Overview

Dataset statistics

Number of variables11
Number of observations630
Missing cells304
Missing cells (%)4.4%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory56.1 KiB
Average record size in memory91.2 B

Variable types

Numeric3
Text4
Categorical4

Alerts

last_load_dttm has constant value ""Constant
s_gubun is highly overall correlated with s_codeHigh correlation
s_code is highly overall correlated with s_gubunHigh correlation
x is highly overall correlated with departHigh correlation
y is highly overall correlated with departHigh correlation
depart is highly overall correlated with x and 1 other fieldsHigh correlation
x has 152 (24.1%) missing valuesMissing
y has 152 (24.1%) missing valuesMissing
num has unique valuesUnique
mem has unique valuesUnique

Reproduction

Analysis started2024-04-17 02:22:19.395495
Analysis finished2024-04-17 02:22:20.911369
Duration1.52 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

num
Real number (ℝ)

UNIQUE 

Distinct630
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean315.5
Minimum1
Maximum630
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size5.7 KiB
2024-04-17T11:22:20.967523image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile32.45
Q1158.25
median315.5
Q3472.75
95-th percentile598.55
Maximum630
Range629
Interquartile range (IQR)314.5

Descriptive statistics

Standard deviation182.00962
Coefficient of variation (CV)0.5768926
Kurtosis-1.2
Mean315.5
Median Absolute Deviation (MAD)157.5
Skewness0
Sum198765
Variance33127.5
MonotonicityNot monotonic
2024-04-17T11:22:21.307767image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
564 1
 
0.2%
172 1
 
0.2%
165 1
 
0.2%
166 1
 
0.2%
167 1
 
0.2%
168 1
 
0.2%
169 1
 
0.2%
170 1
 
0.2%
171 1
 
0.2%
173 1
 
0.2%
Other values (620) 620
98.4%
ValueCountFrequency (%)
1 1
0.2%
2 1
0.2%
3 1
0.2%
4 1
0.2%
5 1
0.2%
6 1
0.2%
7 1
0.2%
8 1
0.2%
9 1
0.2%
10 1
0.2%
ValueCountFrequency (%)
630 1
0.2%
629 1
0.2%
628 1
0.2%
627 1
0.2%
626 1
0.2%
625 1
0.2%
624 1
0.2%
623 1
0.2%
622 1
0.2%
621 1
0.2%

name
Text

Distinct620
Distinct (%)98.4%
Missing0
Missing (%)0.0%
Memory size5.1 KiB
2024-04-17T11:22:21.506465image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length21
Median length18
Mean length8.8253968
Min length2

Characters and Unicode

Total characters5560
Distinct characters403
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

Unique612 ?
Unique (%)97.1%

Sample

1st row토마토아동발달예술심리센터
2nd row토마토지역사회서비스센터
3rd row통증없는바른몸지압원
4th row튼싹아동발달센터
5th row펀펀짐
ValueCountFrequency (%)
심리상담센터 7
 
0.9%
다온 5
 
0.7%
펀펀짐 4
 
0.5%
평생교육원 4
 
0.5%
킴즈포레교육원 3
 
0.4%
안마원 3
 
0.4%
리더스 3
 
0.4%
주식회사 3
 
0.4%
사회서비스센터 3
 
0.4%
산후도우미 3
 
0.4%
Other values (691) 719
95.0%
2024-04-17T11:22:21.817659image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
터 267
 
4.8%
센 265
 
4.8%
리 161
 
2.9%
지 161
 
2.9%
원 140
 
2.5%
127
 
2.3%
아 114
 
2.1%
마 113
 
2.0%
심 111
 
2.0%
사 103
 
1.9%
Other values (393) 3998
71.9%

Most occurring categories

ValueCountFrequency (%)
Other Letter 5308
95.5%
Space Separator 127
 
2.3%
Uppercase Letter 39
 
0.7%
Close Punctuation 29
 
0.5%
Open Punctuation 29
 
0.5%
Decimal Number 13
 
0.2%
Lowercase Letter 11
 
0.2%
Other Punctuation 4
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
터 267
 
