Overview

Dataset statistics

Number of variables4
Number of observations274
Missing cells102
Missing cells (%)9.3%
Duplicate rows1
Duplicate rows (%)0.4%
Total size in memory9.0 KiB
Average record size in memory33.5 B

Variable types

Numeric1
Categorical1
Text2

Dataset

Description경상남도 창녕군 내 의류 수거함 현황입니다. 행복한가게사업단에서 운영 중인 자료로 읍면, 상세위치, 주소를 포함하고 있습니다.
Author경상남도 창녕군
URLhttps://bigdata.gyeongnam.go.kr/index.gn?menuCd=DOM_000000114002001000&publicdatapk=15127242

Alerts

Dataset has 1 (0.4%) duplicate rowsDuplicates
번호 is highly overall correlated with 읍면High correlation
읍면 is highly overall correlated with 번호High correlation
번호 has 34 (12.4%) missing valuesMissing
상세위치 has 34 (12.4%) missing valuesMissing
주소 has 34 (12.4%) missing valuesMissing

Reproduction

Analysis started2024-03-23 07:19:50.420866
Analysis finished2024-03-23 07:19:52.997489
Duration2.58 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

번호
Real number (ℝ)

HIGH CORRELATION  MISSING 

Distinct240
Distinct (%)100.0%
Missing34
Missing (%)12.4%
Infinite0
Infinite (%)0.0%
Mean120.5
Minimum1
Maximum240
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size2.5 KiB
2024-03-23T07:19:53.234346image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile12.95
Q160.75
median120.5
Q3180.25
95-th percentile228.05
Maximum240
Range239
Interquartile range (IQR)119.5

Descriptive statistics

Standard deviation69.42622
Coefficient of variation (CV)0.5761512
Kurtosis-1.2
Mean120.5
Median Absolute Deviation (MAD)60
Skewness0
Sum28920
Variance4820
MonotonicityStrictly increasing
2024-03-23T07:19:53.837656image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
122 1
 
0.4%
154 1
 
0.4%
155 1
 
0.4%
156 1
 
0.4%
157 1
 
0.4%
158 1
 
0.4%
159 1
 
0.4%
160 1
 
0.4%
161 1
 
0.4%
162 1
 
0.4%
Other values (230) 230
83.9%
(Missing) 34
 
12.4%
ValueCountFrequency (%)
1 1
0.4%
2 1
0.4%
3 1
0.4%
4 1
0.4%
5 1
0.4%
6 1
0.4%
7 1
0.4%
8 1
0.4%
9 1
0.4%
10 1
0.4%
ValueCountFrequency (%)
240 1
0.4%
239 1
0.4%
238 1
0.4%
237 1
0.4%
236 1
0.4%
235 1
0.4%
234 1
0.4%
233 1
0.4%
232 1
0.4%
231 1
0.4%

읍면
Categorical

HIGH CORRELATION 

Distinct15
Distinct (%)5.5%
Missing0
Missing (%)0.0%
Memory size2.3 KiB
창녕읍
75 
남지읍
47 
<NA>
34 
영산면
25 
고암면
16 
Other values (10)
77 

Length

Max length4
Median length3
Mean length3.1240876
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
창녕읍 75
27.4%
남지읍 47
17.2%
<NA> 34
12.4%
영산면 25
 
9.1%
고암면 16
 
5.8%
대합면 14
 
5.1%
유어면 11
 
4.0%
부곡면 11
 
4.0%
대지면 9
 
3.3%
계성면 8
 
2.9%
Other values (5) 24
 
8.8%

Length

2024-03-23T07:19:54.305381image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
창녕읍 75
27.4%
남지읍 47
17.2%
na 34
12.4%
영산면 25
 
9.1%
고암면 16
 
5.8%
대합면 14
 
5.1%
유어면 11
 
4.0%
부곡면 11
 
4.0%
대지면 9
 
3.3%
계성면 8
 
2.9%
Other values (5) 24
 
8.8%

상세위치
Text

MISSING 

Distinct239
Distinct (%)99.6%
Missing34
Missing (%)12.4%
Memory size2.3 KiB
2024-03-23T07:19:55.167968image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length26
Median length20
Mean length8.3958333
Min length3

Characters and Unicode

Total characters2015
Distinct characters288
Distinct categories6 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique238 ?
Unique (%)99.2%

Sample

1st row리라음악학원 건너편
2nd row건너편
3rd row슈퍼텍고등학교 오른쪽 골목 안쪽 삼거리
4th row낙영리 마을회관 건너편
5th row홍남빌라방향
ValueCountFrequency (%)
앞 31
 
