Overview

Dataset statistics

Number of variables12
Number of observations620
Missing cells871
Missing cells (%)11.7%
Duplicate rows2
Duplicate rows (%)0.3%
Total size in memory61.3 KiB
Average record size in memory101.2 B

Variable types

Categorical4
Text6
Numeric2

Dataset

Description경기도 화성시_사회복지시설에 대한 데이터로 복지시설번호, 시설명, 지역코드, 산, 번지, 호, 통, 반, 시설전화번호, 설치일자, 입소정원, 시설대표자명 등의 항목을 제공합니다.
Author경기도 화성시
URLhttps://www.data.go.kr/data/15093524/fileData.do

Alerts

Dataset has 2 (0.3%) duplicate rowsDuplicates
복지시설번호 is highly imbalanced (60.1%)Imbalance
산 is highly imbalanced (92.1%)Imbalance
통 is highly imbalanced (98.3%)Imbalance
반 is highly imbalanced (98.3%)Imbalance
지역코드 has 347 (56.0%) missing valuesMissing
번지 has 35 (5.6%) missing valuesMissing
호 has 397 (64.0%) missing valuesMissing
시설전화번호 has 92 (14.8%) missing valuesMissing
입소정원 has 44 (7.1%) zerosZeros

Reproduction

Analysis started2023-12-12 08:48:07.622695
Analysis finished2023-12-12 08:48:09.764496
Duration2.14 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

복지시설번호
Categorical

IMBALANCE 

Distinct4
Distinct (%)0.6%
Missing0
Missing (%)0.0%
Memory size5.0 KiB
5.53E+15
480 
4.12E+15
138 
7.00E+15
 
1
2004 1200001
 
1

Length

Max length16
Median length8
Mean length8.0129032
Min length8

Unique

Unique2 ?
Unique (%)0.3%

Sample

1st row5.53E+15
2nd row5.53E+15
3rd row5.53E+15
4th row5.53E+15
5th row5.53E+15

Common Values

ValueCountFrequency (%)
5.53E+15 480
77.4%
4.12E+15 138
 
22.3%
7.00E+15 1
 
0.2%
2004 1200001 1
 
0.2%

Length

2023-12-12T17:48:09.878534image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T17:48:10.020712image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
5.53e+15 480
77.3%
4.12e+15 138
 
22.2%
7.00e+15 1
 
0.2%
2004 1
 
0.2%
1200001 1
 
0.2%

시설명
Text

Distinct597
Distinct (%)96.3%
Missing0
Missing (%)0.0%
Memory size5.0 KiB
2023-12-12T17:48:10.321588image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length22
Median length21
Mean length7.4193548
Min length2

Characters and Unicode

Total characters4600
Distinct characters356
Distinct categories8 ?
Distinct scripts3 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique576 ?
Unique (%)92.9%

Sample

1st row노랑단추어린이집
2nd row수직1리 경로당
3rd row신성미소지움(A) 경로당
4th row화평수직경로대학
5th row해피아이어린이집
ValueCountFrequency (%)
경로당 101
 
13.0%
아파트 12
 
1.5%
노인회 7
 
0.9%
놀이방 4
 
0.5%
사랑의 3
 
0.4%
자오쉼터 3
 
0.4%
주공11단지 3
 
0.4%
집 3
 
0.4%
남양그룹홈 3
 
0.4%
어린이집 3
 
0.4%
Other values (611) 637
81.8%
2023-12-12T17:48:10.774246image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
이 406
 
8.8%
집 285
 
6.2%
린 283
 
6.2%
어 278
 
6.0%
당 169
 
3.7%
로 167
 
3.6%
경 167
 
3.6%
161
 
3.5%
리 138
 
3.0%
아 89
 
1.9%
Other values (346) 2457
53.4%

Most occurring categories

ValueCountFrequency (%)
Other Letter 4261
92.6%
Space Separator 161
 
3.5%
Decimal Number 141
 
3.1%
Open Punctuation 12
 
0.3%
Close Punctuation 12
 
0.3%
Uppercase Letter 10
 
0.2%
Other Punctuation 2
 
< 0.1%
Math Symbol 1
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
이 406
 
9.5%
집 285
 
6.7%
린 283
 
6.6%
어 278
 
6.5%
당 169
 
4.0%
로 167
 
3.9%
경 167
 
3.9%
리 138
 
3.2%
아 89
 
2.1%
방 85
 
2.0%
Other values (325) 2194
51.5%
Decimal Number
ValueCountFrequency (%)
1 46
32.6%
2 41
29.1%
3 23
16.3%
4 14
 