5.0%
센 265
 
5.0%
리 161
 
3.0%
지 161
 
3.0%
원 140
 
2.6%
아 114
 
2.1%
마 113
 
2.1%
심 111
 
2.1%
사 103
 
1.9%
동 92
 
1.7%
Other values (356) 3781
71.2%
Uppercase Letter
ValueCountFrequency (%)
I 5
12.8%
M 5
12.8%
S 4
10.3%
A 3
 
7.7%
K 3
 
7.7%
C 3
 
7.7%
B 2
 
5.1%
T 2
 
5.1%
P 2
 
5.1%
J 2
 
5.1%
Other values (6) 8
20.5%
Decimal Number
ValueCountFrequency (%)
1 6
46.2%
9 3
23.1%
3 1
 
7.7%
4 1
 
7.7%
5 1
 
7.7%
7 1
 
7.7%
Lowercase Letter
ValueCountFrequency (%)
e 3
27.3%
i 3
27.3%
h 2
18.2%
t 1
 
9.1%
n 1
 
9.1%
d 1
 
9.1%
Other Punctuation
ValueCountFrequency (%)
/ 1
25.0%
· 1
25.0%
& 1
25.0%
: 1
25.0%
Close Punctuation
ValueCountFrequency (%)
) 28
96.6%
] 1
 
3.4%
Open Punctuation
ValueCountFrequency (%)
( 28
96.6%
[ 1
 
3.4%
Space Separator
ValueCountFrequency (%)
127
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 5308
95.5%
Common 202
 
3.6%
Latin 50
 
0.9%

Most frequent character per script

Hangul
ValueCountFrequency (%)
터 267
 
5.0%
센 265
 
5.0%
리 161
 
3.0%
지 161
 
3.0%
원 140
 
2.6%
아 114
 
2.1%
마 113
 
2.1%
심 111
 
2.1%
사 103
 
1.9%
동 92
 
1.7%
Other values (356) 3781
71.2%
Latin
ValueCountFrequency (%)
I 5
 
10.0%
M 5
 
10.0%
S 4
 
8.0%
A 3
 
6.0%
e 3
 
6.0%
i 3
 
6.0%
K 3
 
6.0%
C 3
 
6.0%
B 2
 
4.0%
T 2
 
4.0%
Other values (12) 17
34.0%
Common
ValueCountFrequency (%)
127
62.9%
) 28
 
13.9%
( 28
 
13.9%
1 6
 
3.0%
9 3
 
1.5%
3 1
 
0.5%
/ 1
 
0.5%
· 1
 
0.5%
& 1
 
0.5%
4 1
 
0.5%
Other values (5) 5
 
2.5%

Most occurring blocks

ValueCountFrequency (%)
Hangul 5308
95.5%
ASCII 251
 
4.5%
None 1
 
< 0.1%

Most frequent character per block

Hangul
ValueCountFrequency (%)
터 267
 
5.0%
센 265
 
5.0%
리 161
 
3.0%
지 161
 
3.0%
원 140
 
2.6%
아 114
 
2.1%
마 113
 
2.1%
심 111
 
2.1%
사 103
 
1.9%
동 92
 
1.7%
Other values (356) 3781
71.2%
ASCII
ValueCountFrequency (%)
127
50.6%
) 28
 
11.2%
( 28
 
11.2%
1 6
 
2.4%
I 5
 
2.0%
M 5
 
2.0%
S 4
 
1.6%
A 3
 
1.2%
9 3
 
1.2%
e 3
 
1.2%
Other values (26) 39
 
15.5%
None
ValueCountFrequency (%)
· 1
100.0%

mem
Text

UNIQUE 

Distinct630
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size5.1 KiB
2024-04-17T11:22:22.092499image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length5
Median length5
Mean length5
Min length5

Characters and Unicode

Total characters3150
Distinct characters12
Distinct categories2 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique630 ?
Unique (%)100.0%

Sample

1st rowk1014
2nd rowk0891
3rd rowk0103
4th rowk0916
5th rowk0839
ValueCountFrequency (%)
k1014 1
 
