
Memory size2.5 KiB
2024-03-15T11:21:32.325634image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length30
Median length27
Mean length17.898361
Min length14

Characters and Unicode

Total characters5459
Distinct characters94
Distinct categories7 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique265 ?
Unique (%)86.9%

Sample

1st row대전광역시 서구 계백로 1166-12(가수원동)
2nd row대전광역시 서구 도산로 286(가장동)
3rd row대전광역시 서구 동서대로 1147(가장동)
4th row대전광역시 서구 신갈마로 110-1(갈마동)
5th row대전광역시 서구 계룡로 353(갈마동)
ValueCountFrequency (%)
대전광역시 305
24.9%
서구 305
24.9%
둔산로 20
 
1.6%
대덕대로 17
 
1.4%
도산로 17
 
1.4%
계룡로 16
 
1.3%
청사로 14
 
1.1%
문정로 13
 
1.1%
계백로 13
 
1.1%
관저로 11
 
0.9%
Other values (315) 492
40.2%
2024-03-15T11:21:33.691442image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
918
16.8%
대 364
 
6.7%
서 320
 
5.9%
구 312
 
5.7%
역 306
 
5.6%
전 305
 
5.6%
시 305
 
5.6%
광 305
 
5.6%
로 297
 
5.4%
1 195
 
3.6%
Other values (84) 1832
33.6%

Most occurring categories

ValueCountFrequency (%)
Other Letter 3472
63.6%
Space Separator 918
 
16.8%
Decimal Number 916
 
16.8%
Close Punctuation 67
 
1.2%
Open Punctuation 67
 
1.2%
Dash Punctuation 17
 
0.3%
Other Punctuation 2
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
대 364
10.5%
서 320
9.2%
구 312
 
9.0%
역 306
 
8.8%
전 305
 
8.8%
시 305
 
8.8%
광 305
 
8.8%
로 297
 
8.6%
동 89
 
2.6%
산 79
 
2.3%
Other values (69) 790
22.8%
Decimal Number
ValueCountFrequency (%)
1 195
21.3%
2 124
13.5%
5 97
10.6%
6 92
10.0%
3 91
9.9%
4 84
9.2%
8 65
 
7.1%
7 62
 
6.8%
0 55
 
6.0%
9 51
 
5.6%
Space Separator
ValueCountFrequency (%)
918
100.0%
Close Punctuation
ValueCountFrequency (%)
) 67
100.0%
Open Punctuation
ValueCountFrequency (%)
( 67
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 17
100.0%
Other Punctuation
ValueCountFrequency (%)
, 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 3472
63.6%
Common 1987
36.4%

Most frequent character per script

Hangul
ValueCountFrequency (%)
대 364
10.5%
서 320
9.2%
구 312
 
9.0%
역 306
 
8.8%
전 305
 
8.8%
시 305
 
8.8%
광 305
 
8.8%
로 297
 
8.6%
동 89
 
2.6%
산 79
 
2.3%
Other values (69) 790
22.8%
Common
ValueCountFrequency (%)
918
46.2%
1 195
 
9.8%
2 124
 
6.2%
5 97
 
4.9%
6 92
 
4.6%
3 91
 
4.6%
4 84
 
4.2%
) 67
 
3.4%
( 67
 
3.4%
8 65
 
3.3%
Other values (5) 187
 
9.4%

Most occurring blocks

ValueCountFrequency (%)
Hangul 3472
63.6%
ASCII 1987
36.4%

Most frequent character per block

ASCII
ValueCountFrequency (%)
918
46.2%
1 195
 
9.8%
2 124
 
6.2%
5 97
 
4.9%
6 92
 
4.6%
3 91
 
4.6%
4 84
 
4.2%
) 67
 
3.4%
( 67
 
3.4%
8 65
 
3.3%
Other values (5) 187
 
9.4%
Hangul
ValueCountFrequency (%)
대 364
10.5%
서 320
9.2%
구 312
 
9.0%
역 306
 
8.8%
전 305
 
8.8%
시 305
 
8.8%
광 305
 
8.8%
로 297
 
8.6%
동 89
 
2.6%
산 79
 
2.3%
Other values (69) 790
22.8%

행정동코드
Real number (ℝ)

