Overview

Dataset statistics

Number of variables12
Number of observations100
Missing cells175
Missing cells (%)14.6%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory9.8 KiB
Average record size in memory100.3 B

Variable types

Numeric3
Text6
Categorical3

Alerts

sn is highly overall correlated with use_spce_lo and 2 other fieldsHigh correlation
use_spce_la is highly overall correlated with ctprvn_nm and 1 other fieldsHigh correlation
use_spce_lo is highly overall correlated with sn and 2 other fieldsHigh correlation
ctprvn_nm is highly overall correlated with sn and 3 other fieldsHigh correlation
signgu_nm is highly overall correlated with sn and 3 other fieldsHigh correlation
hmpg_url has 77 (77.0%) missing valuesMissing
rm has 98 (98.0%) missing valuesMissing
sn has unique valuesUnique
rn_addr has unique valuesUnique

Reproduction

Analysis started2023-12-10 09:47:09.909040
Analysis finished2023-12-10 09:47:14.498933
Duration4.59 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

sn
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct100
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean51.85
Minimum1
Maximum102
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.0 KiB
2023-12-10T18:47:14.655594image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile5.95
Q125.75
median52.5
Q377.25
95-th percentile97.05
Maximum102
Range101
Interquartile range (IQR)51.5

Descriptive statistics

Standard deviation29.780129
Coefficient of variation (CV)0.57435156
Kurtosis-1.2124534
Mean51.85
Median Absolute Deviation (MAD)26
Skewness-0.031755518
Sum5185
Variance886.85606
MonotonicityStrictly increasing
2023-12-10T18:47:15.039995image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1 1
 
1.0%
67 1
 
1.0%
77 1
 
1.0%
76 1
 
1.0%
75 1
 
1.0%
74 1
 
1.0%
73 1
 
1.0%
72 1
 
1.0%
71 1
 
1.0%
70 1
 
1.0%
Other values (90) 90
90.0%
ValueCountFrequency (%)
1 1
1.0%
2 1
1.0%
3 1
1.0%
4 1
1.0%
5 1
1.0%
6 1
1.0%
7 1
1.0%
8 1
1.0%
9 1
1.0%
10 1
1.0%
ValueCountFrequency (%)
102 1
1.0%
101 1
1.0%
100 1
1.0%
99 1
1.0%
98 1
1.0%
97 1
1.0%
96 1
1.0%
95 1
1.0%
94 1
1.0%
93 1
1.0%

use_spce_nm
Text

Distinct96
Distinct (%)96.0%
Missing0
Missing (%)0.0%
Memory size932.0 B
2023-12-10T18:47:15.514390image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length16
Median length12
Mean length8.87
Min length4

Characters and Unicode

Total characters887
Distinct characters164
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

Unique92 ?
Unique (%)92.0%

Sample

1st row성덕반딧불 작은도서관
2nd row한국자산관리공사 강원지사
3rd row월대산 작은도서관
4th row어울림 작은도서관
5th row강릉시청소년문화의집
ValueCountFrequency (%)
작은도서관 5
 
4.0%
한국전기안전공사 4
 
3.2%
국민건강보험공단 3
 
2.4%
홍천군청소년수련관 2
 
1.6%
정선군청 2
 
1.6%
한국관광공사 2
 
1.6%
원덕청소년문화의집 2
 
1.6%
청정환경사업소 2
 
1.6%
홍천군 2
 
1.6%
강원동부지사 2
 
1.6%
Other values (100) 100
79.4%
2023-12-10T18:47:16.357545image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
관 55
 
6.2%
소 36
 
4.1%
청 33
 
3.7%
도 31
 
3.5%
서 30
 
3.4%
사 27
 
3.0%
26
 
2.9%
년 25
 
2.8%
시 22
 
2.5%
원 22
 
2.5%
Other values (154) 580
65.4%

Most occurring categories

ValueCountFrequency (%)
Other Letter 855
96.4%
Space Separator 26
 
2.9%
Decimal Number 5
 
0.6%
Other Punctuation 1
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
관 55
 
6.4%
소 36
 
4.2%
청 33
 
3.9%
도 31
 
3.6%
서 30
 
3.5%
사 27
 
3.2%
년 25
 
2.9%
시 22
 
2.6%
원 22
 
2.6%
지 20
 
2.3%
Other values (148) 554
64.8%
Decimal Number
ValueCountFrequency (%)
2 2
40.0%
5 1
20.0%
8 1
20.0%
7 1
20.0%
Space Separator
ValueCountFrequency (%)
26
100.0%
Other Punctuation
ValueCountFrequency (%)
, 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 855
96.4%
Common 32
 
