Overview

Dataset statistics

Number of variables4
Number of observations7534
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory242.9 KiB
Average record size in memory33.0 B

Variable types

Numeric1
Categorical1
Text2

Dataset

Description경상남도 내에 있는 노인여가복지시설 중 경로당 현황에 대한 데이터로 시군명, 시설명, 주소에 대한 정보를 제공합니다.
Author경상남도
URLhttps://bigdata.gyeongnam.go.kr/index.gn?menuCd=DOM_000000114002001000&publicdatapk=15089076

Alerts

연번 is highly overall correlated with 시군명High correlation
시군명 is highly overall correlated with 연번High correlation
연번 has unique valuesUnique

Reproduction

Analysis started2023-12-11 00:34:59.384409
Analysis finished2023-12-11 00:35:00.300720
Duration0.92 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

연번
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct7534
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean3767.5
Minimum1
Maximum7534
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size66.3 KiB
2023-12-11T09:35:00.368834image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile377.65
Q11884.25
median3767.5
Q35650.75
95-th percentile7157.35
Maximum7534
Range7533
Interquartile range (IQR)3766.5

Descriptive statistics

Standard deviation2175.0228
Coefficient of variation (CV)0.57731196
Kurtosis-1.2
Mean3767.5
Median Absolute Deviation (MAD)1883.5
Skewness0
Sum28384345
Variance4730724.2
MonotonicityStrictly increasing
2023-12-11T09:35:00.519045image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1 1
 
< 0.1%
5020 1
 
< 0.1%
5032 1
 
< 0.1%
5031 1
 
< 0.1%
5030 1
 
< 0.1%
5029 1
 
< 0.1%
5028 1
 
< 0.1%
5027 1
 
< 0.1%
5026 1
 
< 0.1%
5025 1
 
< 0.1%
Other values (7524) 7524
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 (%)
7534 1
< 0.1%
7533 1
< 0.1%
7532 1
< 0.1%
7531 1
< 0.1%
7530 1
< 0.1%
7529 1
< 0.1%
7528 1
< 0.1%
7527 1
< 0.1%
7526 1
< 0.1%
7525 1
< 0.1%

시군명
Categorical

HIGH CORRELATION 

Distinct18
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size59.0 KiB
창원시
1027 
김해시
568 
진주시
554 
합천군
527 
밀양시
 
440
Other values (13)
4418 

Length

Max length3
Median length3
Mean length3
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
창원시 1027
13.6%
김해시 568
 
7.5%
진주시 554
 
7.4%
합천군 527
 
7.0%
밀양시 440
 
5.8%
거창군 438
 
5.8%
함양군 409
 
5.4%
창녕군 401
 
5.3%
하동군 382
 
5.1%
산청군 343
 
4.6%
Other values (8) 2445
32.5%

Length

2023-12-11T09:35:00.672670image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
창원시 1027
13.6%
김해시 568
 
7.5%
진주시 554
 
7.4%
합천군 527
 
7.0%
밀양시 440
 
5.8%
거창군 438
 
5.8%
함양군 409
 
5.4%
창녕군 401
 
5.3%
하동군 382
 
5.1%
산청군 343
 
4.6%
Other values (8) 2445
32.5%

시설명
Text

Distinct6031
Distinct (%)80.1%
Missing0
Missing (%)0.0%
Memory size59.0 KiB
2023-12-11T09:35:00.940742image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length20
Median length5
Mean length6.1813114
Min length2

Characters and Unicode

Total characters46570
Distinct characters514
Distinct categories10 ?
Distinct scripts3 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique5332 ?
Unique (%)70.8%

Sample

1st row가곡 경로당
2nd row고양 경로당
3rd row곡목 경로당
4th row금동 경로당
5th row금산 경로당
ValueCountFrequency (%)
경로당 52
 
0.7%
신촌경로당 39
 
0.5%
신기경로당 32
 
0.4%
중촌경로당 22
 
0.3%
상촌경로당 18
 
0.2%
중앙경로당 13
 
0.2%
동산경로당 12
 
0.2%
양지경로당 12
 
0.2%
송정경로당 12
 
0.2%
평촌경로당 12
 
0.2%
Other values (6022) 7395
97.1%
2023-12-11T09:35:01.339488image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
당 6715
 