HIGH CORRELATION 

Distinct24
Distinct (%)7.9%
Missing1
Missing (%)0.3%
Infinite0
Infinite (%)0.0%
Mean3.0170587 × 109
Minimum3.017051 × 109
Maximum3.017066 × 109
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size2.8 KiB
2024-03-15T11:21:33.980356image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum3.017051 × 109
5-th percentile3.017052 × 109
Q13.0170555 × 109
median3.0170587 × 109
Q33.017063 × 109
95-th percentile3.017065 × 109
Maximum3.017066 × 109
Range15000
Interquartile range (IQR)7500

Descriptive statistics

Standard deviation4064.4408
Coefficient of variation (CV)1.3471534 × 10-6
Kurtosis-1.010143
Mean3.0170587 × 109
Median Absolute Deviation (MAD)3200
Skewness0.081931334
Sum9.2020291 × 1011
Variance16519679
MonotonicityNot monotonic
2024-03-15T11:21:34.251329image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=24)
ValueCountFrequency (%)
3017064000 44
14.4%
3017055500 38
 
12.4%
3017059700 23
 
7.5%
3017063000 23
 
7.5%
3017059600 15
 
4.9%
3017053000 14
 
4.6%
3017056000 13
 
4.2%
3017052000 13
 
4.2%
3017066000 13
 
4.2%
3017058700 13
 
4.2%
Other values (14) 96
31.4%
ValueCountFrequency (%)
3017051000 5
 
1.6%
3017052000 13
 
4.2%
3017053000 14
 
4.6%
3017053500 10
 
3.3%
3017054000 7
 
2.3%
3017055000 8
 
2.6%
3017055500 38
12.4%
3017056000 13
 
4.2%
3017057000 5
 
1.6%
3017057500 8
 
2.6%
ValueCountFrequency (%)
3017066000 13
 
4.2%
3017065000 6
 
2.0%
3017064000 44
14.4%
3017063000 23
7.5%
3017060000 4
 
1.3%
3017059700 23
7.5%
3017059600 15
 
4.9%
3017059300 9
 
2.9%
3017059000 5
 
1.6%
3017058800 4
 
1.3%

행정동명
Categorical

HIGH CORRELATION 

Distinct25
Distinct (%)8.2%
Missing0
Missing (%)0.0%
Memory size2.5 KiB
둔산2동
44 
탄방동
38 
관저2동
23 
둔산1동
23 
관저1동
 
15
Other values (20)
163 

Length

Max length4
Median length4
Mean length3.5816993
Min length2

Unique

Unique1 ?
Unique (%)0.3%

Sample

1st row가수원동
2nd row가장동
3rd row가장동
4th row갈마1동
5th row갈마1동

Common Values

ValueCountFrequency (%)
둔산2동 44
14.4%
탄방동 38
 
12.4%
관저2동 23
 
7.5%
둔산1동 23
 
7.5%
관저1동 15
 
4.9%
도마2동 14
 
4.6%
괴정동 13
 
4.2%
도마1동 13
 
4.2%
둔산3동 13
 
4.2%
월평2동 13
 
4.2%
Other values (15) 97
31.7%

Length

2024-03-15T11:21:34.707214image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
둔산2동 44
14.4%
탄방동 38
 
12.4%
관저2동 23
 
7.5%
둔산1동 23
 
7.5%
관저1동 15
 
4.9%
도마2동 14
 
4.6%
괴정동 13
 
4.2%
도마1동 13
 
4.2%
둔산3동 13
 
4.2%
월평2동 13
 
4.2%
Other values (15) 97
31.7%

법정동코드
Real number (ℝ)

HIGH CORRELATION 

Distinct18
Distinct (%)5.9%
Missing1
Missing (%)0.3%
Infinite0
Infinite (%)0.0%
Mean3.017011 × 109
Minimum3.0170101 × 109
Maximum3.0170128 × 109
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size2.8 KiB
2024-03-15T11:21:35.090396image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum3.0170101 × 109
5-th percentile3.0170103 × 109
Q13.0170106 × 109
median3.0170112 × 109
Q33.0170113 × 109
95-th percentile3.0170116 × 109
Maximum3.0170128 × 109
Range2700
Interquartile range (IQR)700