3.6%

Most frequent character per script

Hangul
ValueCountFrequency (%)
관 55
 
6.4%
소 36
 
4.2%
청 33
 
3.9%
도 31
 
3.6%
서 30
 
3.5%
사 27
 
3.2%
년 25
 
2.9%
시 22
 
2.6%
원 22
 
2.6%
지 20
 
2.3%
Other values (148) 554
64.8%
Common
ValueCountFrequency (%)
26
81.2%
2 2
 
6.2%
5 1
 
3.1%
8 1
 
3.1%
, 1
 
3.1%
7 1
 
3.1%

Most occurring blocks

ValueCountFrequency (%)
Hangul 855
96.4%
ASCII 32
 
3.6%

Most frequent character per block

Hangul
ValueCountFrequency (%)
관 55
 
6.4%
소 36
 
4.2%
청 33
 
3.9%
도 31
 
3.6%
서 30
 
3.5%
사 27
 
3.2%
년 25
 
2.9%
시 22
 
2.6%
원 22
 
2.6%
지 20
 
2.3%
Other values (148) 554
64.8%
ASCII
ValueCountFrequency (%)
26
81.2%
2 2
 
6.2%
5 1
 
3.1%
8 1
 
3.1%
, 1
 
3.1%
7 1
 
3.1%

use_spce_cl_nm
Categorical

Distinct13
Distinct (%)13.0%
Missing0
Missing (%)0.0%
Memory size932.0 B
강의실
45 
회의실
25 
청소년전용공간, 연습실
6 
강의실, 회의실
5 
다목적실
5 
Other values (8)
14 

Length

Max length21
Median length3
Mean length4.41
Min length2

Unique

Unique6 ?
Unique (%)6.0%

Sample

1st row강의실
2nd row강의실
3rd row강의실
4th row강의실
5th row회의실

Common Values

ValueCountFrequency (%)
강의실 45
45.0%
회의실 25
25.0%
청소년전용공간, 연습실 6
 
6.0%
강의실, 회의실 5
 
5.0%
다목적실 5
 
5.0%
기타 4
 
4.0%
청소년전용공간 4
 
4.0%
기타, 회의실 1
 
1.0%
정보화교육실 1
 
1.0%
강의실, 청소년전용공간, 연습실, 기타 1
 
1.0%
Other values (3) 3
 
3.0%

Length

2023-12-10T18:47:16.630466image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
강의실 52
43.7%
회의실 33
27.7%
청소년전용공간 11
 
9.2%
연습실 9
 
7.6%
기타 7
 
5.9%
다목적실 6
 
5.0%
정보화교육실 1
 
0.8%

tel_no
Text

Distinct75
Distinct (%)75.0%
Missing0
Missing (%)0.0%
Memory size932.0 B
2023-12-10T18:47:17.108377image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length14
Median length12
Mean length12.02
Min length12

Characters and Unicode

Total characters1202
Distinct characters12
Distinct categories3 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique65 ?
Unique (%)65.0%

Sample

1st row033-660-3273
2nd row033-640-3417
3rd row033-660-3273
4th row033-660-3273
5th row033-640-5987
ValueCountFrequency (%)
033-660-3273 6
 
6.0%
033-660-3285 6
 
6.0%
031-729-8824 5
 
5.0%
063-716-2233 4
 
4.0%
032-322-0700 4
 
4.0%
033-560-2125 2
 
2.0%
033-433-4351 2
 
2.0%
033-340-5914 2
 
2.0%
033-460-2331 2
 
2.0%
033-575-1498 2
 
2.0%
Other values (65) 65
65.0%
2023-12-10T18:47:17.981086image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
3 255
21.2%
- 200
16.6%
0 185
15.4%
2 118
9.8%
6 82
 
6.8%
5 77
 
6.4%
1 75
 
6.2%
4 72
 
6.0%
8 55
 
4.6%
7 52
 
4.3%
Other values (2) 31
 
2.6%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 1001
83.3%
Dash Punctuation 200
 
16.6%
Math Symbol 1
 
0.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
3 255
25.5%
0 185
18.5%
2 118
11.8%
6 82
 