6.0%
마을회관 30
 
5.8%
건너편 25
 
4.9%
인근 19
 
3.7%
입구 13
 
2.5%
주차장 10
 
1.9%
옆 10
 
1.9%
사거리 8
 
1.6%
경로당 8
 
1.6%
영산면 6
 
1.2%
Other values (299) 354
68.9%
2024-03-23T07:19:56.417529image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
275
 
13.6%
관 57
 
2.8%
회 57
 
2.8%
마 55
 
2.7%
을 53
 
2.6%
빌 45
 
2.2%
리 36
 
1.8%
라 35
 
1.7%
건 34
 
1.7%
앞 32
 
1.6%
Other values (278) 1336
66.3%

Most occurring categories

ValueCountFrequency (%)
Other Letter 1663
82.5%
Space Separator 275
 
13.6%
Decimal Number 64
 
3.2%
Dash Punctuation 6
 
0.3%
Other Punctuation 6
 
0.3%
Uppercase Letter 1
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
관 57
 
3.4%
회 57
 
3.4%
마 55
 
3.3%
을 53
 
3.2%
빌 45
 
2.7%
리 36
 
2.2%
라 35
 
2.1%
건 34
 
2.0%
앞 32
 
1.9%
편 31
 
1.9%
Other values (264) 1228
73.8%
Decimal Number
ValueCountFrequency (%)
1 24
37.5%
2 13
20.3%
0 6
 
9.4%
4 6
 
9.4%
3 6
 
9.4%
9 3
 
4.7%
8 2
 
3.1%
6 2
 
3.1%
7 1
 
1.6%
5 1
 
1.6%
Space Separator
ValueCountFrequency (%)
275
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 6
100.0%
Other Punctuation
ValueCountFrequency (%)
, 6
100.0%
Uppercase Letter
ValueCountFrequency (%)
B 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 1663
82.5%
Common 351
 
17.4%
Latin 1
 
< 0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
관 57
 
3.4%
회 57
 
3.4%
마 55
 
3.3%
을 53
 
3.2%
빌 45
 
2.7%
리 36
 
2.2%
라 35
 
2.1%
건 34
 
2.0%
앞 32
 
1.9%
편 31
 
1.9%
Other values (264) 1228
73.8%
Common
ValueCountFrequency (%)
275
78.3%
1 24
 
6.8%
2 13
 
3.7%
0 6
 
1.7%
4 6
 
1.7%
- 6
 
1.7%
, 6
 
1.7%
3 6
 
1.7%
9 3
 
0.9%
8 2
 
0.6%
Other values (3) 4
 
1.1%
Latin
ValueCountFrequency (%)
B 1
100.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 1663
82.5%
ASCII 352
 
17.5%

Most frequent character per block

ASCII
ValueCountFrequency (%)
275
78.1%
1 24
 
6.8%
2 13
 
3.7%
0 6
 
1.7%
4 6
 
1.7%
- 6
 
1.7%
, 6
 
1.7%
3 6
 
1.7%
9 3
 
0.9%
8 2
 
0.6%
Other values (4) 5
 
1.4%
Hangul
ValueCountFrequency (%)
관 57
 
3.4%
회 57
 
3.4%
마 55
 
3.3%
을 53
 
3.2%
빌 45
 
2.7%
리 36
 
2.2%
라 35
 
2.1%
건 34
 
2.0%
앞 32
 
1.9%
편 31
 
1.9%
Other values (264) 1228
73.8%

주소
Text

MISSING 

Distinct230
Distinct (%)95.8%
Missing34
Missing (%)12.4%
Memory size2.3 KiB
2024-03-23T07:19:57.532282image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length25
Median length24
Mean length20.575
Min length18

Characters and Unicode

Total characters4938
Distinct characters157
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

Unique221 ?
Unique (%)92.1%

Sample

1st row경상남도 창녕군 창녕읍 교상길 13
2nd row경상남도 창녕군 창녕읍 교하새길 6
3rd row경상남도 창녕군 창녕읍 낙영2길 3
4th row경상남도 창녕군 창녕읍 낙영3길 3
5th row경상남도 창녕군 창녕읍 낙영길 16-8
ValueCountFrequency (%)
경상남도 240
19.9%
창녕군 240
19.9%
창녕읍 75
 
6.2%
남지읍 47
 
3.9%
영산면 25
 
2.1%
고암면 16
 
1.3%
대합면 14
 
1.2%
부곡면 11
 
0.9%
유어면 11
 
0.9%
남지중앙1길 10
 
0.8%
Other values (318) 518
42.9%
2024-03-23T07:19:58.978318image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
970
19.6%
창 330
 