Descriptive statistics

Standard deviation508.47689
Coefficient of variation (CV)1.6853664 × 10-7
Kurtosis1.2116212
Mean3.017011 × 109
Median Absolute Deviation (MAD)400
Skewness0.45469978
Sum9.2018837 × 1011
Variance258548.75
MonotonicityNot monotonic
2024-03-15T11:21:35.479892image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=18)
ValueCountFrequency (%)
3017011200 80
26.1%
3017010600 38
12.4%
3017011600 38
12.4%
3017010300 27
 
8.8%
3017011300 26
 
8.5%
3017011100 16
 
5.2%
3017010800 13
 
4.2%
3017010400 10
 
3.3%
3017011500 9
 
2.9%
3017011000 8
 
2.6%
Other values (8) 40
13.1%
ValueCountFrequency (%)
3017010100 5
 
1.6%
3017010200 7
 
2.3%
3017010300 27
8.8%
3017010400 10
 
3.3%
3017010500 8
 
2.6%
3017010600 38
12.4%
3017010800 13
 
4.2%
3017010900 5
 
1.6%
3017011000 8
 
2.6%
3017011100 16
5.2%
ValueCountFrequency (%)
3017012800 6
 
2.0%
3017012300 1
 
0.3%
3017011700 3
 
1.0%
3017011600 38
12.4%
3017011500 9
 
2.9%
3017011400 5
 
1.6%
3017011300 26
 
8.5%
3017011200 80
26.1%
3017011100 16
 
5.2%
3017011000 8
 
2.6%

법정동명
Categorical

HIGH CORRELATION 

Distinct19
Distinct (%)6.2%
Missing0
Missing (%)0.0%
Memory size2.5 KiB
둔산동
80 
관저동
38 
탄방동
38 
도마동
27 
월평동
26 
Other values (14)
97 

Length

Max length4
Median length3
Mean length2.9705882
Min length2

Unique

Unique2 ?
Unique (%)0.7%

Sample

1st row가수원동
2nd row가장동
3rd row가장동
4th row갈마동
5th row갈마동

Common Values

ValueCountFrequency (%)
둔산동 80
26.1%
관저동 38
12.4%
탄방동 38
12.4%
도마동 27
 
8.8%
월평동 26
 
8.5%
갈마동 16
 
5.2%
괴정동 13
 
4.2%
정림동 10
 
3.3%
도안동 9
 
2.9%
용문동 8
 
2.6%
Other values (9) 41
13.4%

Length

2024-03-15T11:21:35.878050image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
둔산동 80
26.1%
탄방동 38
12.4%
관저동 38
12.4%
도마동 27
 
8.8%
월평동 26
 
8.5%
갈마동 16
 
5.2%
괴정동 13
 
4.2%
정림동 10
 
3.3%
도안동 9
 
2.9%
내동 8
 
2.6%
Other values (9) 41
13.4%

개설자명
Text

MISSING 

Distinct53
Distinct (%)20.3%
Missing45
Missing (%)14.7%
Memory size2.5 KiB
2024-03-15T11:21:36.487842image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length3
Median length3
Mean length2.9731801
Min length2

Characters and Unicode

Total characters776
Distinct characters50
Distinct categories2 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique21 ?
Unique (%)8.0%

Sample

1st row윤**
2nd row이**
3rd row김**
4th row임**
5th row이**
ValueCountFrequency (%)
김 54
20.7%
이 33
 
12.6%
박 29
 
11.1%
정 15
 
5.7%
최 13
 
5.0%
임 8
 
3.1%
조 7
 
2.7%
윤 7
 
2.7%
강 6
 
2.3%
송 6
 
2.3%
Other values (39) 83
31.8%
2024-03-15T11:21:37.225733image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
* 515
66.4%
김 54
 
7.0%
이 33
 
4.3%
박 29
 
3.7%
정 15
 
1.9%
최 13
 
1.7%
임 8
 
1.0%
조 7
 
0.9%
윤 7
 
0.9%
강 6
 
0.8%
Other values (40) 89
 
11.5%

Most occurring categories

ValueCountFrequency (%)
Other Punctuation 515
66.4%
Other Letter 261
33.6%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
김 54
20.7%
이 33
 