8.2%
5 77
 
7.7%
1 75
 
7.5%
4 72
 
7.2%
8 55
 
5.5%
7 52
 
5.2%
9 30
 
3.0%
Dash Punctuation
ValueCountFrequency (%)
- 200
100.0%
Math Symbol
ValueCountFrequency (%)
~ 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 1202
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
3 255
21.2%
- 200
16.6%
0 185
15.4%
2 118
9.8%
6 82
 
6.8%
5 77
 
6.4%
1 75
 
6.2%
4 72
 
6.0%
8 55
 
4.6%
7 52
 
4.3%
Other values (2) 31
 
2.6%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1202
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
3 255
21.2%
- 200
16.6%
0 185
15.4%
2 118
9.8%
6 82
 
6.8%
5 77
 
6.4%
1 75
 
6.2%
4 72
 
6.0%
8 55
 
4.6%
7 52
 
4.3%
Other values (2) 31
 
2.6%

hmpg_url
Text

MISSING 

Distinct14
Distinct (%)60.9%
Missing77
Missing (%)77.0%
Memory size932.0 B
2023-12-10T18:47:18.329147image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length56
Median length27
Mean length23.217391
Min length7

Characters and Unicode

Total characters534
Distinct characters50
Distinct categories8 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique12 ?
Unique (%)52.2%

Sample

1st rowhttp://www.gnslib.or.kr
2nd rowhttp://www.gnslib.or.kr
3rd rowhttp://www.gnslib.or.kr
4th rowhttp://www.gnslib.or.kr
5th rowhttp://www.gnslib.or.kr
ValueCountFrequency (%)
http://www.gnslib.or.kr 7
30.4%
http://www.donghaelib.go.kr 4
17.4%
youth.samcheok.go.kr 1
 
4.3%
wdyouth.samcheok.go.kr 1
 
4.3%
http://www.속초청소년문화의집.com 1
 
4.3%
www.ywyc.kr 1
 
4.3%
https://xn--zb0bx4fhshyokbuas9an8odtebnk.kr 1
 
4.3%
8130924.tistory.com 1
 
4.3%
youth.cwg.go.kr 1
 
4.3%
https://youthzone.chuncheon.go.kr/page.do?pn=sub01_04_01 1
 
4.3%
Other values (4) 4
17.4%
2023-12-10T18:47:18.876903image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
. 62
 
11.6%
w 49
 
9.2%
o 37
 
6.9%
t 36
 
6.7%
h 30
 
5.6%
/ 30
 
5.6%
r 29
 
5.4%
k 24
 
4.5%
g 23
 
4.3%
n 18
 
3.4%
Other values (40) 196
36.7%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 387
72.5%
Other Punctuation 107
 
20.0%
Decimal Number 24
 
4.5%
Other Letter 9
 
1.7%
Dash Punctuation 2
 
0.4%
Connector Punctuation 2
 
0.4%
Uppercase Letter 2
 
0.4%
Math Symbol 1
 
0.2%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
w 49
12.7%
o 37
 
9.6%
t 36
 
9.3%
h 30
 
7.8%
r 29
 
7.5%
k 24
 
6.2%
g 23
 
5.9%
n 18
 
4.7%
s 17
 
4.4%
b 16
 
4.1%
Other values (13) 108
27.9%
Decimal Number
ValueCountFrequency (%)
1 5
20.8%
0 5
20.8%
4 3
12.5%
3 3
12.5%
8 3
12.5%
9 2
 
8.3%
6 1
 
4.2%
2 1
 
4.2%
5 1
 
4.2%
Other Letter
ValueCountFrequency (%)
청 1
11.1%
집 1
11.1%
의 1
11.1%
화 1
11.1%
문 1
11.1%
년 1
11.1%
소 1
11.1%
초 1
11.1%
속 1
11.1%
Other Punctuation
ValueCountFrequency (%)
. 62
57.9%
/ 30
28.0%
: 14
 
13.1%
? 1
 
0.9%
Uppercase Letter
ValueCountFrequency (%)
P 1
50.0%
N 1
50.0%
Dash Punctuation
ValueCountFrequency (%)
- 2
100.0%
Connector Punctuation
ValueCountFrequency (%)
_ 2
100.0%
Math Symbol
ValueCountFrequency (%)
= 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 389
72.8%
Common 136
 