9.9%
5 8
 
5.7%
7 4
 
2.8%
6 2
 
1.4%
8 1
 
0.7%
0 1
 
0.7%
9 1
 
0.7%
Uppercase Letter
ValueCountFrequency (%)
A 3
30.0%
B 2
20.0%
C 2
20.0%
G 1
 
10.0%
L 1
 
10.0%
D 1
 
10.0%
Space Separator
ValueCountFrequency (%)
161
100.0%
Open Punctuation
ValueCountFrequency (%)
( 12
100.0%
Close Punctuation
ValueCountFrequency (%)
) 12
100.0%
Other Punctuation
ValueCountFrequency (%)
. 2
100.0%
Math Symbol
ValueCountFrequency (%)
→ 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 4261
92.6%
Common 329
 
7.2%
Latin 10
 
0.2%

Most frequent character per script

Hangul
ValueCountFrequency (%)
이 406
 
9.5%
집 285
 
6.7%
린 283
 
6.6%
어 278
 
6.5%
당 169
 
4.0%
로 167
 
3.9%
경 167
 
3.9%
리 138
 
3.2%
아 89
 
2.1%
방 85
 
2.0%
Other values (325) 2194
51.5%
Common
ValueCountFrequency (%)
161
48.9%
1 46
 
14.0%
2 41
 
12.5%
3 23
 
7.0%
4 14
 
4.3%
( 12
 
3.6%
) 12
 
3.6%
5 8
 
2.4%
7 4
 
1.2%
. 2
 
0.6%
Other values (5) 6
 
1.8%
Latin
ValueCountFrequency (%)
A 3
30.0%
B 2
20.0%
C 2
20.0%
G 1
 
10.0%
L 1
 
10.0%
D 1
 
10.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 4261
92.6%
ASCII 338
 
7.3%
Arrows 1
 
< 0.1%

Most frequent character per block

Hangul
ValueCountFrequency (%)
이 406
 
9.5%
집 285
 
6.7%
린 283
 
6.6%
어 278
 
6.5%
당 169
 
4.0%
로 167
 
3.9%
경 167
 
3.9%
리 138
 
3.2%
아 89
 
2.1%
방 85
 
2.0%
Other values (325) 2194
51.5%
ASCII
ValueCountFrequency (%)
161
47.6%
1 46
 
13.6%
2 41
 
12.1%
3 23
 
6.8%
4 14
 
4.1%
( 12
 
3.6%
) 12
 
3.6%
5 8
 
2.4%
7 4
 
1.2%
A 3
 
0.9%
Other values (10) 14
 
4.1%
Arrows
ValueCountFrequency (%)
→ 1
100.0%

지역코드
Text

MISSING 

Distinct95
Distinct (%)34.8%
Missing347
Missing (%)56.0%
Memory size5.0 KiB
2023-12-12T17:48:11.075968image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length3
Median length3
Mean length2.9084249
Min length2

Characters and Unicode

Total characters794
Distinct characters107
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

Unique34 ?
Unique (%)12.5%

Sample

1st row기산동
2nd row제기리
3rd row기안동
4th row병점동
5th row진안동
ValueCountFrequency (%)
상리 12
 
4.4%
와우리 11
 
4.0%
조암리 11
 
4.0%
병점동 10
 
3.7%
화산리 9
 
3.3%
수영리 7
 
2.6%
동화리 7
 
2.6%
진안동 6
 
2.2%
이화리 6
 
2.2%
석천리 5
 
1.8%
Other values (85) 189
69.2%
2023-12-12T17:48:11.484315image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
리 229
28.8%
동 51
 
6.4%
화 34
 
4.3%
안 22
 
2.8%
곡 18
 
2.3%
산 17
 
2.1%
천 15
 
1.9%
우 14
 
1.8%
상 13
 
1.6%
송 13
 
1.6%
Other values (97) 368
46.3%

Most occurring categories

ValueCountFrequency (%)
Other Letter 794
100.0%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
리 229
28.8%
동 51
 