14.4%
로 6566
 
14.1%
경 6540
 
14.0%
동 993
 
2.1%
( 772
 
1.7%
) 772
 
1.7%
아 713
 
1.5%
파 602
 
1.3%
트 587
 
1.3%
산 568
 
1.2%
Other values (504) 21742
46.7%

Most occurring categories

ValueCountFrequency (%)
Other Letter 43774
94.0%
Decimal Number 913
 
2.0%
Open Punctuation 772
 
1.7%
Close Punctuation 772
 
1.7%
Space Separator 170
 
0.4%
Uppercase Letter 111
 
0.2%
Other Punctuation 23
 
< 0.1%
Lowercase Letter 21
 
< 0.1%
Dash Punctuation 13
 
< 0.1%
Math Symbol 1
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
당 6715
 
15.3%
로 6566
 
15.0%
경 6540
 
14.9%
동 993
 
2.3%
아 713
 
1.6%
파 602
 
1.4%
트 587
 
1.3%
산 568
 
1.3%
대 524
 
1.2%
곡 483
 
1.1%
Other values (464) 19483
44.5%
Uppercase Letter
ValueCountFrequency (%)
A 46
41.4%
H 16
 
14.4%
L 15
 
13.5%
S 8
 
7.2%
T 6
 
5.4%
K 4
 
3.6%
P 4
 
3.6%
C 4
 
3.6%
X 1
 
0.9%
F 1
 
0.9%
Other values (6) 6
 
5.4%
Decimal Number
ValueCountFrequency (%)
2 323
35.4%
1 309
33.8%
3 125
 
13.7%
4 48
 
5.3%
5 41
 
4.5%
6 22
 
2.4%
7 18
 
2.0%
8 11
 
1.2%
0 9
 
1.0%
9 7
 
0.8%
Lowercase Letter
ValueCountFrequency (%)
e 17
81.0%
i 1
 
4.8%
t 1
 
4.8%
y 1
 
4.8%
h 1
 
4.8%
Other Punctuation
ValueCountFrequency (%)
. 11
47.8%
, 8
34.8%
@ 3
 
13.0%
· 1
 
4.3%
Open Punctuation
ValueCountFrequency (%)
( 772
100.0%
Close Punctuation
ValueCountFrequency (%)
) 772
100.0%
Space Separator
ValueCountFrequency (%)
170
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 13
100.0%
Math Symbol
ValueCountFrequency (%)
~ 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 43774
94.0%
Common 2664
 
5.7%
Latin 132
 
0.3%

Most frequent character per script

Hangul
ValueCountFrequency (%)
당 6715
 
15.3%
로 6566
 
15.0%
경 6540
 
14.9%
동 993
 
2.3%
아 713
 
1.6%
파 602
 
1.4%
트 587
 
1.3%
산 568
 
1.3%
대 524
 
1.2%
곡 483
 
1.1%
Other values (464) 19483
44.5%
Latin
ValueCountFrequency (%)
A 46
34.8%
e 17
 
12.9%
H 16
 
12.1%
L 15
 
11.4%
S 8
 
6.1%
T 6
 
4.5%
K 4
 
3.0%
P 4
 
3.0%
C 4
 
3.0%
X 1
 
0.8%
Other values (11) 11
 
8.3%
Common
ValueCountFrequency (%)
( 772
29.0%
) 772
29.0%
2 323
12.1%
1 309
11.6%
170
 
6.4%
3 125
 
4.7%
4 48
 
1.8%
5 41
 
1.5%
6 22
 
0.8%
7 18
 
0.7%
Other values (9) 64
 
2.4%

Most occurring blocks

ValueCountFrequency (%)
Hangul 43774
94.0%
ASCII 2795
 
6.0%
None 1
 
< 0.1%

Most frequent character per block

Hangul
ValueCountFrequency (%)
당 6715
 
15.3%
로 6566
 
15.0%
경 6540
 
14.9%
동 993
 
2.3%
아 713
 
1.6%
파 602
 
1.4%
트 587
 
1.3%
산 568
 
1.3%
대 524
 
1.2%
곡 483
 
1.1%
Other values (464) 19483
44.5%
ASCII
ValueCountFrequency (%)
( 772
27.6%
) 772
27.6%
2 323
11.6%
1 309
11.1%
170
 