25.5%
Hangul 9
 
1.7%

Most frequent character per script

Latin
ValueCountFrequency (%)
w 49
12.6%
o 37
 
9.5%
t 36
 
9.3%
h 30
 
7.7%
r 29
 
7.5%
k 24
 
6.2%
g 23
 
5.9%
n 18
 
4.6%
s 17
 
4.4%
b 16
 
4.1%
Other values (15) 110
28.3%
Common
ValueCountFrequency (%)
. 62
45.6%
/ 30
22.1%
: 14
 
10.3%
1 5
 
3.7%
0 5
 
3.7%
4 3
 
2.2%
3 3
 
2.2%
8 3
 
2.2%
- 2
 
1.5%
_ 2
 
1.5%
Other values (6) 7
 
5.1%
Hangul
ValueCountFrequency (%)
청 1
11.1%
집 1
11.1%
의 1
11.1%
화 1
11.1%
문 1
11.1%
년 1
11.1%
소 1
11.1%
초 1
11.1%
속 1
11.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 525
98.3%
Hangul 9
 
1.7%

Most frequent character per block

ASCII
ValueCountFrequency (%)
. 62
 
11.8%
w 49
 
9.3%
o 37
 
7.0%
t 36
 
6.9%
h 30
 
5.7%
/ 30
 
5.7%
r 29
 
5.5%
k 24
 
4.6%
g 23
 
4.4%
n 18
 
3.4%
Other values (31) 187
35.6%
Hangul
ValueCountFrequency (%)
청 1
11.1%
집 1
11.1%
의 1
11.1%
화 1
11.1%
문 1
11.1%
년 1
11.1%
소 1
11.1%
초 1
11.1%
속 1
11.1%

rn_addr
Text

UNIQUE 

Distinct100
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size932.0 B
2023-12-10T18:47:19.288012image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length36
Median length25
Mean length18.12
Min length13

Characters and Unicode

Total characters1812
Distinct characters158
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

Unique100 ?
Unique (%)100.0%

Sample

1st row강원 강릉시 강중길 55
2nd row강원 강릉시 경강로 2151
3rd row강원 강릉시 성덕포남로 80-21
4th row강원 강릉시 성덕포남로149번길 42
5th row강원 강릉시 연곡면 연주로 224
ValueCountFrequency (%)
강원 35
 
7.7%
강원도 35
 
7.7%
경기 30
 
6.6%
강릉시 18
 
4.0%
부천시 13
 
2.9%
춘천시 7
 
1.5%
홍천군 6
 
1.3%
성남시 6
 
1.3%
분당구 6
 
1.3%
구리시 6
 
1.3%
Other values (213) 291
64.2%
2023-12-10T18:47:20.018059image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
353
19.5%
강 97
 
5.4%
원 90
 
5.0%
로 80
 
4.4%
시 78
 
4.3%
1 67
 
3.7%
2 51
 
2.8%
길 40
 
2.2%
5 40
 
2.2%
3 37
 
2.0%
Other values (148) 879
48.5%

Most occurring categories

ValueCountFrequency (%)
Other Letter 1085
59.9%
Space Separator 353
 
19.5%
Decimal Number 332
 
18.3%
Dash Punctuation 17
 
0.9%
Close Punctuation 12
 
0.7%
Open Punctuation 12
 
0.7%
Other Punctuation 1
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
강 97
 
8.9%
원 90
 
8.3%
로 80
 
7.4%
시 78
 
7.2%
길 40
 
3.7%
천 36
 
3.3%
도 35
 
3.2%
경 33
 
3.0%
기 30
 
2.8%
읍 25
 
2.3%
Other values (133) 541
49.9%
Decimal Number
ValueCountFrequency (%)
1 67
20.2%
2 51
15.4%
5 40
12.0%
3 37
11.1%
4 37
11.1%
0 29
8.7%
9 22
 
6.6%
6 17
 
5.1%
7 17
 
5.1%
8 15
 
4.5%
Space Separator
ValueCountFrequency (%)
353
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 17
100.0%
Close Punctuation
ValueCountFrequency (%)
) 12
100.0%
Open Punctuation
ValueCountFrequency (%)
( 12
100.0%
Other Punctuation
ValueCountFrequency (%)
. 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 1085
59.9%
Common 727
40.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
강 97
 
