Overview

Dataset statistics

Number of variables5
Number of observations8129
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory333.5 KiB
Average record size in memory42.0 B

Variable types

Numeric2
Categorical1
Text2

Dataset

Description경상북도 노인여가 복지시설(경로당) 정보로써 시군별, 명칭, 이용 회원수, 시설 소재지를 파악한 자료 현황 입니다.
Author경상북도
URLhttps://www.data.go.kr/data/15052032/fileData.do

Alerts

연번 is highly overall correlated with 시군High correlation
시군 is highly overall correlated with 연번High correlation
연번 has unique valuesUnique

Reproduction

Analysis started2024-03-14 14:39:44.440202
Analysis finished2024-03-14 14:39:47.332910
Duration2.89 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

연번
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct8129
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean4065
Minimum1
Maximum8129
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size71.6 KiB
2024-03-14T23:39:47.479269image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile407.4
Q12033
median4065
Q36097
95-th percentile7722.6
Maximum8129
Range8128
Interquartile range (IQR)4064

Descriptive statistics

Standard deviation2346.7845
Coefficient of variation (CV)0.57731476
Kurtosis-1.2
Mean4065
Median Absolute Deviation (MAD)2032
Skewness0
Sum33044385
Variance5507397.5
MonotonicityStrictly increasing
2024-03-14T23:39:47.847066image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1 1
 
< 0.1%
5416 1
 
< 0.1%
5429 1
 
< 0.1%
5428 1
 
< 0.1%
5427 1
 
< 0.1%
5426 1
 
< 0.1%
5425 1
 
< 0.1%
5424 1
 
< 0.1%
5423 1
 
< 0.1%
5422 1
 
< 0.1%
Other values (8119) 8119
99.9%
ValueCountFrequency (%)
1 1
< 0.1%
2 1
< 0.1%
3 1
< 0.1%
4 1
< 0.1%
5 1
< 0.1%
6 1
< 0.1%
7 1
< 0.1%
8 1
< 0.1%
9 1
< 0.1%
10 1
< 0.1%
ValueCountFrequency (%)
8129 1
< 0.1%
8128 1
< 0.1%
8127 1
< 0.1%
8126 1
< 0.1%
8125 1
< 0.1%
8124 1
< 0.1%
8123 1
< 0.1%
8122 1
< 0.1%
8121 1
< 0.1%
8120 1
< 0.1%

시군
Categorical

HIGH CORRELATION 

Distinct23
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Memory size63.6 KiB
경주시
624 
포항시
621 
상주시
588 
안동시
531 
김천시
 
523
Other values (18)
5242 

Length

Max length3
Median length3
Mean length3
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
경주시 624
 
7.7%
포항시 621
 
7.6%
상주시 588
 
7.2%
안동시 531
 
6.5%
김천시 523
 
6.4%
의성군 485
 
6.0%
영천시 419
 
5.2%
구미시 413
 
5.1%
문경시 385
 
4.7%
경산시 381
 
4.7%
Other values (13) 3159
38.9%

Length

2024-03-14T23:39:48.088643image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
경주시 624
 
7.7%
포항시 621
 
7.6%
상주시 588
 
7.2%
안동시 531
 
6.5%
김천시 523
 
6.4%
의성군 485
 
6.0%
영천시 419
 
5.2%
구미시 413
 
5.1%
문경시 385
 
4.7%
경산시 381
 
4.7%
Other values (13) 3159
38.9%

경로당명
Text

Distinct7571
Distinct (%)93.1%
Missing0
Missing (%)0.0%
Memory size63.6 KiB
2024-03-14T23:39:48.967045image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length19
Median length17
Mean length6.9591586
Min length2

Characters and Unicode

Total characters56571
Distinct characters546
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

Unique7145 ?
Unique (%)87.9%

Sample

1st row구룡포1리경로당
2nd row구룡포2리경로당
3rd row중앙경로당
4th row구룡포4리경로당
5th row장안경로당(구룡포5리)
ValueCountFrequency (%)
경로당 844
 
9.1%
할머니 14
 
0.2%
할머니경로당 13
 
0.1%
분회 10
 
0.1%
중앙경로당 8
 
0.1%
현대아파트경로당 7
 
0.1%
신기경로당 6
 
0.1%
서부경로당 6
 
0.1%
금곡2리경로당 5
 
0.1%
대동경로당 5
 
0.1%
Other values (7607) 8344
90.1%
2024-03-14T23:39:50.095773image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
당 7162
 
