Overview

Dataset statistics

Number of variables5
Number of observations42
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory1.9 KiB
Average record size in memory45.1 B

Variable types

Numeric2
Text3

Dataset

Description전라북도요양보호사교육기관현황20174월현재
Author전라북도
URLhttps://www.bigdatahub.go.kr/opendata/dataSet/detail.nm?contentId=37&rlik=49451aebf056b486&serviceId=201877

Alerts

명 칭 has unique valuesUnique
도로명주소 has unique valuesUnique
전화번호 has unique valuesUnique

Reproduction

Analysis started2024-03-14 01:24:31.547013
Analysis finished2024-03-14 01:24:32.193087
Duration0.65 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

번호
Real number (ℝ)

Distinct19
Distinct (%)45.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean6.0714286
Minimum1
Maximum19
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size510.0 B
2024-03-14T10:24:32.246051image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q12
median4
Q38.75
95-th percentile16.95
Maximum19
Range18
Interquartile range (IQR)6.75

Descriptive statistics

Standard deviation5.4207949
Coefficient of variation (CV)0.89283681
Kurtosis-0.11472864
Mean6.0714286
Median Absolute Deviation (MAD)3
Skewness1.0171892
Sum255
Variance29.385017
MonotonicityNot monotonic
2024-03-14T10:24:32.610391image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=19)
ValueCountFrequency (%)
1 10
23.8%
2 5
11.9%
3 4
 
9.5%
4 3
 
7.1%
5 3
 
7.1%
6 2
 
4.8%
7 2
 
4.8%
8 2
 
4.8%
15 1
 
2.4%
19 1
 
2.4%
Other values (9) 9
21.4%
ValueCountFrequency (%)
1 10
23.8%
2 5
11.9%
3 4
 
9.5%
4 3
 
7.1%
5 3
 
7.1%
6 2
 
4.8%
7 2
 
4.8%
8 2
 
4.8%
9 1
 
2.4%
10 1
 
2.4%
ValueCountFrequency (%)
19 1
2.4%
18 1
2.4%
17 1
2.4%
16 1
2.4%
15 1
2.4%
14 1
2.4%
13 1
2.4%
12 1
2.4%
11 1
2.4%
10 1
2.4%

명 칭
Text

UNIQUE 

Distinct42
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size468.0 B
2024-03-14T10:24:32.796726image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length20
Median length17.5
Mean length14.047619
Min length10

Characters and Unicode

Total characters590
Distinct characters81
Distinct categories3 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique42 ?
Unique (%)100.0%

Sample

1st row전주성모간호요양보호사교육원
2nd row전주성신간호학원 부설 요양보호사교육원
3rd row온누리요양보호사교육원
4th row전주요양보호사교육원
5th row전주여성인력개발센터 요양보호사교육원
ValueCountFrequency (%)
요양보호사교육원 9
 
15.5%
부설 5
 
8.6%
평화요양보호사교육원 2
 
3.4%
종로요양보호사교육원 1
 
1.7%
고창성모요양보호사교육원 1
 
1.7%
군산여성인력개발센터 1
 
1.7%
익산간호요양보호사교육원 1
 
1.7%
이리간호교육원 1
 
1.7%
원광보건대학평생교육원요양보호사교육원 1
 
1.7%
익산성모요양보호사교육원 1
 
1.7%
Other values (35) 35
60.3%
2024-03-14T10:24:33.086397image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
호 60
 
10.2%
원 60
 
10.2%
교 45
 
7.6%
육 44
 
7.5%
보 43
 
7.3%
사 43
 
7.3%
요 42
 
7.1%
양 42
 
7.1%
간 17
 
2.9%
16
 
2.7%
Other values (71) 178
30.2%

Most occurring categories

ValueCountFrequency (%)
Other Letter 572
96.9%
Space Separator 16
 
2.7%
Uppercase Letter 2
 
0.3%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
호 60
 
10.5%
원 60
 
10.5%
교 45
 
7.9%
육 44
 
7.7%
보 43
 
7.5%
사 43
 
7.5%
요 42
 
7.3%
양 42
 
7.3%
간 17
 
3.0%
학 14
 
2.4%
Other values (68) 162
28.3%
Uppercase Letter
ValueCountFrequency (%)
J 1
50.0%
K 1
50.0%
Space Separator
ValueCountFrequency (%)
16
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 572
96.9%
Common 16
 