0.2%
k1073 1
 
0.2%
k0793 1
 
0.2%
k1045 1
 
0.2%
k0471 1
 
0.2%
k0066 1
 
0.2%
k0922 1
 
0.2%
k0192 1
 
0.2%
k0811 1
 
0.2%
k1059 1
 
0.2%
Other values (620) 620
98.4%
2024-04-17T11:22:22.465802image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 727
23.1%
k 630
20.0%
1 367
11.7%
7 196
 
6.2%
9 186
 
5.9%
2 182
 
5.8%
5 182
 
5.8%
8 174
 
5.5%
4 170
 
5.4%
6 170
 
5.4%
Other values (2) 166
 
5.3%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 2519
80.0%
Lowercase Letter 631
 
20.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 727
28.9%
1 367
14.6%
7 196
 
7.8%
9 186
 
7.4%
2 182
 
7.2%
5 182
 
7.2%
8 174
 
6.9%
4 170
 
6.7%
6 170
 
6.7%
3 165
 
6.6%
Lowercase Letter
ValueCountFrequency (%)
k 630
99.8%
o 1
 
0.2%

Most occurring scripts

ValueCountFrequency (%)
Common 2519
80.0%
Latin 631
 
20.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 727
28.9%
1 367
14.6%
7 196
 
7.8%
9 186
 
7.4%
2 182
 
7.2%
5 182
 
7.2%
8 174
 
6.9%
4 170
 
6.7%
6 170
 
6.7%
3 165
 
6.6%
Latin
ValueCountFrequency (%)
k 630
99.8%
o 1
 
0.2%

Most occurring blocks

ValueCountFrequency (%)
ASCII 3150
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 727
23.1%
k 630
20.0%
1 367
11.7%
7 196
 
6.2%
9 186
 
5.9%
2 182
 
5.8%
5 182
 
5.8%
8 174
 
5.5%
4 170
 
5.4%
6 170
 
5.4%
Other values (2) 166
 
5.3%

x
Real number (ℝ)

HIGH CORRELATION  MISSING 

Distinct454
Distinct (%)95.0%
Missing152
Missing (%)24.1%
Infinite0
Infinite (%)0.0%
Mean129.06404
Minimum128.8425
Maximum129.2352
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size5.7 KiB
2024-04-17T11:22:22.587306image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum128.8425
5-th percentile128.95713
Q1129.01689
median129.07415
Q3129.1059
95-th percentile129.17513
Maximum129.2352
Range0.39270548
Interquartile range (IQR)0.089007915

Descriptive statistics

Standard deviation0.067529295
Coefficient of variation (CV)0.00052322315
Kurtosis0.14610915
Mean129.06404
Median Absolute Deviation (MAD)0.040747817
Skewness-0.22615619
Sum61692.612
Variance0.0045602057
MonotonicityNot monotonic
2024-04-17T11:22:22.711452image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
128.92208896606314 3
 
0.5%
129.023827444118 2
 
0.3%
128.981788856844 2
 
0.3%
129.086227115795 2
 
0.3%
128.95718633868145 2
 
0.3%
129.093614415887 2
 
0.3%
129.1776796648616 2
 
0.3%
129.072226586557 2
 
0.3%
128.978056746847 2
 
0.3%
128.90405175182016 2
 
0.3%
Other values (444) 457
72.5%
(Missing) 152
 
24.1%
ValueCountFrequency (%)
128.842495700007 1
0.2%
128.87781291076843 1
0.2%
128.882372098998 1
0.2%
128.8973623855151 1
0.2%
128.9016895641785 1
0.2%
128.90298405919896 1
0.2%
128.90405175182016 2
0.3%
128.908565724208 1
0.2%
128.909237606778 1
0.2%
128.9178877245894 1
0.2%
ValueCountFrequency (%)
129.2352011778335 1
0.2%
129.222805630865 1
0.2%
129.218424384191 1
0.2%
129.2178933534697 1
0.2%
129.2169575291174 1
0.2%
129.21680184350737 1
0.2%
129.21627777733863 1
0.2%
129.21564245705255 1
0.2%
129.21528504388652 1
0.2%
129.214113798439 1
0.2%

y
Real number (ℝ)