8.9%
원 90
 
8.3%
로 80
 
7.4%
시 78
 
7.2%
길 40
 
3.7%
천 36
 
3.3%
도 35
 
3.2%
경 33
 
3.0%
기 30
 
2.8%
읍 25
 
2.3%
Other values (133) 541
49.9%
Common
ValueCountFrequency (%)
353
48.6%
1 67
 
9.2%
2 51
 
7.0%
5 40
 
5.5%
3 37
 
5.1%
4 37
 
5.1%
0 29
 
4.0%
9 22
 
3.0%
- 17
 
2.3%
6 17
 
2.3%
Other values (5) 57
 
7.8%

Most occurring blocks

ValueCountFrequency (%)
Hangul 1085
59.9%
ASCII 727
40.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
353
48.6%
1 67
 
9.2%
2 51
 
7.0%
5 40
 
5.5%
3 37
 
5.1%
4 37
 
5.1%
0 29
 
4.0%
9 22
 
3.0%
- 17
 
2.3%
6 17
 
2.3%
Other values (5) 57
 
7.8%
Hangul
ValueCountFrequency (%)
강 97
 
8.9%
원 90
 
8.3%
로 80
 
7.4%
시 78
 
7.2%
길 40
 
3.7%
천 36
 
3.3%
도 35
 
3.2%
경 33
 
3.0%
기 30
 
2.8%
읍 25
 
2.3%
Other values (133) 541
49.9%

ctprvn_nm
Categorical

HIGH CORRELATION 

Distinct2
Distinct (%)2.0%
Missing0
Missing (%)0.0%
Memory size932.0 B
강원도
70 
경기도
30 

Length

Max length3
Median length3
Mean length3
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
강원도 70
70.0%
경기도 30
30.0%

Length

2023-12-10T18:47:20.471706image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T18:47:20.832447image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
강원도 70
70.0%
경기도 30
30.0%

signgu_nm
Categorical

HIGH CORRELATION 

Distinct22
Distinct (%)22.0%
Missing0
Missing (%)0.0%
Memory size932.0 B
강릉시
18 
부천시
13 
춘천시
7 
원주시
6 
구리시
6 
Other values (17)
50 

Length

Max length3
Median length3
Mean length3
Min length3

Unique

Unique4 ?
Unique (%)4.0%

Sample

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

Common Values

ValueCountFrequency (%)
강릉시 18
18.0%
부천시 13
13.0%
춘천시 7
 
7.0%
원주시 6
 
6.0%
구리시 6
 
6.0%
홍천군 6
 
6.0%
성남시 6
 
6.0%
동해시 5
 
5.0%
삼척시 5
 
5.0%
정선군 4
 
4.0%
Other values (12) 24
24.0%

Length

2023-12-10T18:47:21.028044image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
강릉시 18
18.0%
부천시 13
13.0%
춘천시 7
 
7.0%
원주시 6
 
6.0%
구리시 6
 
6.0%
홍천군 6
 
6.0%
성남시 6
 
6.0%
동해시 5
 
5.0%
삼척시 5
 
5.0%
정선군 4
 
4.0%
Other values (12) 24
24.0%

emd_nm
Text

Distinct64
Distinct (%)64.0%
Missing0
Missing (%)0.0%
Memory size932.0 B
2023-12-10T18:47:21.414520image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length4
Median length3
Mean length2.95
Min length2

Characters and Unicode

Total characters295
Distinct characters90
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique46 ?
Unique (%)46.0%

Sample

1st row입암동
2nd row옥천동
3rd row입암동
4th row포남동
5th row연곡면
ValueCountFrequency (%)
분당구 6
 
6.0%
홍천읍 5
 
5.0%
교동 4
 
4.0%
횡성읍 4
 
4.0%
반곡동 4
 
4.0%
입암동 4
 
4.0%
원덕읍 3
 
3.0%
인창동 3
 
3.0%
정선읍 3
 
3.0%
북면 2
 
2.0%
Other values (54) 62
62.0%
2023-12-10T18:47:22.190908image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
동 63
21.4%
읍 25
 
8.5%
천 10
 
3.4%
구 9
 
3.1%
당 9
 
3.1%
곡 9
 
3.1%
분 6
 
2.0%
홍 6
 
2.0%
교 6
 
2.0%
성 6
 
2.0%
Other values (80) 146
49.5%

Most occurring categories

ValueCountFrequency (%)
Other Letter 295
100.0%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
동 63
21.4%
읍 25
 