6.4%
화 34
 
4.3%
안 22
 
2.8%
곡 18
 
2.3%
산 17
 
2.1%
천 15
 
1.9%
우 14
 
1.8%
상 13
 
1.6%
송 13
 
1.6%
Other values (97) 368
46.3%

Most occurring scripts

ValueCountFrequency (%)
Hangul 794
100.0%

Most frequent character per script

Hangul
ValueCountFrequency (%)
리 229
28.8%
동 51
 
6.4%
화 34
 
4.3%
안 22
 
2.8%
곡 18
 
2.3%
산 17
 
2.1%
천 15
 
1.9%
우 14
 
1.8%
상 13
 
1.6%
송 13
 
1.6%
Other values (97) 368
46.3%

Most occurring blocks

ValueCountFrequency (%)
Hangul 794
100.0%

Most frequent character per block

Hangul
ValueCountFrequency (%)
리 229
28.8%
동 51
 
6.4%
화 34
 
4.3%
안 22
 
2.8%
곡 18
 
2.3%
산 17
 
2.1%
천 15
 
1.9%
우 14
 
1.8%
상 13
 
1.6%
송 13
 
1.6%
Other values (97) 368
46.3%

산
Categorical

IMBALANCE 

Distinct2
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Memory size5.0 KiB
1
614 
2
 
6

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row1
2nd row1
3rd row1
4th row1
5th row1

Common Values

ValueCountFrequency (%)
1 614
99.0%
2 6
 
1.0%

Length

2023-12-12T17:48:11.619071image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T17:48:11.717034image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
1 614
99.0%
2 6
 
1.0%

번지
Text

MISSING 

Distinct308
Distinct (%)52.6%
Missing35
Missing (%)5.6%
Memory size5.0 KiB
2023-12-12T17:48:12.027394image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length8
Median length3
Mean length3.191453
Min length1

Characters and Unicode

Total characters1867
Distinct characters30
Distinct categories6 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique206 ?
Unique (%)35.2%

Sample

1st row466
2nd row110
3rd row409
4th row357
5th row290
ValueCountFrequency (%)
817 17
 
2.9%
911 12
 
2.0%
910 12
 
2.0%
895 11
 
1.9%
466 10
 
1.7%
865 8
 
1.4%
237 8
 
1.4%
485 8
 
1.4%
614 7
 
1.2%
868 7
 
1.2%
Other values (299) 486
82.9%
2023-12-12T17:48:12.567660image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 262
14.0%
5 201
10.8%
8 197
10.6%
2 185
9.9%
9 177
9.5%
0 176
9.4%
6 160
8.6%
4 159
8.5%
3 142
7.6%
7 116
6.2%
Other values (20) 92
 
4.9%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 1775
95.1%
Dash Punctuation 56
 
3.0%
Lowercase Letter 20
 
1.1%
Uppercase Letter 10
 
0.5%
Other Letter 5
 
0.3%
Space Separator 1
 
0.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 262
14.8%
5 201
11.3%
8 197
11.1%
2 185
10.4%
9 177
10.0%
0 176
9.9%
6 160
9.0%
4 159
9.0%
3 142
8.0%
7 116
6.5%
Lowercase Letter
ValueCountFrequency (%)
n 4
20.0%
r 3
15.0%
e 3
15.0%
p 3
15.0%
a 3
15.0%
u 2
10.0%
c 1
 
5.0%
b 1
 
5.0%
Uppercase Letter
ValueCountFrequency (%)
J 4
40.0%
A 2
20.0%
F 1
 
10.0%
S 1
 
10.0%
M 1
 
10.0%
D 1
 
10.0%
Other Letter
ValueCountFrequency (%)
외 2
40.0%
호 1
20.0%
일 1
20.0%
월 1
20.0%
Dash Punctuation
ValueCountFrequency (%)
- 56
100.0%
Space Separator
ValueCountFrequency (%)
1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 1832
98.1%
Latin 30
 
1.6%
Hangul 5
 
0.3%

Most frequent character per script

Latin
ValueCountFrequency (%)
n 4
13.3%
J 4
13.3%
r 3
10.0%
e 3
10.0%
p 3
10.0%
a 3
10.0%
u 2
6.7%
A 2
6.7%
F 1
 
3.3%
S 1
 
3.3%
Other values (4) 4
13.3%
Common
ValueCountFrequency (%)
1 262
14.3%
5 201
11.0%
8 197
10.8%
2 185
10.1%
9 177
9.7%
0 176
9.6%
6 160
8.7%
4 159
8.7%
3 142
7.8%
7 116
6.3%
Other values (2) 57
 