2.7%
Latin 2
 
0.3%

Most frequent character per script

Hangul
ValueCountFrequency (%)
호 60
 
10.5%
원 60
 
10.5%
교 45
 
7.9%
육 44
 
7.7%
보 43
 
7.5%
사 43
 
7.5%
요 42
 
7.3%
양 42
 
7.3%
간 17
 
3.0%
학 14
 
2.4%
Other values (68) 162
28.3%
Latin
ValueCountFrequency (%)
J 1
50.0%
K 1
50.0%
Common
ValueCountFrequency (%)
16
100.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 572
96.9%
ASCII 18
 
3.1%

Most frequent character per block

Hangul
ValueCountFrequency (%)
호 60
 
10.5%
원 60
 
10.5%
교 45
 
7.9%
육 44
 
7.7%
보 43
 
7.5%
사 43
 
7.5%
요 42
 
7.3%
양 42
 
7.3%
간 17
 
3.0%
학 14
 
2.4%
Other values (68) 162
28.3%
ASCII
ValueCountFrequency (%)
16
88.9%
J 1
 
5.6%
K 1
 
5.6%

도로명주소
Text

UNIQUE 

Distinct42
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size468.0 B
2024-03-14T10:24:33.329578image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length38
Median length23
Mean length21.02381
Min length15

Characters and Unicode

Total characters883
Distinct characters128
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

Unique42 ?
Unique (%)100.0%

Sample

1st row전주시 완산구 팔달로 229 (고사동)
2nd row전주시 완산구 팔달로 250 (서노송동)
3rd row전주시 완산구 팔달로 202-16 (3층)
4th row전주시 덕진구 떡전 4길 8 (금암동)
5th row전주시 완산구 장승배기로 213 BYC빌딩 2층
ValueCountFrequency (%)
전주시 19
 
9.5%
완산구 10
 
5.0%
덕진구 9
 
4.5%
익산시 8
 
4.0%
3층 8
 
4.0%
2층 5
 
2.5%
군산시 5
 
2.5%
익산대로 4
 
2.0%
무왕로 4
 
2.0%
4층 4
 
2.0%
Other values (107) 123
61.8%
2024-03-14T10:24:33.666670image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
157
 
17.8%
로 41
 
4.6%
시 38
 
4.3%
1 35
 
4.0%
동 33
 
3.7%
( 32
 
3.6%
) 32
 
3.6%
2 31
 
3.5%
산 30
 
3.4%
층 21
 
2.4%
Other values (118) 433
49.0%

Most occurring categories

ValueCountFrequency (%)
Other Letter 471
53.3%
Space Separator 157
 
17.8%
Decimal Number 156
 
17.7%
Open Punctuation 32
 
3.6%
Close Punctuation 32
 
3.6%
Other Punctuation 15
 
1.7%
Lowercase Letter 10
 
1.1%
Dash Punctuation 7
 
0.8%
Uppercase Letter 3
 
0.3%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
로 41
 
8.7%
시 38
 
8.1%
동 33
 
7.0%
산 30
 
6.4%
층 21
 
4.5%
전 21
 
4.5%
주 21
 
4.5%
구 19
 
4.0%
익 12
 
2.5%
가 11
 
2.3%
Other values (92) 224
47.6%
Decimal Number
ValueCountFrequency (%)
1 35
22.4%
2 31
19.9%
3 19
12.2%
4 19
12.2%
5 13
 
8.3%
7 9
 
5.8%
6 8
 
5.1%
8 8
 
5.1%
0 7
 
4.5%
9 7
 
4.5%
Lowercase Letter
ValueCountFrequency (%)
k 3
30.0%
u 3
30.0%
r 1
 
10.0%
w 1
 
10.0%
a 1
 
10.0%
c 1
 
10.0%
Other Punctuation
ValueCountFrequency (%)
, 12
80.0%
. 2
 
13.3%
@ 1
 
6.7%
Uppercase Letter
ValueCountFrequency (%)
B 1
33.3%
Y 1
33.3%
C 1
33.3%
Space Separator
ValueCountFrequency (%)
157
100.0%
Open Punctuation
ValueCountFrequency (%)
( 32
100.0%
Close Punctuation
ValueCountFrequency (%)
) 32
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 7
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 471
53.3%
Common 399
45.2%
Latin 13
 