8.5%
천 10
 
3.4%
구 9
 
3.1%
당 9
 
3.1%
곡 9
 
3.1%
분 6
 
2.0%
홍 6
 
2.0%
교 6
 
2.0%
성 6
 
2.0%
Other values (80) 146
49.5%

Most occurring scripts

ValueCountFrequency (%)
Hangul 295
100.0%

Most frequent character per script

Hangul
ValueCountFrequency (%)
동 63
21.4%
읍 25
 
8.5%
천 10
 
3.4%
구 9
 
3.1%
당 9
 
3.1%
곡 9
 
3.1%
분 6
 
2.0%
홍 6
 
2.0%
교 6
 
2.0%
성 6
 
2.0%
Other values (80) 146
49.5%

Most occurring blocks

ValueCountFrequency (%)
Hangul 295
100.0%

Most frequent character per block

Hangul
ValueCountFrequency (%)
동 63
21.4%
읍 25
 
8.5%
천 10
 
3.4%
구 9
 
3.1%
당 9
 
3.1%
곡 9
 
3.1%
분 6
 
2.0%
홍 6
 
2.0%
교 6
 
2.0%
성 6
 
2.0%
Other values (80) 146
49.5%

use_spce_la
Real number (ℝ)

HIGH CORRELATION 

Distinct89
Distinct (%)89.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean37.596186
Minimum37.100492
Maximum38.191595
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.0 KiB
2023-12-10T18:47:22.477185image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum37.100492
5-th percentile37.176378
Q137.418425
median37.539114
Q337.762352
95-th percentile38.107245
Maximum38.191595
Range1.0911029
Interquartile range (IQR)0.3439265

Descriptive statistics

Standard deviation0.25585104
Coefficient of variation (CV)0.0068052394
Kurtosis-0.24682011
Mean37.596186
Median Absolute Deviation (MAD)0.1878841
Skewness0.34950386
Sum3759.6186
Variance0.065459757
MonotonicityNot monotonic
2023-12-10T18:47:22.759655image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
37.6898445 3
 
3.0%
37.7638741 2
 
2.0%
37.3805051 2
 
2.0%
37.4899924 2
 
2.0%
37.5103154 2
 
2.0%
37.3245494 2
 
2.0%
37.1764788 2
 
2.0%
37.7559784 2
 
2.0%
37.762352 2
 
2.0%
37.7629892 2
 
2.0%
Other values (79) 79
79.0%
ValueCountFrequency (%)
37.1004919 1
1.0%
37.1436556 1
1.0%
37.1650578 1
1.0%
37.1672043 1
1.0%
37.1744611 1
1.0%
37.1764788 2
2.0%
37.1781563 1
1.0%
37.2143754 1
1.0%
37.3119965 1
1.0%
37.324388 1
1.0%
ValueCountFrequency (%)
38.1915948 1
1.0%
38.1914131 1
1.0%
38.1459397 1
1.0%
38.1259062 1
1.0%
38.1254899 1
1.0%
38.1062847 1
1.0%
38.105424 1
1.0%
38.070159 1
1.0%
37.949058 1
1.0%
37.8949844 1
1.0%

use_spce_lo
Real number (ℝ)

HIGH CORRELATION 

Distinct89
Distinct (%)89.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean128.01799
Minimum126.74022
Maximum129.33491
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.0 KiB
2023-12-10T18:47:23.017156image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum126.74022
5-th percentile126.77332
Q1127.1415
median127.97713
Q3128.89092
95-th percentile129.12006
Maximum129.33491
Range2.59469
Interquartile range (IQR)1.7494147

Descriptive statistics

Standard deviation0.84672872
Coefficient of variation (CV)0.0066141388
Kurtosis-1.4121211
Mean128.01799
Median Absolute Deviation (MAD)0.86938225
Skewness-0.13077326
Sum12801.799
Variance0.71694953
MonotonicityNot monotonic
2023-12-10T18:47:23.276479image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
127.8951409 3
 
