Overview

Dataset statistics

Number of variables7
Number of observations159
Missing cells3
Missing cells (%)0.3%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory9.1 KiB
Average record size in memory58.8 B

Variable types

Categorical2
Text3
Numeric2

Dataset

Description부산광역시_노인교실현황_20230930
Author부산광역시
URLhttp://data.busan.go.kr/dataSet/detail.nm?contentId=10&publicdatapk=15065862

Alerts

데이터기준일자 has constant value ""Constant
경도 is highly overall correlated with 구군명High correlation
위도 is highly overall correlated with 구군명High correlation
구군명 is highly overall correlated with 경도 and 1 other fieldsHigh correlation
전화번호 has 3 (1.9%) missing valuesMissing
노인교실명 has unique valuesUnique
도로명주소 has unique valuesUnique

Reproduction

Analysis started2023-12-10 16:36:28.655673
Analysis finished2023-12-10 16:36:30.073686
Duration1.42 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

구군명
Categorical

HIGH CORRELATION 

Distinct16
Distinct (%)10.1%
Missing0
Missing (%)0.0%
Memory size1.4 KiB
북구
19 
해운대구
18 
부산진구
16 
금정구
14 
동래구
13 
Other values (11)
79 

Length

Max length4
Median length3
Mean length2.9433962
Min length2

Unique

Unique1 ?
Unique (%)0.6%

Sample

1st row중구
2nd row서구
3rd row서구
4th row서구
5th row서구

Common Values

ValueCountFrequency (%)
북구 19
11.9%
해운대구 18
11.3%
부산진구 16
10.1%
금정구 14
8.8%
동래구 13
8.2%
남구 13
8.2%
영도구 12
7.5%
연제구 11
6.9%
사상구 10
 
6.3%
사하구 8
 
5.0%
Other values (6) 25
15.7%

Length

2023-12-11T01:36:30.186728image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
북구 19
11.9%
해운대구 18
11.3%
부산진구 16
10.1%
금정구 14
8.8%
동래구 13
8.2%
남구 13
8.2%
영도구 12
7.5%
연제구 11
6.9%
사상구 10
 
6.3%
사하구 8
 
5.0%
Other values (6) 25
15.7%

노인교실명
Text

UNIQUE 

Distinct159
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size1.4 KiB
2023-12-11T01:36:30.485823image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length24
Median length20
Mean length9.8742138
Min length5

Characters and Unicode

Total characters1570
Distinct characters187
Distinct categories5 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique159 ?
Unique (%)100.0%

Sample

1st row대한노인회 부산중구지회 부설 노인대학
2nd row노인건강학교
3rd row소문노인대학
4th row한마음노인대학
5th row해강노인교실
ValueCountFrequency (%)
노인대학 17
 
7.0%
노인교실 13
 
5.3%
부설 8
 
3.3%
대한노인회 7
 
2.9%
부설노인대학 3
 
1.2%
부설노인교실 3
 
1.2%
늘푸른대학 3
 
1.2%
사하구종합사회복지관 1
 
0.4%
사하복지노인교실 1
 
0.4%
몰운대종합사회복지관 1
 
0.4%
Other values (186) 186
76.5%
2023-12-11T01:36:30.896826image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
대 134
 
8.5%
인 127
 
8.1%
노 126
 
8.0%
학 121
 
7.7%
84
 
5.4%
회 53
 
3.4%
교 53
 
3.4%
실 51
 
3.2%
지 45
 
2.9%
부 41
 
2.6%
Other values (177) 735
46.8%

Most occurring categories

ValueCountFrequency (%)
Other Letter 1474
93.9%
Space Separator 84
 
5.4%
Open Punctuation 5
 
0.3%
Close Punctuation 5
 
0.3%
Decimal Number 2
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
대 134
 