1.5%

Most frequent character per script

Hangul
ValueCountFrequency (%)
로 41
 
8.7%
시 38
 
8.1%
동 33
 
7.0%
산 30
 
6.4%
층 21
 
4.5%
전 21
 
4.5%
주 21
 
4.5%
구 19
 
4.0%
익 12
 
2.5%
가 11
 
2.3%
Other values (92) 224
47.6%
Common
ValueCountFrequency (%)
157
39.3%
1 35
 
8.8%
( 32
 
8.0%
) 32
 
8.0%
2 31
 
7.8%
3 19
 
4.8%
4 19
 
4.8%
5 13
 
3.3%
, 12
 
3.0%
7 9
 
2.3%
Other values (7) 40
 
10.0%
Latin
ValueCountFrequency (%)
k 3
23.1%
u 3
23.1%
r 1
 
7.7%
w 1
 
7.7%
a 1
 
7.7%
c 1
 
7.7%
B 1
 
7.7%
Y 1
 
7.7%
C 1
 
7.7%

Most occurring blocks

ValueCountFrequency (%)
Hangul 471
53.3%
ASCII 412
46.7%

Most frequent character per block

ASCII
ValueCountFrequency (%)
157
38.1%
1 35
 
8.5%
( 32
 
7.8%
) 32
 
7.8%
2 31
 
7.5%
3 19
 
4.6%
4 19
 
4.6%
5 13
 
3.2%
, 12
 
2.9%
7 9
 
2.2%
Other values (16) 53
 
12.9%
Hangul
ValueCountFrequency (%)
로 41
 
8.7%
시 38
 
8.1%
동 33
 
7.0%
산 30
 
6.4%
층 21
 
4.5%
전 21
 
4.5%
주 21
 
4.5%
구 19
 
4.0%
익 12
 
2.5%
가 11
 
2.3%
Other values (92) 224
47.6%

전화번호
Text

UNIQUE 

Distinct42
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size468.0 B
2024-03-14T10:24:33.846202image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length17
Median length8
Mean length8.3809524
Min length8

Characters and Unicode

Total characters352
Distinct characters13
Distinct categories4 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique42 ?
Unique (%)100.0%

Sample

1st row283-6662~5
2nd row285-1999 285-1990
3rd row231-4554
4th row284-1199
5th row232-2346
ValueCountFrequency (%)
283-6662~5 1
 
2.3%
538-3663 1
 
2.3%
468-0055 1
 
2.3%
858-9840 1
 
2.3%
851-2411 1
 
2.3%
840-1492 1
 
2.3%
853-8331 1
 
2.3%
852-0129 1
 
2.3%
835-7698 1
 
2.3%
833-4477 1
 
2.3%
Other values (33) 33
76.7%
2024-03-14T10:24:34.114859image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
2 56
15.9%
- 44
12.5%
3 35
9.9%
4 32
9.1%
8 30
8.5%
5 30
8.5%
1 30
8.5%
6 25
7.1%
7 23
6.5%
0 23
6.5%
Other values (3) 24
6.8%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 306
86.9%
Dash Punctuation 44
 
12.5%
Math Symbol 1
 
0.3%
Space Separator 1
 
0.3%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
2 56
18.3%
3 35
11.4%
4 32
10.5%
8 30
9.8%
5 30
9.8%
1 30
9.8%
6 25
8.2%
7 23
7.5%
0 23
7.5%
9 22
 
7.2%
Dash Punctuation
ValueCountFrequency (%)
- 44
100.0%
Math Symbol
ValueCountFrequency (%)
~ 1
100.0%
Space Separator
ValueCountFrequency (%)
1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 352
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
2 56
15.9%
- 44
12.5%
3 35
9.9%
4 32
9.1%
8 30
8.5%
5 30
8.5%
1 30
8.5%
6 25
7.1%
7 23
6.5%
0 23
6.5%
Other values (3) 24
6.8%

Most occurring blocks

ValueCountFrequency (%)
ASCII 352
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
2 56
15.9%
- 44
12.5%
3 35
9.9%
4 32
9.1%
8 30
8.5%
5 30
8.5%
1 30
8.5%
6 25
7.1%
7 23
6.5%
0 23
6.5%
Other values (3) 24
6.8%

우편번호
Real number (ℝ)