HIGH CORRELATION  MISSING 

Distinct454
Distinct (%)95.0%
Missing152
Missing (%)24.1%
Infinite0
Infinite (%)0.0%
Mean35.171354
Minimum35.048771
Maximum35.33581
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size5.7 KiB
2024-04-17T11:22:22.831152image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum35.048771
5-th percentile35.091637
Q135.135479
median35.169399
Q335.203768
95-th percentile35.256854
Maximum35.33581
Range0.28703908
Interquartile range (IQR)0.068288653

Descriptive statistics

Standard deviation0.054938813
Coefficient of variation (CV)0.0015620329
Kurtosis0.36724084
Mean35.171354
Median Absolute Deviation (MAD)0.034007371
Skewness0.45231356
Sum16811.907
Variance0.0030182731
MonotonicityNot monotonic
2024-04-17T11:22:22.939596image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
35.09751481338803 3
 
0.5%
35.0962405987544 2
 
0.3%
35.1676936041364 2
 
0.3%
35.2402959450991 2
 
0.3%
35.0997143828983 2
 
0.3%
35.1224973584867 2
 
0.3%
35.16957635051104 2
 
0.3%
35.1658498304458 2
 
0.3%
35.1014662142321 2
 
0.3%
35.07990528476568 2
 
0.3%
Other values (444) 457
72.5%
(Missing) 152
 
24.1%
ValueCountFrequency (%)
35.0487712466506 1
0.2%
35.051021908881125 1
0.2%
35.05645947208821 1
0.2%
35.06177145514268 1
0.2%
35.06199868213317 1
0.2%
35.073083582942054 1
0.2%
35.07599639621529 1
0.2%
35.0772995308949 1
0.2%
35.0794385742764 1
0.2%
35.07990528476568 2
0.3%
ValueCountFrequency (%)
35.335810326089494 1
0.2%
35.335775777496536 1
0.2%
35.334493914407105 1
0.2%
35.32943691648715 1
0.2%
35.32655607038338 1
0.2%
35.3265546193691 1
0.2%
35.32635995230407 1
0.2%
35.325667061210574 1
0.2%
35.3224841048583 1
0.2%
35.32195584562486 1
0.2%

tel
Text

Distinct621
Distinct (%)98.6%
Missing0
Missing (%)0.0%
Memory size5.1 KiB
2024-04-17T11:22:23.164392image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length13
Median length12
Mean length12.080952
Min length12

Characters and Unicode

Total characters7611
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

Unique614 ?
Unique (%)97.5%

Sample

1st row051-626-6268
2nd row051-976-9669
3rd row051-544-9675
4th row051-755-9103
5th row051-292-7655
ValueCountFrequency (%)
051-756-2820 3
 
0.5%
051-208-1110 3
 
0.5%
051-513-9066 2
 
0.3%
051-711-0137 2
 
0.3%
010-5663-2901 2
 
0.3%
051-515-7200 2
 
0.3%
051-727-3712 2
 
0.3%
051-342-7942 1
 
0.2%
051-201-0440 1
 
0.2%
051-894-8103 1
 
0.2%
Other values (611) 611
97.0%
2024-04-17T11:22:23.503021image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
- 1260
16.6%
0 1159
15.2%
5 1153
15.1%
1 1012
13.3%
7 555
7.3%
2 536
7.0%
3 480
 
6.3%
6 401
 
5.3%
8 385
 
5.1%
9 335
 
4.4%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 6351
83.4%
Dash Punctuation 1260
 
16.6%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 1159
18.2%
5 1153
18.2%
1 1012
15.9%
7 555
8.7%
2 536
8.4%
3 480
7.6%
6 401
 
6.3%
8 385
 
6.1%
9 335
 
5.3%
4 335
 
5.3%
Dash Punctuation
ValueCountFrequency (%)
- 1260
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 7611
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
- 1260
16.6%
0 1159
15.2%
5 1153
15.1%
1 1012
13.3%
7 555
7.3%
2 536
7.0%
3 480
 
6.3%
6 401
 
5.3%
8 385
 
5.1%
9 335
 
4.4%

Most occurring blocks

ValueCountFrequency (%)
ASCII 7611
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
- 1260
16.6%
0 1159
15.2%
5 1153
15.1%
1 1012
13.3%
7 555
7.3%
2 536
7.0%
3 480
 