9.1%
인 127
 
8.6%
노 126
 
8.5%
학 121
 
8.2%
회 53
 
3.6%
교 53
 
3.6%
실 51
 
3.5%
지 45
 
3.1%
부 41
 
2.8%
사 37
 
2.5%
Other values (172) 686
46.5%
Decimal Number
ValueCountFrequency (%)
2 1
50.0%
4 1
50.0%
Space Separator
ValueCountFrequency (%)
84
100.0%
Open Punctuation
ValueCountFrequency (%)
( 5
100.0%
Close Punctuation
ValueCountFrequency (%)
) 5
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 1474
93.9%
Common 96
 
6.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
대 134
 
9.1%
인 127
 
8.6%
노 126
 
8.5%
학 121
 
8.2%
회 53
 
3.6%
교 53
 
3.6%
실 51
 
3.5%
지 45
 
3.1%
부 41
 
2.8%
사 37
 
2.5%
Other values (172) 686
46.5%
Common
ValueCountFrequency (%)
84
87.5%
( 5
 
5.2%
) 5
 
5.2%
2 1
 
1.0%
4 1
 
1.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 1474
93.9%
ASCII 96
 
6.1%

Most frequent character per block

Hangul
ValueCountFrequency (%)
대 134
 
9.1%
인 127
 
8.6%
노 126
 
8.5%
학 121
 
8.2%
회 53
 
3.6%
교 53
 
3.6%
실 51
 
3.5%
지 45
 
3.1%
부 41
 
2.8%
사 37
 
2.5%
Other values (172) 686
46.5%
ASCII
ValueCountFrequency (%)
84
87.5%
( 5
 
5.2%
) 5
 
5.2%
2 1
 
1.0%
4 1
 
1.0%

도로명주소
Text

UNIQUE 

Distinct159
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size1.4 KiB
2023-12-11T01:36:31.195220image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length35
Median length29
Mean length24.333333
Min length15

Characters and Unicode

Total characters3869
Distinct characters175
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

Unique159 ?
Unique (%)100.0%

Sample

1st row부산광역시 중구 대청로99번길 22
2nd row부산광역시 서구 대티로 129-5
3rd row부산광역시 서구 구덕로 186번길 9
4th row부산광역시 서구 망양로 193번길 104
5th row부산광역시 서구 해돋이로 67
ValueCountFrequency (%)
부산광역시 155
23.6%
북구 19
 
2.9%
해운대구 17
 
2.6%
부산진구 16
 
2.4%
금정구 14
 
2.1%
동래구 13
 
2.0%
남구 13
 
2.0%
영도구 12
 
1.8%
연제구 11
 
1.7%
사상구 10
 
1.5%
Other values (329) 376
57.3%
2023-12-11T01:36:31.641245image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
502
 
13.0%
산 184
 
4.8%
동 180
 
4.7%
부 177
 
4.6%
구 161
 
4.2%
광 158
 
4.1%
시 158
 
4.1%
역 155
 
4.0%
로 150
 
3.9%
( 144
 
3.7%
Other values (165) 1900
49.1%

Most occurring categories

ValueCountFrequency (%)
Other Letter 2449
63.3%
Decimal Number 606
 
15.7%
Space Separator 502
 
13.0%
Open Punctuation 144
 
3.7%
Close Punctuation 143
 
3.7%
Dash Punctuation 21
 
0.5%
Other Punctuation 4
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
산 184
 
7.5%
동 180
 
7.3%
부 177
 
7.2%
구 161
 
6.6%
광 158
 
6.5%
시 158
 
6.5%
역 155
 
6.3%
로 150
 
6.1%
길 95
 
3.9%
번 87
 
3.6%
Other values (150) 944
38.5%
Decimal Number
ValueCountFrequency (%)
1 133
21.9%
2 87
14.4%
3 64
10.6%
4 55
9.1%
5 54
8.9%
9 49
 
8.1%
0 48
 
7.9%
7 47
 
7.8%
6 38
 
6.3%
8 31
 
5.1%
Space Separator
ValueCountFrequency (%)
502
100.0%
Open Punctuation
ValueCountFrequency (%)
( 144
100.0%
Close Punctuation
ValueCountFrequency (%)
) 143
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 21
100.0%
Other Punctuation
ValueCountFrequency (%)
, 4
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 2449
63.3%
Common 1420
36.7%