Distinct37
Distinct (%)88.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean55016.524
Minimum54085
Maximum56436
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size510.0 B
2024-03-14T10:24:34.271287image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum54085
5-th percentile54131.25
Q154649.25
median54960.5
Q355118
95-th percentile56180.2
Maximum56436
Range2351
Interquartile range (IQR)468.75

Descriptive statistics

Standard deviation622.70591
Coefficient of variation (CV)0.011318525
Kurtosis0.059154382
Mean55016.524
Median Absolute Deviation (MAD)298.5
Skewness0.7608858
Sum2310694
Variance387762.65
MonotonicityNot monotonic
2024-03-14T10:24:34.392940image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=37)
ValueCountFrequency (%)
55039 2
 
4.8%
54662 2
 
4.8%
54545 2
 
4.8%
54893 2
 
4.8%
56165 2
 
4.8%
56181 1
 
2.4%
54674 1
 
2.4%
54536 1
 
2.4%
54645 1
 
2.4%
54554 1
 
2.4%
Other values (27) 27
64.3%
ValueCountFrequency (%)
54085 1
2.4%
54130 1
2.4%
54131 1
2.4%
54136 1
2.4%
54143 1
2.4%
54392 1
2.4%
54536 1
2.4%
54545 2
4.8%
54554 1
2.4%
54645 1
2.4%
ValueCountFrequency (%)
56436 1
2.4%
56315 1
2.4%
56181 1
2.4%
56165 2
4.8%
56038 1
2.4%
55764 1
2.4%
55763 1
2.4%
55326 1
2.4%
55123 1
2.4%
55122 1
2.4%

Interactions

2024-03-14T10:24:31.858517image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T10:24:31.726268image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T10:24:31.938833image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T10:24:31.796556image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-03-14T10:24:34.490461image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
번호명 칭도로명주소전화번호우편번호
번호1.0001.0001.0001.0000.000
명 칭1.0001.0001.0001.0001.000
도로명주소1.0001.0001.0001.0001.000
전화번호1.0001.0001.0001.0001.000
우편번호0.0001.0001.0001.0001.000
2024-03-14T10:24:34.627166image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
번호우편번호
번호1.000-0.151
우편번호-0.1511.000

Missing values

2024-03-14T10:24:32.066863image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-03-14T10:24:32.153991image/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

번호명 칭도로명주소전화번호우편번호
01전주성모간호요양보호사교육원전주시 완산구 팔달로 229 (고사동)283-6662~555039
12전주성신간호학원 부설 요양보호사교육원전주시 완산구 팔달로 250 (서노송동)285-1999 285-199054995
23온누리요양보호사교육원전주시 완산구 팔달로 202-16 (3층)231-455455000
34전주요양보호사교육원전주시 덕진구 떡전 4길 8 (금암동)284-119954932
45전주여성인력개발센터 요양보호사교육원전주시 완산구 장승배기로 213 BYC빌딩 2층232-234655106
56전주메디칼요양보호사교육원전주시 완산구 용머리로 57 3층 (효자동1가)225-391055056
67평화요양보호사교육원전주시 완산구 장승배기로 210 (평화동 1가)225-144155122
78송천 탑클래스간호학원 요양보호사교육원전주시 덕진구 천마산로 19(송천동2가)277-770154829
89미래간호학원 부설 요양보호사교육원전주시 덕진구 기린대로 469(덕진동1가)272-474754893
910JK요양보호사교육원전라북도 전주시 완산구 다가동4가 118-5273-835454989
번호명 칭도로명주소전화번호우편번호
321종로요양보호사교육원정읍시 관통로 14-4 (장명동)538-366356165
332정읍간호학원부설요양보호사교육원정읍시 충정로 324 (연지동)535-029756181
343성모간호학원부설요양보호사교육원정읍시 충정로 175-1 (연지동)534-111956165
351남원간호요양보호사교육원남원시 의총로 77. 3층 (왕정동)632-299355764
362남원한국요양보호사교육원남원시 광한북로 43-2 (하정동)626-223355763
371김제성모 요양보호사교육원김제시 동서로 222 (요촌동)545-988854392
381봉동간호학원 부설 요양보호사교육원완주군 봉동읍 봉동로 139261-112555326
391순창요양보호사교육원순창군 순창읍 순화로 25 (2층)652-800156038
401고창성모요양보호사교육원고창군 고창읍 중앙로 180, 3층563-003856436
411부안요양보호사교육원부안군 부안읍 석정로 241 (2층)582-622256315