12.7%
경 7129
 
12.6%
로 7093
 
12.5%
리 5323
 
9.4%
1 1862
 
3.3%
2 1847
 
3.3%
1341
 
2.4%
산 662
 
1.2%
동 597
 
1.1%
곡 548
 
1.0%
Other values (536) 23007
40.7%

Most occurring categories

ValueCountFrequency (%)
Other Letter 49888
88.2%
Decimal Number 4472
 
7.9%
Space Separator 1341
 
2.4%
Close Punctuation 383
 
0.7%
Open Punctuation 383
 
0.7%
Uppercase Letter 70
 
0.1%
Other Punctuation 21
 
< 0.1%
Lowercase Letter 11
 
< 0.1%
Dash Punctuation 2
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
당 7162
 
14.4%
경 7129
 
14.3%
로 7093
 
14.2%
리 5323
 
10.7%
산 662
 
1.3%
동 597
 
1.2%
곡 548
 
1.1%
신 459
 
0.9%
아 441
 
0.9%
천 422
 
0.8%
Other values (503) 20052
40.2%
Uppercase Letter
ValueCountFrequency (%)
A 18
25.7%
L 11
15.7%
H 10
14.3%
T 5
 
7.1%
K 5
 
7.1%
C 5
 
7.1%
W 4
 
5.7%
P 4
 
5.7%
S 4
 
5.7%
G 2
 
2.9%
Other values (2) 2
 
2.9%
Decimal Number
ValueCountFrequency (%)
1 1862
41.6%
2 1847
41.3%
3 474
 
10.6%
4 139
 
3.1%
5 50
 
1.1%
6 36
 
0.8%
7 24
 
0.5%
8 20
 
0.4%
9 11
 
0.2%
0 9
 
0.2%
Other Punctuation
ValueCountFrequency (%)
, 12
57.1%
. 6
28.6%
@ 2
 
9.5%
& 1
 
4.8%
Lowercase Letter
ValueCountFrequency (%)
e 9
81.8%
s 1
 
9.1%
k 1
 
9.1%
Space Separator
ValueCountFrequency (%)
1341
100.0%
Close Punctuation
ValueCountFrequency (%)
) 383
100.0%
Open Punctuation
ValueCountFrequency (%)
( 383
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 49888
88.2%
Common 6602
 
11.7%
Latin 81
 
0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
당 7162
 
14.4%
경 7129
 
14.3%
로 7093
 
14.2%
리 5323
 
10.7%
산 662
 
1.3%
동 597
 
1.2%
곡 548
 
1.1%
신 459
 
0.9%
아 441
 
0.9%
천 422
 
0.8%
Other values (503) 20052
40.2%
Common
ValueCountFrequency (%)
1 1862
28.2%
2 1847
28.0%
1341
20.3%
3 474
 
7.2%
) 383
 
5.8%
( 383
 
5.8%
4 139
 
2.1%
5 50
 
0.8%
6 36
 
0.5%
7 24
 
0.4%
Other values (8) 63
 
1.0%
Latin
ValueCountFrequency (%)
A 18
22.2%
L 11
13.6%
H 10
12.3%
e 9
11.1%
T 5
 
6.2%
K 5
 
6.2%
C 5
 
6.2%
W 4
 
4.9%
P 4
 
4.9%
S 4
 
4.9%
Other values (5) 6
 
7.4%

Most occurring blocks

ValueCountFrequency (%)
Hangul 49888
88.2%
ASCII 6683
 
11.8%

Most frequent character per block

Hangul
ValueCountFrequency (%)
당 7162
 
14.4%
경 7129
 
14.3%
로 7093
 
14.2%
리 5323
 
10.7%
산 662
 
1.3%
동 597
 
1.2%
곡 548
 
1.1%
신 459
 
0.9%
아 441
 
0.9%
천 422
 
0.8%
Other values (503) 20052
40.2%
ASCII
ValueCountFrequency (%)
1 1862
27.9%
2 1847
27.6%
1341
20.1%
3 474
 