3.0%
128.8909187 2
 
2.0%
128.6608685 2
 
2.0%
127.9771328 2
 
2.0%
127.9705144 2
 
2.0%
127.9902185 2
 
2.0%
129.334911 2
 
2.0%
128.908161 2
 
2.0%
128.9180743 2
 
2.0%
128.9083931 2
 
2.0%
Other values (79) 79
79.0%
ValueCountFrequency (%)
126.740221 1
1.0%
126.7543519 1
1.0%
126.7628572 1
1.0%
126.7631494 1
1.0%
126.7663462 1
1.0%
126.7736884 1
1.0%
126.7789795 1
1.0%
126.7857502 1
1.0%
126.7943259 1
1.0%
126.7962235 1
1.0%
ValueCountFrequency (%)
129.334911 2
2.0%
129.2864267 1
1.0%
129.16466 1
1.0%
129.1575222 1
1.0%
129.1180884 1
1.0%
129.114202 1
1.0%
129.1059792 1
1.0%
129.1044104 1
1.0%
129.0682535 1
1.0%
129.0242694 1
1.0%

rm
Text

MISSING 

Distinct2
Distinct (%)100.0%
Missing98
Missing (%)98.0%
Memory size932.0 B
2023-12-10T18:47:23.615064image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length6
Median length6
Mean length6
Min length6

Characters and Unicode

Total characters12
Distinct characters12
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique2 ?
Unique (%)100.0%

Sample

1st row홈페이지없음
2nd row정보찾기힘듦
ValueCountFrequency (%)
홈페이지없음 1
50.0%
정보찾기힘듦 1
50.0%
2023-12-10T18:47:24.114008image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
홈 1
8.3%
페 1
8.3%
이 1
8.3%
지 1
8.3%
없 1
8.3%
음 1
8.3%
정 1
8.3%
보 1
8.3%
찾 1
8.3%
기 1
8.3%
Other values (2) 2
16.7%

Most occurring categories

ValueCountFrequency (%)
Other Letter 12
100.0%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
홈 1
8.3%
페 1
8.3%
이 1
8.3%
지 1
8.3%
없 1
8.3%
음 1
8.3%
정 1
8.3%
보 1
8.3%
찾 1
8.3%
기 1
8.3%
Other values (2) 2
16.7%

Most occurring scripts

ValueCountFrequency (%)
Hangul 12
100.0%

Most frequent character per script

Hangul
ValueCountFrequency (%)
홈 1
8.3%
페 1
8.3%
이 1
8.3%
지 1
8.3%
없 1
8.3%
음 1
8.3%
정 1
8.3%
보 1
8.3%
찾 1
8.3%
기 1
8.3%
Other values (2) 2
16.7%

Most occurring blocks

ValueCountFrequency (%)
Hangul 12
100.0%

Most frequent character per block

Hangul
ValueCountFrequency (%)
홈 1
8.3%
페 1
8.3%
이 1
8.3%
지 1
8.3%
없 1
8.3%
음 1
8.3%
정 1
8.3%
보 1
8.3%
찾 1
8.3%
기 1
8.3%
Other values (2) 2
16.7%

Interactions

2023-12-10T18:47:12.793941image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T18:47:11.832944image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T18:47:12.370493image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T18:47:12.932397image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T18:47:12.064494image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T18:47:12.506962image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T18:47:13.174692image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T18:47:12.218804image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T18:47:12.646330image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-10T18:47:24.296197image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
snuse_spce_nmuse_spce_cl_nmtel_nohmpg_urlrn_addrctprvn_nmsigngu_nmemd_nmuse_spce_lause_spce_lorm
sn1.0000.6700.4780.9540.8821.0000.9990.9010.8860.7920.8610.000
use_spce_nm0.6701.0000.9570.9971.0001.0001.0001.0001.0001.0001.0000.000
use_spce_cl_nm0.4780.9571.0000.8981.0001.0000.2210.4350.8610.0000.216NaN
tel_no0.9540.9970.8981.0001.0001.0001.0000.9970.9890.9870.9970.000
hmpg_url0.8821.0001.0001.0001.0001.000NaN1.0001.0000.9300.9990.000
rn_addr1.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0000.000
ctprvn_nm0.9991.0000.2211.000NaN1.0001.0001.0001.0000.7381.000NaN
signgu_nm0.9011.0000.4350.9971.0001.0001.0001.0001.0000.9490.9930.000
emd_nm0.8861.0000.8610.9891.0001.0001.0001.0001.0000.9980.9980.000
use_spce_la0.7921.0000.0000.9870.9301.0000.7380.9490.9981.0000.9090.000
use_spce_lo0.8611.0000.2160.9970.9991.0001.0000.9930.9980.9091.0000.000
rm0.0000.000NaN0.0000.0000.000NaN0.0000.0000.0000.0001.000
2023-12-10T18:47:24.570816image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
use_spce_cl_nmctprvn_nmsigngu_nm
use_spce_cl_nm1.0000.1900.143
ctprvn_nm0.1901.0000.892
signgu_nm0.1430.8921.000
2023-12-10T18:47:25.241269image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
snuse_spce_lause_spce_louse_spce_cl_nmctprvn_nmsigngu_nm
sn1.000-0.265-0.7420.2130.9350.580
use_spce_la-0.2651.0000.0230.0000.5550.703
use_spce_lo-0.7420.0231.0000.0810.9580.891
use_spce_cl_nm0.2130.0000.0811.0000.1900.143
ctprvn_nm0.9350.5550.9580.1901.0000.892
signgu_nm0.5800.7030.8910.1430.8921.000