6.3%
6 401
 
5.3%
8 385
 
5.1%
9 335
 
4.4%

addr
Text

Distinct627
Distinct (%)99.5%
Missing0
Missing (%)0.0%
Memory size5.1 KiB
2024-04-17T11:22:23.782279image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length63
Median length47
Mean length32.463492
Min length16

Characters and Unicode

Total characters20452
Distinct characters375
Distinct categories11 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique624 ?
Unique (%)99.0%

Sample

1st row부산광역시 남구 용호로197번길 58 2층 202호 (용호동 굿모닝빌딩) 토마토아동발달예술심리센터
2nd row부산광역시 수영구 과정로 67 4층 (망미동)
3rd row부산 해운대구 아랫반송로 13-1 주민센타 맞은편 2층
4th row부산광역시 연제구 토곡남로 11 상가동 201호 (연산동 연산부전타워)
5th row부산광역시 사하구 괴정로270번길 29 2동 지하1층 (괴정동 괴정동신동화아파트)
ValueCountFrequency (%)
부산광역시 598
 
14.8%
2층 100
 
2.5%
3층 78
 
1.9%
해운대구 78
 
1.9%
부산진구 58
 
1.4%
북구 56
 
1.4%
4층 56
 
1.4%
동래구 53
 
1.3%
연제구 50
 
1.2%
사하구 47
 
1.2%
Other values (1311) 2858
70.9%
2024-04-17T11:22:24.183820image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
4028
 
19.7%
동 782
 
3.8%
산 756
 
3.7%
부 733
 
3.6%
1 667
 
3.3%
시 651
 
3.2%
구 642
 
3.1%
광 633
 
3.1%
역 599
 
2.9%
로 575
 
2.8%
Other values (365) 10386
50.8%

Most occurring categories

ValueCountFrequency (%)
Other Letter 11848
57.9%
Space Separator 4028
 
19.7%
Decimal Number 3370
 
16.5%
Open Punctuation 531
 
2.6%
Close Punctuation 529
 
2.6%
Dash Punctuation 104
 
0.5%
Uppercase Letter 29
 
0.1%
Control 7
 
< 0.1%
Other Punctuation 4
 
< 0.1%
Math Symbol 1
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
동 782
 
6.6%
산 756
 
6.4%
부 733
 
6.2%
시 651
 
5.5%
구 642
 
5.4%
광 633
 
5.3%
역 599
 
5.1%
로 575
 
4.9%
층 351
 
3.0%
대 325
 
2.7%
Other values (333) 5801
49.0%
Uppercase Letter
ValueCountFrequency (%)
B 6
20.7%
A 4
13.8%
S 4
13.8%
C 3
10.3%
K 3
10.3%
T 3
10.3%
I 2
 
6.9%
E 1
 
3.4%
Y 1
 
3.4%
P 1
 
3.4%
Decimal Number
ValueCountFrequency (%)
1 667
19.8%
2 538
16.0%
3 431
12.8%
0 377
11.2%
4 358
10.6%
5 287
8.5%
6 195
 
5.8%
7 183
 
5.4%
8 168
 
5.0%
9 166
 
4.9%
Open Punctuation
ValueCountFrequency (%)
( 530
99.8%
[ 1
 
0.2%
Close Punctuation
ValueCountFrequency (%)
) 528
99.8%
] 1
 
0.2%
Other Punctuation
ValueCountFrequency (%)
. 3
75.0%
/ 1
 
25.0%
Space Separator
ValueCountFrequency (%)
4028
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 104
100.0%
Control
ValueCountFrequency (%)
7
100.0%
Math Symbol
ValueCountFrequency (%)
~ 1
100.0%
Lowercase Letter
ValueCountFrequency (%)
b 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 11848
57.9%
Common 8574
41.9%
Latin 30
 
0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
동 782
 
6.6%
산 756
 
6.4%
부 733
 
6.2%
시 651
 
5.5%
구 642
 
5.4%
광 633
 
5.3%
역 599
 
5.1%
로 575
 
4.9%
층 351
 
3.0%
대 325
 
2.7%
Other values (333) 5801
49.0%
Common
ValueCountFrequency (%)
4028
47.0%
1 667
 