7.1%
) 383
 
5.7%
( 383
 
5.7%
4 139
 
2.1%
5 50
 
0.7%
6 36
 
0.5%
7 24
 
0.4%
Other values (23) 144
 
2.2%

소재지
Text

Distinct7994
Distinct (%)98.3%
Missing0
Missing (%)0.0%
Memory size63.6 KiB
2024-03-14T23:39:51.755646image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length44
Median length38
Mean length15.726412
Min length4

Characters and Unicode

Total characters127840
Distinct characters548
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

Unique7867 ?
Unique (%)96.8%

Sample

1st row포항시 남구 구룡포읍 구룡포길 33-1
2nd row포항시 남구 구룡포읍 구룡포길 66-20
3rd row포항시 남구 구룡포읍 석문길 24-1
4th row포항시 남구 구룡포읍 석문길30번길 12
5th row포항시 남구 구룡포읍 구룡포길 117번길 13
ValueCountFrequency (%)
경주시 631
 
2.1%
포항시 629
 
2.1%
상주시 588
 
1.9%
안동시 538
 
1.8%
김천시 527
 
1.7%
의성군 485
 
1.6%
경상북도 454
 
1.5%
경북 439
 
1.4%
구미시 418
 
1.4%
영천시 410
 
1.3%
Other values (9397) 25490
83.3%
2024-03-14T23:39:53.913248image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
23339
 
18.3%
길 6590
 
5.2%
1 6185
 
4.8%
면 4682
 
3.7%
시 4301
 
3.4%
2 4156
 
3.3%
3 3135
 
2.5%
로 2524
 
2.0%
- 2505
 
2.0%
4 2445
 
1.9%
Other values (538) 67978
53.2%

Most occurring categories

ValueCountFrequency (%)
Other Letter 73307
57.3%
Decimal Number 26510
 
20.7%
Space Separator 23342
 
18.3%
Dash Punctuation 2505
 
2.0%
Close Punctuation 930
 
0.7%
Open Punctuation 925
 
0.7%
Other Punctuation 273
 
0.2%
Uppercase Letter 44
 
< 0.1%
Lowercase Letter 4
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
길 6590
 
9.0%
면 4682
 
6.4%
시 4301
 
5.9%
로 2524
 
3.4%
동 2369
 
3.2%
군 2133
 
2.9%
경 1844
 
2.5%
주 1833
 
2.5%
천 1824
 
2.5%
북 1650
 
2.3%
Other values (505) 43557
59.4%
Uppercase Letter
ValueCountFrequency (%)
A 22
50.0%
L 4
 
9.1%
H 4
 
9.1%
C 3
 
6.8%
P 3
 
6.8%
T 3
 
6.8%
U 1
 
2.3%
W 1
 
2.3%
B 1
 
2.3%
D 1
 
2.3%
Decimal Number
ValueCountFrequency (%)
1 6185
23.3%
2 4156
15.7%
3 3135
11.8%
4 2445
 
9.2%
5 2176
 
8.2%
6 2027
 
7.6%
7 1698
 
6.4%
8 1604
 
6.1%
0 1562
 
5.9%
9 1522
 
5.7%
Other Punctuation
ValueCountFrequency (%)
, 267
97.8%
/ 3
 
1.1%
. 2
 
0.7%
@ 1
 
0.4%
Lowercase Letter
ValueCountFrequency (%)
e 2
50.0%
k 1
25.0%
s 1
25.0%
Space Separator
ValueCountFrequency (%)
23339
> 99.9%
　 3
 
< 0.1%
Dash Punctuation
ValueCountFrequency (%)
- 2505
100.0%
Close Punctuation
ValueCountFrequency (%)
) 930
100.0%
Open Punctuation
ValueCountFrequency (%)
( 925
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 73307
57.3%
Common 54485
42.6%
Latin 48
 
< 0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
길 6590
 
9.0%
면 4682
 
6.4%
시 4301
 
5.9%
로 2524
 
3.4%
동 2369
 
3.2%
군 2133
 
2.9%
경 1844
 
2.5%
주 1833
 
2.5%
천 1824
 
2.5%
북 1650
 
2.3%
Other values (505) 43557
59.4%
Common
ValueCountFrequency (%)
23339
42.8%
1 6185
 