12.6%
박 29
 
11.1%
정 15
 
5.7%
최 13
 
5.0%
임 8
 
3.1%
조 7
 
2.7%
윤 7
 
2.7%
강 6
 
2.3%
송 6
 
2.3%
Other values (39) 83
31.8%
Other Punctuation
ValueCountFrequency (%)
* 515
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 515
66.4%
Hangul 261
33.6%

Most frequent character per script

Hangul
ValueCountFrequency (%)
김 54
20.7%
이 33
 
12.6%
박 29
 
11.1%
정 15
 
5.7%
최 13
 
5.0%
임 8
 
3.1%
조 7
 
2.7%
윤 7
 
2.7%
강 6
 
2.3%
송 6
 
2.3%
Other values (39) 83
31.8%
Common
ValueCountFrequency (%)
* 515
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 515
66.4%
Hangul 261
33.6%

Most frequent character per block

ASCII
ValueCountFrequency (%)
* 515
100.0%
Hangul
ValueCountFrequency (%)
김 54
20.7%
이 33
 
12.6%
박 29
 
11.1%
정 15
 
5.7%
최 13
 
5.0%
임 8
 
3.1%
조 7
 
2.7%
윤 7
 
2.7%
강 6
 
2.3%
송 6
 
2.3%
Other values (39) 83
31.8%

전화번호
Text

MISSING 

Distinct17
Distinct (%)100.0%
Missing289
Missing (%)94.4%
Memory size2.5 KiB
2024-03-15T11:21:37.923242image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length12
Median length12
Mean length12
Min length12

Characters and Unicode

Total characters204
Distinct characters11
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique17 ?
Unique (%)100.0%

Sample

1st row042-488-6297
2nd row042-331-1155
3rd row042-537-0615
4th row042-528-0890
5th row042-482-2032
ValueCountFrequency (%)
042-488-6297 1
 
5.9%
042-485-1009 1
 
5.9%
042-526-4832 1
 
5.9%
042-472-2960 1
 
5.9%
042-489-9031 1
 
5.9%
042-535-7991 1
 
5.9%
042-526-4002 1
 
5.9%
042-483-6014 1
 
5.9%
042-537-4500 1
 
5.9%
042-331-1155 1
 
5.9%
Other values (7) 7
41.2%
2024-03-15T11:21:38.907431image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
- 34
16.7%
2 32
15.7%
0 31
15.2%
4 31
15.2%
5 19
9.3%
8 14
6.9%
3 10
 
4.9%
1 10
 
4.9%
9 9
 
4.4%
6 7
 
3.4%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 170
83.3%
Dash Punctuation 34
 
16.7%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
2 32
18.8%
0 31
18.2%
4 31
18.2%
5 19
11.2%
8 14
8.2%
3 10
 
5.9%
1 10
 
5.9%
9 9
 
5.3%
6 7
 
4.1%
7 7
 
4.1%
Dash Punctuation
ValueCountFrequency (%)
- 34
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 204
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
- 34
16.7%
2 32
15.7%
0 31
15.2%
4 31
15.2%
5 19
9.3%
8 14
6.9%
3 10
 
4.9%
1 10
 
4.9%
9 9
 
4.4%
6 7
 
3.4%

Most occurring blocks

ValueCountFrequency (%)
ASCII 204
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
- 34
16.7%
2 32
15.7%
0 31
15.2%
4 31
15.2%
5 19
9.3%
8 14
6.9%
3 10
 
4.9%
1 10
 
4.9%
9 9
 
4.4%
6 7
 
3.4%

비고
Categorical

HIGH CORRELATION  IMBALANCE 

Distinct2
Distinct (%)0.7%
Missing0
Missing (%)0.0%
Memory size2.5 KiB
<NA>
278 
민원실
28 

Length

Max length4
Median length4
Mean length3.9084967
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row<NA>
2nd row<NA>
3rd row<NA>
4th row<NA>
5th row<NA>

Common Values

ValueCountFrequency (%)
<NA> 278
90.8%
민원실 28
 
9.2%

Length

2024-03-15T11:21:39.473552image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-15T11:21:39.894708image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 278
90.8%
민원실 28
 