3.1%
Hangul
ValueCountFrequency (%)
외 2
40.0%
호 1
20.0%
일 1
20.0%
월 1
20.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1862
99.7%
Hangul 5
 
0.3%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 262
14.1%
5 201
10.8%
8 197
10.6%
2 185
9.9%
9 177
9.5%
0 176
9.5%
6 160
8.6%
4 159
8.5%
3 142
7.6%
7 116
6.2%
Other values (16) 87
 
4.7%
Hangul
ValueCountFrequency (%)
외 2
40.0%
호 1
20.0%
일 1
20.0%
월 1
20.0%

호
Real number (ℝ)

MISSING 

Distinct37
Distinct (%)16.6%
Missing397
Missing (%)64.0%
Infinite0
Infinite (%)0.0%
Mean11.686099
Minimum1
Maximum346
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size5.6 KiB
2023-12-12T17:48:12.740744image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q11
median4
Q311
95-th percentile32
Maximum346
Range345
Interquartile range (IQR)10

Descriptive statistics

Standard deviation32.15209
Coefficient of variation (CV)2.7513108
Kurtosis68.981577
Mean11.686099
Median Absolute Deviation (MAD)3
Skewness7.6743253
Sum2606
Variance1033.7569
MonotonicityNot monotonic
2023-12-12T17:48:12.888324image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=37)
ValueCountFrequency (%)
1 59
 
9.5%
2 27
 
4.4%
3 18
 
2.9%
5 15
 
2.4%
4 15
 
2.4%
6 9
 
1.5%
12 7
 
1.1%
9 7
 
1.1%
15 5
 
0.8%
10 5
 
0.8%
Other values (27) 56
 
9.0%
(Missing) 397
64.0%
ValueCountFrequency (%)
1 59
9.5%
2 27
4.4%
3 18
 
2.9%
4 15
 
2.4%
5 15
 
2.4%
6 9
 
1.5%
7 5
 
0.8%
8 5
 
0.8%
9 7
 
1.1%
10 5
 
0.8%
ValueCountFrequency (%)
346 1
0.2%
260 1
0.2%
129 1
0.2%
100 1
0.2%
93 1
0.2%
83 1
0.2%
71 1
0.2%
46 1
0.2%
45 1
0.2%
38 1
0.2%

통
Categorical

IMBALANCE 

Distinct2
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Memory size5.0 KiB
<NA>
619 
9
 
1

Length

Max length4
Median length4
Mean length3.9951613
Min length1

Unique

Unique1 ?
Unique (%)0.2%

Sample

1st row<NA>
2nd row<NA>
3rd row<NA>
4th row<NA>
5th row<NA>

Common Values

ValueCountFrequency (%)
<NA> 619
99.8%
9 1
 
0.2%

Length

2023-12-12T17:48:13.036858image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T17:48:13.138178image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 619
99.8%
9 1
 
0.2%

반
Categorical

IMBALANCE 

Distinct2
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Memory size5.0 KiB
<NA>
619 
1
 
1

Length

Max length4
Median length4
Mean length3.9951613
Min length1

Unique

Unique1 ?
Unique (%)0.2%

Sample

1st row<NA>
2nd row<NA>
3rd row<NA>
4th row<NA>
5th row<NA>

Common Values

ValueCountFrequency (%)
<NA> 619
99.8%
1 1
 
0.2%

Length

2023-12-12T17:48:13.238498image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T17:48:13.338391image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 619
99.8%
1 1
 
0.2%

시설전화번호
Text

MISSING 

Distinct517
Distinct (%)97.9%
Missing92
Missing (%)14.8%
Memory size5.0 KiB
2023-12-12T17:48:13.618563image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length12
Median length12
Mean length11.715909
Min length8

Characters and Unicode

Total characters6186
Distinct characters14
Distinct categories5 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique509 ?
Unique (%)96.4%

Sample

1st row031 234 9567
2nd row031 354 3906
3rd row031 234 2199
4th row031 235 5373
5th row031 221 7222
ValueCountFrequency (%)
031 382
35.4%
358 11
 