11.4%
2 4156
 
7.6%
3 3135
 
5.8%
- 2505
 
4.6%
4 2445
 
4.5%
5 2176
 
4.0%
6 2027
 
3.7%
7 1698
 
3.1%
8 1604
 
2.9%
Other values (9) 5215
 
9.6%
Latin
ValueCountFrequency (%)
A 22
45.8%
L 4
 
8.3%
H 4
 
8.3%
C 3
 
6.2%
P 3
 
6.2%
T 3
 
6.2%
e 2
 
4.2%
k 1
 
2.1%
s 1
 
2.1%
U 1
 
2.1%
Other values (4) 4
 
8.3%

Most occurring blocks

ValueCountFrequency (%)
Hangul 73307
57.3%
ASCII 54530
42.7%
None 3
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
23339
42.8%
1 6185
 
11.3%
2 4156
 
7.6%
3 3135
 
5.7%
- 2505
 
4.6%
4 2445
 
4.5%
5 2176
 
4.0%
6 2027
 
3.7%
7 1698
 
3.1%
8 1604
 
2.9%
Other values (22) 5260
 
9.6%
Hangul
ValueCountFrequency (%)
길 6590
 
9.0%
면 4682
 
6.4%
시 4301
 
5.9%
로 2524
 
3.4%
동 2369
 
3.2%
군 2133
 
2.9%
경 1844
 
2.5%
주 1833
 
2.5%
천 1824
 
2.5%
북 1650
 
2.3%
Other values (505) 43557
59.4%
None
ValueCountFrequency (%)
　 3
100.0%

이용회원수
Real number (ℝ)

Distinct160
Distinct (%)2.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean39.240251
Minimum0
Maximum392
Zeros18
Zeros (%)0.2%
Negative0
Negative (%)0.0%
Memory size71.6 KiB
2024-03-14T23:39:54.334176image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile15
Q124
median34
Q348
95-th percentile80
Maximum392
Range392
Interquartile range (IQR)24

Descriptive statistics

Standard deviation22.810639
Coefficient of variation (CV)0.58130717
Kurtosis21.003773
Mean39.240251
Median Absolute Deviation (MAD)11
Skewness2.8203974
Sum318984
Variance520.32527
MonotonicityNot monotonic
2024-03-14T23:39:54.799017image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
30 377
 
4.6%
20 348
 
4.3%
25 286
 
3.5%
40 264
 
3.2%
35 230
 
2.8%
21 210
 
2.6%
23 207
 
2.5%
24 204
 
2.5%
31 202
 
2.5%
27 195
 
2.4%
Other values (150) 5606
69.0%
ValueCountFrequency (%)
0 18
 
0.2%
5 1
 
< 0.1%
6 2
 
< 0.1%
7 2
 
< 0.1%
8 3
 
< 0.1%
9 7
 
0.1%
10 56
0.7%
11 51
0.6%
12 45
0.6%
13 79
1.0%
ValueCountFrequency (%)
392 1
< 0.1%
353 1
< 0.1%
350 1
< 0.1%
228 1
< 0.1%
210 1
< 0.1%
209 1
< 0.1%
198 1
< 0.1%
192 1
< 0.1%
190 1
< 0.1%
185 1
< 0.1%

Interactions

2024-03-14T23:39:46.434327image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T23:39:45.843754image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T23:39:46.721463image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T23:39:46.146686image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-03-14T23:39:55.079472image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
연번시군이용회원수
연번1.0000.9850.112
시군0.9851.0000.179
이용회원수0.1120.1791.000
2024-03-14T23:39:55.315050image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
연번이용회원수시군
연번1.000-0.0470.914
이용회원수-0.0471.0000.072
시군0.9140.0721.000

Missing values

2024-03-14T23:39:47.088434image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-03-14T23:39:47.257861image/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

연번시군경로당명소재지이용회원수
01포항시구룡포1리경로당포항시 남구 구룡포읍 구룡포길 33-171
12포항시구룡포2리경로당포항시 남구 구룡포읍 구룡포길 66-2026
23포항시중앙경로당포항시 남구 구룡포읍 석문길 24-144
34포항시구룡포4리경로당포항시 남구 구룡포읍 석문길30번길 1278
45포항시장안경로당(구룡포5리)포항시 남구 구룡포읍 구룡포길 117번길 1354
56포항시구룡포6리 남여 경로당포항시 남구 구룡포읍 용주로7번길 20-677
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