9.2%

위도
Real number (ℝ)

HIGH CORRELATION 

Distinct281
Distinct (%)92.1%
Missing1
Missing (%)0.3%
Infinite0
Infinite (%)0.0%
Mean36.334367
Minimum36.223119
Maximum36.368271
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size2.8 KiB
2024-03-15T11:21:40.271398image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum36.223119
5-th percentile36.298731
Q136.313228
median36.343617
Q336.351565
95-th percentile36.361528
Maximum36.368271
Range0.14515227
Interquartile range (IQR)0.03833708

Descriptive statistics

Standard deviation0.02330548
Coefficient of variation (CV)0.00064141698
Kurtosis1.2542069
Mean36.334367
Median Absolute Deviation (MAD)0.01183486
Skewness-1.0287703
Sum11081.982
Variance0.0005431454
MonotonicityNot monotonic
2024-03-15T11:21:40.782569image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
36.34361715 3
 
1.0%
36.3499618 3
 
1.0%
36.30656898 3
 
1.0%
36.35632919 2
 
0.7%
36.29932268 2
 
0.7%
36.3594322 2
 
0.7%
36.3529017 2
 
0.7%
36.31330796 2
 
0.7%
36.35382305 2
 
0.7%
36.30813094 2
 
0.7%
Other values (271) 282
92.2%
ValueCountFrequency (%)
36.22311888 1
0.3%
36.2546112 1
0.3%
36.25485872 1
0.3%
36.25580814 1
0.3%
36.29549706 1
0.3%
36.29638535 2
0.7%
36.29669992 1
0.3%
36.29670382 1
0.3%
36.29672772 1
0.3%
36.29673351 1
0.3%
ValueCountFrequency (%)
36.36827115 1
0.3%
36.36819907 1
0.3%
36.36757353 1
0.3%
36.36708996 1
0.3%
36.36708867 1
0.3%
36.36586013 1
0.3%
36.36382471 2
0.7%
36.36356466 1
0.3%
36.36272197 1
0.3%
36.36245573 1
0.3%

경도
Real number (ℝ)

HIGH CORRELATION 

Distinct281
Distinct (%)92.1%
Missing1
Missing (%)0.3%
Infinite0
Infinite (%)0.0%
Mean127.37358
Minimum127.2946
Maximum127.40077
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size2.8 KiB
2024-03-15T11:21:41.265973image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum127.2946
5-th percentile127.33642
Q1127.36688
median127.37899
Q3127.38674
95-th percentile127.39548
Maximum127.40077
Range0.1061748
Interquartile range (IQR)0.0198572

Descriptive statistics

Standard deviation0.018734899
Coefficient of variation (CV)0.00014708623
Kurtosis0.74660641
Mean127.37358
Median Absolute Deviation (MAD)0.0091037
Skewness-1.1526775
Sum38848.941
Variance0.00035099644
MonotonicityNot monotonic
2024-03-15T11:21:41.773534image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
127.3840781 3
 
1.0%
127.3872313 3
 
1.0%
127.3411443 3
 
1.0%
127.3872426 2
 
0.7%
127.3397725 2
 
0.7%
127.3891005 2
 
0.7%
127.3898621 2
 
0.7%
127.3795775 2
 
0.7%
127.3822529 2
 
0.7%
127.3698908 2
 
0.7%
Other values (271) 282
92.2%
ValueCountFrequency (%)
127.2945959 1
0.3%
127.3256229 1
0.3%
127.3259883 2
0.7%
127.3261351 1
0.3%
127.3315668 1
0.3%
127.3316448 1
0.3%
127.3325835 1
0.3%
127.3341592 1
0.3%
127.334392 1
0.3%
127.3352512 1
0.3%
ValueCountFrequency (%)
127.4007707 1
0.3%
127.4000229 1
0.3%
127.399637 1
0.3%
127.3990337 1
0.3%
127.3982541 1
0.3%
127.3982142 1
0.3%
127.397682 1
0.3%
127.3974346 2
0.7%
127.397289 1
0.3%
127.397197 1
0.3%