1.0%
0031 10
 
0.9%
031358 8
 
0.7%
221 7
 
0.6%
356 6
 
0.6%
357 5
 
0.5%
031224 5
 
0.5%
352 5
 
0.5%
031357 5
 
0.5%
Other values (570) 635
58.9%
2023-12-12T17:48:14.324479image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
3 1153
18.6%
904
14.6%
0 850
13.7%
1 794
12.8%
2 671
10.8%
5 446
 
7.2%
7 327
 
5.3%
8 273
 
4.4%
9 263
 
4.3%
4 255
 
4.1%
Other values (4) 250
 
4.0%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 5279
85.3%
Space Separator 904
 
14.6%
Other Punctuation 1
 
< 0.1%
Uppercase Letter 1
 
< 0.1%
Math Symbol 1
 
< 0.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
3 1153
21.8%
0 850
16.1%
1 794
15.0%
2 671
12.7%
5 446
 
8.4%
7 327
 
6.2%
8 273
 
5.2%
9 263
 
5.0%
4 255
 
4.8%
6 247
 
4.7%
Space Separator
ValueCountFrequency (%)
904
100.0%
Other Punctuation
ValueCountFrequency (%)
. 1
100.0%
Uppercase Letter
ValueCountFrequency (%)
E 1
100.0%
Math Symbol
ValueCountFrequency (%)
+ 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 6185
> 99.9%
Latin 1
 
< 0.1%

Most frequent character per script

Common
ValueCountFrequency (%)
3 1153
18.6%
904
14.6%
0 850
13.7%
1 794
12.8%
2 671
10.8%
5 446
 
7.2%
7 327
 
5.3%
8 273
 
4.4%
9 263
 
4.3%
4 255
 
4.1%
Other values (3) 249
 
4.0%
Latin
ValueCountFrequency (%)
E 1
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 6186
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
3 1153
18.6%
904
14.6%
0 850
13.7%
1 794
12.8%
2 671
10.8%
5 446
 
7.2%
7 327
 
5.3%
8 273
 
4.4%
9 263
 
4.3%
4 255
 
4.1%
Other values (4) 250
 
4.0%

설치일자
Text

Distinct435
Distinct (%)70.2%
Missing0
Missing (%)0.0%
Memory size5.0 KiB
2023-12-12T17:48:14.725556image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length10
Median length10
Mean length10
Min length10

Characters and Unicode

Total characters6200
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

Unique333 ?
Unique (%)53.7%

Sample

1st row2006-04-18
2nd row1996-01-11
3rd row2006-05-10
4th row2006-05-22
5th row2006-05-17
ValueCountFrequency (%)
2005-01-25 10
 
1.6%
1989-06-03 9
 
1.5%
2004-07-23 9
 
1.5%
2004-08-16 6
 
1.0%
2005-01-28 6
 
1.0%
2004-07-08 6
 
1.0%
1999-03-06 5
 
0.8%
2005-01-19 5
 
0.8%
2004-12-28 5
 
0.8%
2004-10-22 4
 
0.6%
Other values (425) 555
89.5%
2023-12-12T17:48:15.248520image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 1642
26.5%
- 1240
20.0%
2 861
13.9%
1 764
12.3%
9 533
 
8.6%
4 224
 
3.6%
6 207
 
3.3%
3 202
 
3.3%
5 196
 
3.2%
8 180
 
2.9%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 4960
80.0%
Dash Punctuation 1240
 
20.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 1642
33.1%
2 861
17.4%
1 764
15.4%
9 533
 
10.7%
4 224
 
4.5%
6 207
 
4.2%
3 202
 
4.1%
5 196
 
4.0%
8 180
 
3.6%
7 151
 
3.0%
Dash Punctuation
ValueCountFrequency (%)
- 1240
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 6200
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 1642
26.5%
- 1240
20.0%
2 861
13.9%
1 764
12.3%
9 533
 
8.6%
4 224
 
3.6%
6 207
 
3.3%
3 202
 
3.3%
5 196
 
3.2%
8 180
 
2.9%

Most occurring blocks

ValueCountFrequency (%)
ASCII 6200
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 1642
26.5%
- 1240
20.0%
2 861
13.9%
1 764
12.3%
9 533
 
8.6%
4 224
 
3.6%
6 207
 
3.3%
3 202
 
3.3%
5 196
 
3.2%
8 180
 
2.9%

입소정원
Real number (ℝ)