Missing values

2023-12-10T18:47:13.395121image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-10T18:47:13.980841image/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.
2023-12-10T18:47:14.294360image/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

snuse_spce_nmuse_spce_cl_nmtel_nohmpg_urlrn_addrctprvn_nmsigngu_nmemd_nmuse_spce_lause_spce_lorm
01성덕반딧불 작은도서관강의실033-660-3273<NA>강원 강릉시 강중길 55강원도강릉시입암동37.755978128.908161<NA>
12한국자산관리공사 강원지사강의실033-640-3417<NA>강원 강릉시 경강로 2151강원도강릉시옥천동37.758119128.900636<NA>
23월대산 작은도서관강의실033-660-3273<NA>강원 강릉시 성덕포남로 80-21강원도강릉시입암동37.762352128.918074<NA>
34어울림 작은도서관강의실033-660-3273<NA>강원 강릉시 성덕포남로149번길 42강원도강릉시포남동37.762989128.908393<NA>
45강릉시청소년문화의집회의실033-640-5987<NA>강원 강릉시 연곡면 연주로 224강원도강릉시연곡면37.873631128.831859<NA>
56초당 작은도서관 본관2층강의실033-660-3273<NA>강원 강릉시 연당길 116강원도강릉시초당동37.782721128.913791<NA>
67한국전기안전공사 강원동부지사회의실063-716-2233<NA>강원 강릉시 유죽길 533강원도강릉시죽헌동37.780932128.874389<NA>
78모루도서관강의실033-660-3273<NA>강원 강릉시 율곡로 2923-12강원도강릉시교동37.763874128.890919<NA>
89문화 작은도서관강의실033-660-3273<NA>강원 강릉시 임영로155번길 18강원도강릉시홍제동37.754521128.889762<NA>
910동북지방통계청강릉사무소강의실033-640-3936<NA>강원 강릉시 화부산로40번길 49강원도강릉시교동37.761421128.89007<NA>
snuse_spce_nmuse_spce_cl_nmtel_nohmpg_urlrn_addrctprvn_nmsigngu_nmemd_nmuse_spce_lause_spce_lorm
9093꿈빛도서관회의실032-625-4629<NA>경기 부천시 신흥로275번길 19경기도부천시중동37.508033126.773688<NA>
9194심곡종합사회복지관강의실032-625-2825<NA>경기 부천시 심곡로9번길 54경기도부천시심곡본동37.482402126.77898<NA>
9295부천시산울림청소년수련관강의실, 회의실032-322-0700<NA>경기 부천시 역곡로 149-65경기도부천시춘의동37.498326126.804976<NA>
9396부천여성청소년재단 5층회의실032-322-0700<NA>경기 부천시 장말로 107경기도부천시상동37.494903126.754352<NA>
9497판교생태학습원강의실031-729-8824<NA>경기 성남시 분당구 대왕판교로645번길 21경기도성남시분당구37.399494127.103799<NA>
9598지구촌평생교육원강의실031-729-8824<NA>경기 성남시 분당구 돌마로 52경기도성남시분당구37.349645127.107737<NA>
9699보람무지개작은도서관강의실031-729-8824<NA>경기 성남시 분당구 동판교로 59경기도성남시분당구37.396443127.111483<NA>
97100성남시율동생태학습원강의실031-729-8824<NA>경기 성남시 분당구 문정로 145경기도성남시분당구37.382827127.149969<NA>
98101구미도서관강의실031-729-4684<NA>경기 성남시 분당구 미금일로 105경기도성남시분당구37.345442127.107764<NA>
99102성남지역사회교육협의회강의실031-729-8824<NA>경기 성남시 분당구 방아로 40경기도성남시분당구37.398452127.133056<NA>