Most frequent character per script

Hangul
ValueCountFrequency (%)
산 184
 
7.5%
동 180
 
7.3%
부 177
 
7.2%
구 161
 
6.6%
광 158
 
6.5%
시 158
 
6.5%
역 155
 
6.3%
로 150
 
6.1%
길 95
 
3.9%
번 87
 
3.6%
Other values (150) 944
38.5%
Common
ValueCountFrequency (%)
502
35.4%
( 144
 
10.1%
) 143
 
10.1%
1 133
 
9.4%
2 87
 
6.1%
3 64
 
4.5%
4 55
 
3.9%
5 54
 
3.8%
9 49
 
3.5%
0 48
 
3.4%
Other values (5) 141
 
9.9%

Most occurring blocks

ValueCountFrequency (%)
Hangul 2449
63.3%
ASCII 1420
36.7%

Most frequent character per block

ASCII
ValueCountFrequency (%)
502
35.4%
( 144
 
10.1%
) 143
 
10.1%
1 133
 
9.4%
2 87
 
6.1%
3 64
 
4.5%
4 55
 
3.9%
5 54
 
3.8%
9 49
 
3.5%
0 48
 
3.4%
Other values (5) 141
 
9.9%
Hangul
ValueCountFrequency (%)
산 184
 
7.5%
동 180
 
7.3%
부 177
 
7.2%
구 161
 
6.6%
광 158
 
6.5%
시 158
 
6.5%
역 155
 
6.3%
로 150
 
6.1%
길 95
 
3.9%
번 87
 
3.6%
Other values (150) 944
38.5%

전화번호
Text

MISSING 

Distinct155
Distinct (%)99.4%
Missing3
Missing (%)1.9%
Memory size1.4 KiB
2023-12-11T01:36:31.885363image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length12
Median length12
Mean length12
Min length12

Characters and Unicode

Total characters1872
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

Unique154 ?
Unique (%)98.7%

Sample

1st row051-247-1820
2nd row051-256-0734
3rd row051-256-2301
4th row051-253-1922
5th row051-248-6321
ValueCountFrequency (%)
051-582-2483 2
 
1.3%
051-264-9033 1
 
0.6%
051-581-4008 1
 
0.6%
051-247-1820 1
 
0.6%
051-543-5717 1
 
0.6%
051-202-8810 1
 
0.6%
051-265-9471 1
 
0.6%
051-205-0708 1
 
0.6%
051-293-2688 1
 
0.6%
051-206-9763 1
 
0.6%
Other values (145) 145
92.9%
2023-12-11T01:36:32.212733image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
- 312
16.7%
5 300
16.0%
1 292
15.6%
0 276
14.7%
3 121
 
6.5%
6 111
 
5.9%
2 109
 
5.8%
4 104
 
5.6%
7 95
 
5.1%
8 80
 
4.3%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 1560
83.3%
Dash Punctuation 312
 
16.7%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
5 300
19.2%
1 292
18.7%
0 276
17.7%
3 121
7.8%
6 111
 
7.1%
2 109
 
7.0%
4 104
 
6.7%
7 95
 
6.1%
8 80
 
5.1%
9 72
 
4.6%
Dash Punctuation
ValueCountFrequency (%)
- 312
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 1872
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
- 312
16.7%
5 300
16.0%
1 292
15.6%
0 276
14.7%
3 121
 
6.5%
6 111
 
5.9%
2 109
 
5.8%
4 104
 
5.6%
7 95
 
5.1%
8 80
 
4.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1872
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
- 312
16.7%
5 300
16.0%
1 292
15.6%
0 276
14.7%
3 121
 
6.5%
6 111
 
5.9%
2 109
 
5.8%
4 104
 
5.6%
7 95
 
5.1%
8 80
 
4.3%

경도
Real number (ℝ)