ZEROS 

Distinct95
Distinct (%)15.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean35.227419
Minimum0
Maximum676
Zeros44
Zeros (%)7.1%
Negative0
Negative (%)0.0%
Memory size5.6 KiB
2023-12-12T17:48:15.417560image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q118
median24
Q339
95-th percentile94
Maximum676
Range676
Interquartile range (IQR)21

Descriptive statistics

Standard deviation43.154809
Coefficient of variation (CV)1.2250346
Kurtosis86.011182
Mean35.227419
Median Absolute Deviation (MAD)10
Skewness7.2026856
Sum21841
Variance1862.3375
MonotonicityNot monotonic
2023-12-12T17:48:15.586887image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
20 95
 
15.3%
0 44
 
7.1%
19 38
 
6.1%
39 33
 
5.3%
15 22
 
3.5%
17 17
 
2.7%
18 14
 
2.3%
50 14
 
2.3%
29 14
 
2.3%
30 14
 
2.3%
Other values (85) 315
50.8%
ValueCountFrequency (%)
0 44
7.1%
5 9
 
1.5%
6 1
 
0.2%
7 3
 
0.5%
8 1
 
0.2%
9 5
 
0.8%
10 10
 
1.6%
11 4
 
0.6%
12 5
 
0.8%
13 8
 
1.3%
ValueCountFrequency (%)
676 1
0.2%
300 2
0.3%
274 1
0.2%
260 1
0.2%
250 1
0.2%
189 2
0.3%
177 1
0.2%
163 1
0.2%
149 1
0.2%
147 1
0.2%

시설대표자명
Text

Distinct555
Distinct (%)89.5%
Missing0
Missing (%)0.0%
Memory size5.0 KiB
2023-12-12T17:48:15.887730image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length23
Median length3
Mean length3.3193548
Min length2

Characters and Unicode

Total characters2058
Distinct characters192
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

Unique499 ?
Unique (%)80.5%

Sample

1st row오석화
2nd row박귀연
3rd row황지순
4th row(자)한국노인대학복지협의회 화평수직경로대학
5th row우정남
ValueCountFrequency (%)
고난식 4
 
0.6%
윤영자 3
 
0.5%
김진영 3
 
0.5%
최순덕 3
 
0.5%
경산복지재단 3
 
0.5%
유민수 3
 
0.5%
김미아 3
 
0.5%
조시현 3
 
0.5%
김은희 2
 
0.3%
김정원 2
 
0.3%
Other values (548) 596
95.4%
2023-12-12T17:48:16.279874image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
김 108
 
5.2%
이 90
 
4.4%
정 81
 
3.9%
숙 63
 
3.1%
영 60
 
2.9%
희 51
 
2.5%
순 49
 
2.4%
경 45
 
2.2%
현 45
 
2.2%
최 41
 
2.0%
Other values (182) 1425
69.2%

Most occurring categories

ValueCountFrequency (%)
Other Letter 2043
99.3%
Space Separator 5
 
0.2%
Close Punctuation 5
 
0.2%
Open Punctuation 5
 
0.2%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
김 108
 
5.3%
이 90
 
4.4%
정 81
 
4.0%
숙 63
 
3.1%
영 60
 
2.9%
희 51
 
2.5%
순 49
 
2.4%
경 45
 
2.2%
현 45
 
2.2%
최 41
 
2.0%
Other values (179) 1410
69.0%
Space Separator
ValueCountFrequency (%)
5
100.0%
Close Punctuation
ValueCountFrequency (%)
) 5
100.0%
Open Punctuation
ValueCountFrequency (%)
( 5
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 2043
99.3%
Common 15
 
0.7%

Most frequent character per script

Hangul
ValueCountFrequency (%)
김 108
 
5.3%
이 90
 
4.4%
정 81
 
4.0%
숙 63
 
3.1%
영 60
 
2.9%
희 51
 
2.5%
순 49
 
2.4%
경 45
 
2.2%
현 45
 
2.2%
최 41
 
2.0%
Other values (179) 1410
69.0%
Common
ValueCountFrequency (%)
5
33.3%
) 5
33.3%
( 5
33.3%

Most occurring blocks

ValueCountFrequency (%)
Hangul 2043
99.3%
ASCII 15
 
0.7%

Most frequent character per block

Hangul
ValueCountFrequency (%)
김 108
 
5.3%
이 90
 
4.4%
정 81
 
4.0%
숙 63
 
3.1%
영 60
 
2.9%
희 51
 
2.5%
순 49
 
2.4%
경 45
 
2.2%
현 45
 
2.2%
최 41
 
2.0%
Other values (179) 1410
69.0%
ASCII
ValueCountFrequency (%)
5
33.3%
) 5
33.3%
( 5
33.3%