6.1%
3 125
 
4.5%
4 48
 
1.7%
A 46
 
1.6%
5 41
 
1.5%
6 22
 
0.8%
Other values (29) 167
 
6.0%
None
ValueCountFrequency (%)
· 1
100.0%

주소
Text

Distinct7225
Distinct (%)95.9%
Missing0
Missing (%)0.0%
Memory size59.0 KiB
2023-12-11T09:35:01.644202image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length43
Median length35
Mean length16.843642
Min length5

Characters and Unicode

Total characters126900
Distinct characters501
Distinct categories10 ?
Distinct scripts3 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique6925 ?
Unique (%)91.9%

Sample

1st row의창구 동읍 신촌본포로442번길 26
2nd row의창구 동읍 백월로 540
3rd row의창구 동읍 동읍로 359번길 43
4th row의창구 동읍 동읍로 835번길 7
5th row의창구 동읍 동읍로 670번길 6
ValueCountFrequency (%)
경상남도 1714
 
6.2%
진주시 563
 
2.0%
김해시 491
 
1.8%
밀양시 440
 
1.6%
하동군 382
 
1.4%
산청군 343
 
1.2%
사천시 340
 
1.2%
고성군 330
 
1.2%
함안군 328
 
1.2%
양산시 320
 
1.2%
Other values (8669) 22491
81.1%
2023-12-11T09:35:02.066500image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
21648
 
17.1%
1 5971
 
4.7%
길 5710
 
4.5%
면 4578
 
3.6%
2 3986
 
3.1%
로 3546
 
2.8%
3 2890
 
2.3%
동 2738
 
2.2%
산 2541
 
2.0%
남 2459
 
1.9%
Other values (491) 70833
55.8%

Most occurring categories

ValueCountFrequency (%)
Other Letter 74403
58.6%
Decimal Number 25799
 
20.3%
Space Separator 21648
 
17.1%
Dash Punctuation 2094
 
1.7%
Close Punctuation 1213
 
1.0%
Open Punctuation 1212
 
1.0%
Other Punctuation 446
 
0.4%
Uppercase Letter 76
 
0.1%
Other Symbol 5
 
< 0.1%
Lowercase Letter 4
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
길 5710
 
7.7%
면 4578
 
6.2%
로 3546
 
4.8%
동 2738
 
3.7%
산 2541
 
3.4%
남 2459
 
3.3%
시 2436
 
3.3%
상 2215
 
3.0%
도 1965
 
2.6%
경 1816
 
2.4%
Other values (459) 44399
59.7%
Decimal Number
ValueCountFrequency (%)
1 5971
23.1%
2 3986
15.5%
3 2890
11.2%
4 2397
9.3%
5 2228
 
8.6%
6 1838
 
7.1%
7 1760
 
6.8%
8 1626
 
6.3%
9 1590
 
6.2%
0 1513
 
5.9%
Uppercase Letter
ValueCountFrequency (%)
A 51
67.1%
H 7
 
9.2%
L 7
 
9.2%
B 3
 
3.9%
S 2
 
2.6%
T 2
 
2.6%
P 1
 
1.3%
Q 1
 
1.3%
X 1
 
1.3%
K 1
 
1.3%
Other Punctuation
ValueCountFrequency (%)
, 410
91.9%
@ 29
 
6.5%
. 5
 
1.1%
/ 2
 
0.4%
Lowercase Letter
ValueCountFrequency (%)
e 2
50.0%
s 1
25.0%
d 1
25.0%
Space Separator
ValueCountFrequency (%)
21648
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 2094
100.0%
Close Punctuation
ValueCountFrequency (%)
) 1213
100.0%
Open Punctuation
ValueCountFrequency (%)
( 1212
100.0%
Other Symbol
ValueCountFrequency (%)
㉵ 5
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 74408
58.6%
Common 52412
41.3%
Latin 80
 