6.7%
녕 325
 
6.6%
남 319
 
6.5%
도 249
 
5.0%
상 248
 
5.0%
경 244
 
4.9%
군 240
 
4.9%
길 189
 
3.8%
1 185
 
3.7%
Other values (147) 1639
33.2%

Most occurring categories

ValueCountFrequency (%)
Other Letter 3292
66.7%
Space Separator 970
 
19.6%
Decimal Number 617
 
12.5%
Dash Punctuation 59
 
1.2%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
창 330
 
10.0%
녕 325
 
9.9%
남 319
 
9.7%
도 249
 
7.6%
상 248
 
7.5%
경 244
 
7.4%
군 240
 
7.3%
길 189
 
5.7%
읍 122
 
3.7%
면 118
 
3.6%
Other values (135) 908
27.6%
Decimal Number
ValueCountFrequency (%)
1 185
30.0%
2 90
14.6%
3 62
 
10.0%
5 50
 
8.1%
6 46
 
7.5%
4 41
 
6.6%
8 40
 
6.5%
9 36
 
5.8%
7 36
 
5.8%
0 31
 
5.0%
Space Separator
ValueCountFrequency (%)
970
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 59
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 3292
66.7%
Common 1646
33.3%

Most frequent character per script

Hangul
ValueCountFrequency (%)
창 330
 
10.0%
녕 325
 
9.9%
남 319
 
9.7%
도 249
 
7.6%
상 248
 
7.5%
경 244
 
7.4%
군 240
 
7.3%
길 189
 
5.7%
읍 122
 
3.7%
면 118
 
3.6%
Other values (135) 908
27.6%
Common
ValueCountFrequency (%)
970
58.9%
1 185
 
11.2%
2 90
 
5.5%
3 62
 
3.8%
- 59
 
3.6%
5 50
 
3.0%
6 46
 
2.8%
4 41
 
2.5%
8 40
 
2.4%
9 36
 
2.2%
Other values (2) 67
 
4.1%

Most occurring blocks

ValueCountFrequency (%)
Hangul 3292
66.7%
ASCII 1646
33.3%

Most frequent character per block

ASCII
ValueCountFrequency (%)
970
58.9%
1 185
 
11.2%
2 90
 
5.5%
3 62
 
3.8%
- 59
 
3.6%
5 50
 
3.0%
6 46
 
2.8%
4 41
 
2.5%
8 40
 
2.4%
9 36
 
2.2%
Other values (2) 67
 
4.1%
Hangul
ValueCountFrequency (%)
창 330
 
10.0%
녕 325
 
9.9%
남 319
 
9.7%
도 249
 
7.6%
상 248
 
7.5%
경 244
 
7.4%
군 240
 
7.3%
길 189
 
5.7%
읍 122
 
3.7%
면 118
 
3.6%
Other values (135) 908
27.6%

Interactions

2024-03-23T07:19:51.297626image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-03-23T07:19:59.326677image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
번호읍면
번호1.0000.939
읍면0.9391.000
2024-03-23T07:19:59.680247image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
번호읍면
번호1.0000.754
읍면0.7541.000

Missing values

2024-03-23T07:19:51.721145image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-03-23T07:19:52.216277image/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.
2024-03-23T07:19:52.752567image/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

번호읍면상세위치주소
01창녕읍리라음악학원 건너편경상남도 창녕군 창녕읍 교상길 13
12창녕읍건너편경상남도 창녕군 창녕읍 교하새길 6
23창녕읍슈퍼텍고등학교 오른쪽 골목 안쪽 삼거리경상남도 창녕군 창녕읍 낙영2길 3
34창녕읍낙영리 마을회관 건너편경상남도 창녕군 창녕읍 낙영3길 3
45창녕읍홍남빌라방향경상남도 창녕군 창녕읍 낙영길 16-8
56창녕읍목련아파트 건너편경상남도 창녕군 창녕읍 남창녕로 20
67창녕읍청호아파트경상남도 창녕군 창녕읍 남창녕로 47
78창녕읍금천아트빌경상남도 창녕군 창녕읍 당산1길 26-13
89창녕읍술정마을회관경상남도 창녕군 창녕읍 당산길 13-5
910창녕읍어울림빌라경상남도 창녕군 창녕읍 당산길 25
번호읍면상세위치주소
264<NA><NA><NA><NA>
265<NA><NA><NA><NA>
266<NA><NA><NA><NA>
267<NA><NA><NA><NA>
268<NA><NA><NA><NA>
269<NA><NA><NA><NA>
270<NA><NA><NA><NA>
271<NA><NA><NA><NA>
272<NA><NA><NA><NA>
273<NA><NA><NA><NA>

Duplicate rows

Most frequently occurring

번호읍면상세위치주소# duplicates
0<NA><NA><NA><NA>34