Interactions

2023-12-12T17:48:08.665685image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T17:48:08.429361image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T17:48:08.761158image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T17:48:08.556561image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-12T17:48:16.389634image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
복지시설번호지역코드산호입소정원
복지시설번호1.0000.0000.0000.6620.108
지역코드0.0001.0000.0000.6290.677
산0.0000.0001.0000.0000.301
호0.6620.6290.0001.0000.000
입소정원0.1080.6770.3010.0001.000
2023-12-12T17:48:16.500819image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
통산복지시설번호반
통1.000NaNNaNNaN
산NaN1.0000.000NaN
복지시설번호NaN0.0001.000NaN
반NaNNaNNaN1.000
2023-12-12T17:48:16.618819image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
호입소정원복지시설번호산통반
호1.0000.0890.3480.000NaNNaN
입소정원0.0891.0000.0700.216NaNNaN
복지시설번호0.3480.0701.0000.000NaNNaN
산0.0000.2160.0001.000NaNNaN
통NaNNaNNaNNaN1.000NaN
반NaNNaNNaNNaNNaN1.000

Missing values

2023-12-12T17:48:08.933162image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-12T17:48:09.166868image/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.
2023-12-12T17:48:09.650944image/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

복지시설번호시설명지역코드산번지호통반시설전화번호설치일자입소정원시설대표자명
05.53E+15노랑단추어린이집기산동1466<NA><NA><NA>031 234 95672006-04-1830오석화
15.53E+15수직1리 경로당<NA>11104<NA><NA><NA>1996-01-1136박귀연
25.53E+15신성미소지움(A) 경로당<NA>1409<NA><NA><NA><NA>2006-05-1030황지순
35.53E+15화평수직경로대학제기리13571<NA><NA>031 354 39062006-05-2262(자)한국노인대학복지협의회 화평수직경로대학
45.53E+15해피아이어린이집기안동1290<NA><NA><NA>031 234 21992006-05-1715우정남
55.53E+15예솔아이어린이집병점동1520<NA><NA><NA><NA>2006-05-1715양근자
65.53E+15아이뜰어린이집진안동1911<NA><NA><NA>031 235 53732006-05-1917차성덕
75.53E+15한승영재어린이집송산동1222<NA><NA><NA>031 221 72222006-05-2326김순기
85.53E+15한승미메이드경로당송산동1222<NA><NA><NA><NA>2006-05-2220정만기
95.53E+15방교2리경로당<NA>16434<NA><NA>031 374 37302006-06-1223유춘산
복지시설번호시설명지역코드산번지호통반시설전화번호설치일자입소정원시설대표자명
6105.53E+15당하1리 경로당당하리11352<NA><NA><NA>1985-02-090홍성표
6115.53E+15하길3리 경로당<NA>13141<NA><NA><NA>2003-12-0128성화용
6125.53E+15신예은어린이집신리130432<NA><NA>031353 89422006-03-2039김현화
6135.53E+15월드메르디앙 아파트 1단지 경로당진안동1935<NA><NA><NA>031231 96592006-03-3040장인영
6145.53E+15장짐1리 경로당<NA>11112<NA><NA><NA>2003-02-2640예종칠
6155.53E+15하길2리 경로당<NA>12194<NA><NA><NA>2003-07-3049신춘식
6165.53E+15재크와콩나무 어린이집병점동1133<NA><NA><NA>031 226 56052006-04-0546안미영
6175.53E+15뉴질랜드 어린이집병점동1346-8<NA><NA><NA>031 222 72782006-03-2749이석준
6185.53E+15해바라기병점동1<NA><NA><NA><NA>031 890 00902006-04-1720이민영
6195.53E+15화성삼성어린이집반월동216<NA><NA><NA>031 208 32932006-04-19300삼성전자(주)

Duplicate rows

Most frequently occurring

복지시설번호시설명지역코드산번지호통반시설전화번호설치일자입소정원시설대표자명# duplicates
05.53E+15청덕동경로당<NA>15283<NA><NA><NA>2004-03-040박복희2
15.53E+15화산장수노인대학화산리1576<NA><NA><NA>031 358 17072005-04-07100조시현2