데이터기준일자
Date

CONSTANT 

Distinct1
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Memory size2.5 KiB
Minimum2024-01-17 00:00:00
Maximum2024-01-17 00:00:00
2024-03-15T11:21:42.306102image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T11:21:42.644949image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=1)

Interactions

2024-03-15T11:21:21.320720image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T11:21:15.785064image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T11:21:17.231582image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T11:21:18.396921image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T11:21:19.975353image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T11:21:21.479087image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T11:21:16.038149image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T11:21:17.474858image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T11:21:18.732484image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T11:21:20.244312image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T11:21:21.806404image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T11:21:16.382669image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T11:21:17.685781image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T11:21:19.125814image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T11:21:20.530457image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T11:21:22.117450image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T11:21:16.676906image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T11:21:17.861533image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T11:21:19.389693image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T11:21:20.789708image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T11:21:22.346338image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T11:21:16.963417image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T11:21:18.091414image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T11:21:19.694492image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T11:21:21.067236image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-03-15T11:21:42.885032image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
순번수거장소구분명행정동코드행정동명법정동코드법정동명개설자명전화번호위도경도
순번1.0000.7980.3740.5720.4340.5570.263NaN0.3360.434
수거장소구분명0.7981.0000.0970.3050.2140.329NaNNaN0.2550.289
행정동코드0.3740.0971.0001.0000.9260.9610.1581.0000.7180.826
행정동명0.5720.3051.0001.0000.9900.9990.1451.0000.9640.908
법정동코드0.4340.2140.9260.9901.0001.0000.4091.0000.9460.803
법정동명0.5570.3290.9610.9991.0001.0000.4491.0000.9580.947
개설자명0.263NaN0.1580.1450.4090.4491.000NaN0.3620.000
전화번호NaNNaN1.0001.0001.0001.000NaN1.0001.0001.000
위도0.3360.2550.7180.9640.9460.9580.3621.0001.0000.776
경도0.4340.2890.8260.9080.8030.9470.0001.0000.7761.000
2024-03-15T11:21:43.114039image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
비고행정동명법정동명수거장소구분명
비고1.0001.0001.0001.000
행정동명1.0001.0000.9570.142
법정동명1.0000.9571.0000.155
수거장소구분명1.0000.1420.1551.000
2024-03-15T11:21:43.609310image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
순번행정동코드법정동코드위도경도수거장소구분명행정동명법정동명비고
순번1.000-0.089-0.1320.1410.1670.6800.2380.2421.000
행정동코드-0.0891.0000.7570.442-0.0030.0000.9740.8191.000
법정동코드-0.1320.7571.0000.108-0.4780.1330.9130.9831.000
위도0.1410.4420.1081.0000.4660.1660.7120.8151.000
경도0.167-0.003-0.4780.4661.0000.1310.6290.6411.000
수거장소구분명0.6800.0000.1330.1660.1311.0000.1420.1551.000
행정동명0.2380.9740.9130.7120.6290.1421.0000.9571.000
법정동명0.2420.8190.9830.8150.6410.1550.9571.0001.000
비고1.0001.0001.0001.0001.0001.0001.0001.0001.000

Missing values

2024-03-15T11:21:22.725211image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-03-15T11:21:23.119189image/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.
2024-03-15T11:21:23.719652image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
The correlation heatmap measures nullity correlation: how strongly the presence or absence of one variable affects the presence of another.