HIGH CORRELATION 

Distinct158
Distinct (%)99.4%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean129.06048
Minimum128.81701
Maximum129.21329
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.5 KiB
2023-12-11T01:36:32.371022image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum128.81701
5-th percentile128.97987
Q1129.01973
median129.06753
Q3129.09807
95-th percentile129.15535
Maximum129.21329
Range0.3962754
Interquartile range (IQR)0.07833785

Descriptive statistics

Standard deviation0.05951051
Coefficient of variation (CV)0.0004611056
Kurtosis1.8715725
Mean129.06048
Median Absolute Deviation (MAD)0.0366714
Skewness-0.6215707
Sum20520.616
Variance0.0035415008
MonotonicityNot monotonic
2023-12-11T01:36:32.542511image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
128.8762151 2
 
1.3%
129.031058 1
 
0.6%
128.9805856 1
 
0.6%
128.9600056 1
 
0.6%
128.985473 1
 
0.6%
129.0055561 1
 
0.6%
129.0077021 1
 
0.6%
128.9635537 1
 
0.6%
128.9934067 1
 
0.6%
128.9867137 1
 
0.6%
Other values (148) 148
93.1%
ValueCountFrequency (%)
128.817012 1
0.6%
128.8762151 2
1.3%
128.9028146 1
0.6%
128.9600056 1
0.6%
128.9635537 1
0.6%
128.9727618 1
0.6%
128.9734691 1
0.6%
128.9805856 1
0.6%
128.9832169 1
0.6%
128.9835963 1
0.6%
ValueCountFrequency (%)
129.2132874 1
0.6%
129.1862213 1
0.6%
129.1752248 1
0.6%
129.1731996 1
0.6%
129.1700013 1
0.6%
129.1645481 1
0.6%
129.1625165 1
0.6%
129.1585247 1
0.6%
129.1550004 1
0.6%
129.150092 1
0.6%

위도
Real number (ℝ)

HIGH CORRELATION 

Distinct158
Distinct (%)99.4%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean35.170642
Minimum35.029833
Maximum35.293396
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.5 KiB
2023-12-11T01:36:33.088394image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum35.029833
5-th percentile35.085344
Q135.13139
median35.173577
Q335.21148
95-th percentile35.253148
Maximum35.293396
Range0.26356274
Interquartile range (IQR)0.080089575

Descriptive statistics

Standard deviation0.052947348
Coefficient of variation (CV)0.0015054416
Kurtosis-0.49508978
Mean35.170642
Median Absolute Deviation (MAD)0.03880329
Skewness-0.20593276
Sum5592.1321
Variance0.0028034217
MonotonicityNot monotonic
2023-12-11T01:36:33.255375image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
35.1273856 2
 
1.3%
35.10453177 1
 
0.6%
35.08854547 1
 
0.6%
35.09639944 1
 
0.6%
35.06274344 1
 
0.6%
35.08851194 1
 
0.6%
35.09446142 1
 
0.6%
35.05122843 1
 
0.6%
35.09586857 1
 
0.6%
35.08563822 1
 
0.6%
Other values (148) 148
93.1%
ValueCountFrequency (%)
35.02983289 1
0.6%
35.05122843 1
0.6%
35.06274344 1
0.6%
35.07221265 1
0.6%
35.07600143 1
0.6%
35.08121547 1
0.6%
35.0833273 1
0.6%
35.08517116 1
0.6%
35.08536319 1
0.6%
35.08551797 1
0.6%
ValueCountFrequency (%)
35.29339563 1
0.6%
35.27917441 1
0.6%
35.27355883 1
0.6%
35.26773195 1
0.6%
35.2646556 1
0.6%
35.25988579 1
0.6%
35.2588917 1
0.6%
35.25636309 1
0.6%
35.25279093 1
0.6%
35.25168258 1
0.6%

데이터기준일자
Categorical

CONSTANT 

Distinct1
Distinct (%)0.6%
Missing0
Missing (%)0.0%
Memory size1.4 KiB
2023-09-30
159 