0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
길 5710
 
7.7%
면 4578
 
6.2%
로 3546
 
4.8%
동 2738
 
3.7%
산 2541
 
3.4%
남 2459
 
3.3%
시 2436
 
3.3%
상 2215
 
3.0%
도 1965
 
2.6%
경 1816
 
2.4%
Other values (460) 44404
59.7%
Common
ValueCountFrequency (%)
21648
41.3%
1 5971
 
11.4%
2 3986
 
7.6%
3 2890
 
5.5%
4 2397
 
4.6%
5 2228
 
4.3%
- 2094
 
4.0%
6 1838
 
3.5%
7 1760
 
3.4%
8 1626
 
3.1%
Other values (8) 5974
 
11.4%
Latin
ValueCountFrequency (%)
A 51
63.7%
H 7
 
8.8%
L 7
 
8.8%
B 3
 
3.8%
S 2
 
2.5%
e 2
 
2.5%
T 2
 
2.5%
P 1
 
1.2%
Q 1
 
1.2%
X 1
 
1.2%
Other values (3) 3
 
3.8%

Most occurring blocks

ValueCountFrequency (%)
Hangul 74403
58.6%
ASCII 52492
41.4%
None 5
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
21648
41.2%
1 5971
 
11.4%
2 3986
 
7.6%
3 2890
 
5.5%
4 2397
 
4.6%
5 2228
 
4.2%
- 2094
 
4.0%
6 1838
 
3.5%
7 1760
 
3.4%
8 1626
 
3.1%
Other values (21) 6054
 
11.5%
Hangul
ValueCountFrequency (%)
길 5710
 
7.7%
면 4578
 
6.2%
로 3546
 
4.8%
동 2738
 
3.7%
산 2541
 
3.4%
남 2459
 
3.3%
시 2436
 
3.3%
상 2215
 
3.0%
도 1965
 
2.6%
경 1816
 
2.4%
Other values (459) 44399
59.7%
None
ValueCountFrequency (%)
㉵ 5
100.0%

Interactions

2023-12-11T09:35:00.052967image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-11T09:35:02.143998image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
연번시군명
연번1.0000.975
시군명0.9751.000
2023-12-11T09:35:02.205434image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
연번시군명
연번1.0000.874
시군명0.8741.000

Missing values

2023-12-11T09:35:00.183030image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-11T09:35:00.265052image/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

연번시군명시설명주소
01창원시가곡 경로당의창구 동읍 신촌본포로442번길 26
12창원시고양 경로당의창구 동읍 백월로 540
23창원시곡목 경로당의창구 동읍 동읍로 359번길 43
34창원시금동 경로당의창구 동읍 동읍로 835번길 7
45창원시금산 경로당의창구 동읍 동읍로 670번길 6
56창원시기로회 경로당의창구 동읍 용잠로 45-5
67창원시남산경로당의창구 동읍 용남길 10번길 74
78창원시내단 경로당의창구 동읍 자여로 118번길 7
89창원시노옥 경로당의창구 동읍노연로 143번길 12
910창원시다호 경로당의창구 동읍 의창구 동읍로 267번길 35
연번시군명시설명주소
75247525합천군(용주)관음경로당용주면 방곡1길 88
75257526합천군(용주)방곡2구경로당용주면 방곡1길 12
75267527합천군(용주)신방경로당용주면 방곡길 7
75277528합천군(용주)월평1구경로당용주면 연촌길 9
75287529합천군(용주)월평2구경로당용주면 월평길 161
75297530합천군(용주)성산경로당용주면 성산3길 31
75307531합천군(용주)성산2구경로당용주면 성산길 18
75317532합천군(용주)손목경로당용주면 손목2길 13
75327533합천군(용주)손목1구할머니경로당용주면 황계폭포로 1395
75337534합천군(용주)손목2구경로당용주면 손목3길 74