Sample

순번수거장소구분명수거장소명지번주소도로명주소행정동코드행정동명법정동코드법정동명개설자명전화번호비고위도경도데이터기준일자
01약국건강약국대전광역시 서구 가수원동 765-6대전광역시 서구 계백로 1166-12(가수원동)3017059000가수원동3017011400가수원동윤**<NA><NA>36.304312127.3528782024-01-17
12약국가장약국대전광역시 서구 가장동 45-9 가장크리닉대전광역시 서구 도산로 286(가장동)3017057000가장동3017010900가장동이**<NA><NA>36.331973127.3856182024-01-17
23약국가장태평양약국대전광역시 서구 가장동 32-23 온누리크리닉대전광역시 서구 동서대로 1147(가장동)3017057000가장동3017010900가장동김**<NA><NA>36.328103127.3878312024-01-17
34약국갈마드림약국대전광역시 서구 갈마동 393-13대전광역시 서구 신갈마로 110-1(갈마동)3017058100갈마1동3017011100갈마동임**<NA><NA>36.343876127.3688342024-01-17
45약국갈마약국대전광역시 서구 갈마동 261-14대전광역시 서구 계룡로 353(갈마동)3017058100갈마1동3017011100갈마동이**<NA><NA>36.353715127.3684512024-01-17
56약국기쁨가득한약국대전광역시 서구 갈마동 394-16대전광역시 서구 갈마로 79(갈마동)3017058200갈마2동3017011100갈마동최**<NA><NA>36.345195127.3698172024-01-17
67약국다정약국대전광역시 서구 갈마동 343-45대전광역시 서구 갈마중로 11(갈마동)3017058200갈마2동3017011100갈마동박**<NA><NA>36.347711127.3705182024-01-17
78약국건양건강약국대전광역시 서구 관저동 1898대전광역시 서구 관저동로 164(관저동)3017059600관저1동3017011600관저동최**<NA><NA>36.306874127.3411472024-01-17
89약국건양사랑약국대전광역시 서구 관저동 1898대전광역시 서구 관저동로 164(관저동)3017059600관저1동3017011600관저동차**<NA><NA>36.306874127.3411472024-01-17
910약국건양정문약국대전광역시 서구 관저동 1899 건양프라자대전광역시 서구 관저동로 162(관저동)3017059600관저1동3017011600관저동강**<NA><NA>36.306569127.3411442024-01-17
순번수거장소구분명수거장소명지번주소도로명주소행정동코드행정동명법정동코드법정동명개설자명전화번호비고위도경도데이터기준일자
296297복지관,성당,체육시설,기타도솔다목적체육관대전광역시 서구 도마동 426대전광역시 서구 배재로197번길 413017053000도마2동3017010300도마동<NA>042-522-3820<NA>36.324894127.3681352024-01-17
297298복지관,성당,체육시설,기타갈마동 성당대전광역시 서구 갈마동 316-1대전광역시 서구 신갈마로195번길 133017058100갈마1동3017011100갈마동<NA>042-537-4500<NA>36.350828127.367432024-01-17
298299복지관,성당,체육시설,기타탄방동 성당대전광역시 서구 탄방동 786대전광역시 서구 탄방로 163017055500탄방동3017010600탄방동<NA>042-485-1009<NA>36.345226127.3897442024-01-17
299300복지관,성당,체육시설,기타월평동 성당대전광역시 서구 월평동 1041대전광역시 서구 월평중로13번길 533017058600월평1동3017011300월평동<NA>042-483-6014<NA>36.35549127.3606872024-01-17
300301복지관,성당,체육시설,기타내동 성당대전광역시 서구 내동 17-18대전광역시 서구 도솔로252번길 193017057500내동3017011000내동<NA>042-526-4002<NA>36.331908127.3789992024-01-17
301302복지관,성당,체육시설,기타괴정동 성당대전광역시 서구 괴정동 80-3대전광역시 서구 도솔로 3363017056000괴정동3017010800괴정동<NA>042-535-7991<NA>36.337456127.3846382024-01-17
302303복지관,성당,체육시설,기타만년동 성당대전광역시 서구 월평동 224대전광역시 서구 대덕대로 3333017058700월평2동3017011300월평동<NA>042-489-9031<NA>36.362722127.3789952024-01-17
303304복지관,성당,체육시설,기타둔산동 성당대전광역시 서구 둔산동 1383대전광역시 서구 둔산북로 1753017063000둔산1동3017011200둔산동<NA>042-472-2960<NA>36.356297127.392682024-01-17
304305복지관,성당,체육시설,기타서구노인지회대전광역시 서구 갈마동 295-27대전광역시 서구 계룡로342번길 283017058100갈마1동3017011100갈마동<NA>042-526-4832<NA>36.352676127.3661432024-01-17
305306복지관,성당,체육시설,기타지역교육사회협의회대전광역시 서구 갈마동 338-22대전광역시 서구 갈마로 343017058100갈마1동3017011100갈마동<NA>042-489-8177<NA>36.349501127.3690192024-01-17