Length

Max length10
Median length10
Mean length10
Min length10

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row2023-09-30
2nd row2023-09-30
3rd row2023-09-30
4th row2023-09-30
5th row2023-09-30

Common Values

ValueCountFrequency (%)
2023-09-30 159
100.0%

Length

2023-12-11T01:36:33.399644image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T01:36:33.518839image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2023-09-30 159
100.0%

Interactions

2023-12-11T01:36:29.524408image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T01:36:29.156622image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T01:36:29.681347image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T01:36:29.385197image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-11T01:36:33.639566image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
구군명경도위도
구군명1.0000.8630.837
경도0.8631.0000.439
위도0.8370.4391.000
2023-12-11T01:36:33.876107image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
경도위도구군명
경도1.0000.3180.539
위도0.3181.0000.515
구군명0.5390.5151.000

Missing values

2023-12-11T01:36:29.849717image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-11T01:36:30.009280image/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

구군명노인교실명도로명주소전화번호경도위도데이터기준일자
0중구대한노인회 부산중구지회 부설 노인대학부산광역시 중구 대청로99번길 22051-247-1820129.03105835.1045322023-09-30
1서구노인건강학교부산광역시 서구 대티로 129-5051-256-0734129.00948335.1107532023-09-30
2서구소문노인대학부산광역시 서구 구덕로 186번길 9051-256-2301129.02024935.1014862023-09-30
3서구한마음노인대학부산광역시 서구 망양로 193번길 104051-253-1922129.02635935.1111792023-09-30
4서구해강노인교실부산광역시 서구 해돋이로 67051-248-6321129.02023235.0851712023-09-30
5동구범일노인대학(장기휴지)부산광역시 동구 범곡로 9(범일동)051-646-5979129.05573235.138872023-09-30
6동구인창실버예술대학부산광역시 동구 고관로 36(초량동)051-714-3872129.04305735.1225562023-09-30
7동구비둘기노인대학부산광역시 동구 성남로 37(좌천동)051-635-5734129.05408935.1298072023-09-30
8동구자성대노인복지관 노인교실부산광역시 동구 자성로 140번길 32(범일동051-632-7597129.06484135.1356442023-09-30
9동구동구종합사회복지관 오색빛깔실버대학부산광역시 동구 안창로57(범일동)051-633-3367129.0424335.1456282023-09-30
구군명노인교실명도로명주소전화번호경도위도데이터기준일자
149사상구사상구종합사회복지관 다솜노인대학부산광역시 사상구 백양대로 527(모라동)051-314-8948128.99477935.1554312023-09-30
150사상구백양복지관부설노인교실부산광역시 사상구 모라로192번길 20-23(모라동)051-305-4286129.00184335.1827572023-09-30
151사상구대한노인회사상구지회 부설 노인대학부산광역시 사상구 사상로319번길 6 (덕포동)051-304-2160128.98362735.1735772023-09-30
152사상구학장종합사회복지관 천수어르신교실부산광역시 사상구 학감대로49번길 28-70(학장동)051-311-4017128.98974635.1386522023-09-30
153사상구모라교회부설 모라상록교실부산광역시 사상구 모덕로95번길 101 (모라동)051-302-9191128.98748535.1857422023-09-30
154사상구감전교회부설 감전어르신 교실부산광역시 사상구 괘감로 77(괘법동)051-325-9341128.98321735.158692023-09-30
155사상구은혜로교회노인대학(구엄궁교회)부산광역시 사상구 엄궁로203번길 17 (엄궁동)051-313-4603128.97276235.1296412023-09-30
156사상구사상노인대학부산광역시 사상구 새벽로 172 (감전동)051-311-7587128.98359635.1564692023-09-30
157기장군철마노인대학부산광역시 기장군 철마면 개좌로 822051-721-9136129.15009235.2735592023-09-30
158기장군기장군지회 부설 노인대학부산광역시 기장군 기장읍 차성로333번길 4051-722-5610129.21328735.2474862023-09-30