7.8%
2 538
 
6.3%
( 530
 
6.2%
) 528
 
6.2%
3 431
 
5.0%
0 377
 
4.4%
4 358
 
4.2%
5 287
 
3.3%
6 195
 
2.3%
Other values (10) 635
 
7.4%
Latin
ValueCountFrequency (%)
B 6
20.0%
A 4
13.3%
S 4
13.3%
C 3
10.0%
K 3
10.0%
T 3
10.0%
I 2
 
6.7%
E 1
 
3.3%
Y 1
 
3.3%
P 1
 
3.3%
Other values (2) 2
 
6.7%

Most occurring blocks

ValueCountFrequency (%)
Hangul 11848
57.9%
ASCII 8604
42.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
4028
46.8%
1 667
 
7.8%
2 538
 
6.3%
( 530
 
6.2%
) 528
 
6.1%
3 431
 
5.0%
0 377
 
4.4%
4 358
 
4.2%
5 287
 
3.3%
6 195
 
2.3%
Other values (22) 665
 
7.7%
Hangul
ValueCountFrequency (%)
동 782
 
6.6%
산 756
 
6.4%
부 733
 
6.2%
시 651
 
5.5%
구 642
 
5.4%
광 633
 
5.3%
역 599
 
5.1%
로 575
 
4.9%
층 351
 
3.0%
대 325
 
2.7%
Other values (333) 5801
49.0%

depart
Categorical

HIGH CORRELATION 

Distinct16
Distinct (%)2.5%
Missing0
Missing (%)0.0%
Memory size5.1 KiB
해운대구
78 
부산진구
57 
북구
55 
동래구
53 
연제구
50 
Other values (11)
337 

Length

Max length4
Median length3
Mean length2.9793651
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row남구
2nd row수영구
3rd row해운대구
4th row연제구
5th row사하구

Common Values

ValueCountFrequency (%)
해운대구 78
12.4%
부산진구 57
9.0%
북구 55
8.7%
동래구 53
8.4%
연제구 50
 
7.9%
사하구 47
 
7.5%
남구 45
 
7.1%
금정구 41
 
6.5%
수영구 39
 
6.2%
사상구 36
 
5.7%
Other values (6) 129
20.5%

Length

2024-04-17T11:22:24.308265image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
해운대구 78
12.4%
부산진구 57
9.0%
북구 55
8.7%
동래구 53
8.4%
연제구 50
 
7.9%
사하구 47
 
7.5%
남구 45
 
7.1%
금정구 41
 
6.5%
수영구 39
 
6.2%
사상구 36
 
5.7%
Other values (6) 129
20.5%

s_gubun
Categorical

HIGH CORRELATION 

Distinct6
Distinct (%)1.0%
Missing0
Missing (%)0.0%
Memory size5.1 KiB
청소년아동,
369 
노인,
141 
성인가족,
55 
아동,
37 
<NA>
 
24

Length

Max length9
Median length6
Mean length5.0079365
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row청소년아동,
2nd row청소년아동,
3rd row노인,
4th row청소년아동,
5th row아동,

Common Values

ValueCountFrequency (%)
청소년아동, 369
58.6%
노인, 141
 
22.4%
성인가족, 55
 
8.7%
아동, 37
 
5.9%
<NA> 24
 
3.8%
청소년아동장애인, 4
 
0.6%

Length

2024-04-17T11:22:24.414433image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T11:22:24.506393image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
청소년아동 369
58.6%
노인 141
 
22.4%
성인가족 55
 
8.7%
아동 37
 
5.9%
na 24
 
3.8%
청소년아동장애인 4
 
0.6%

s_code
Categorical

HIGH CORRELATION 

Distinct17
Distinct (%)2.7%
Missing0
Missing (%)0.0%
Memory size5.1 KiB
아동청소년심리치유서비스(우리아이가달라졌어요!)
324 
시각장애인 안마서비스
97 
산모신생아건강관리지원사업
47 
아동건강관리서비스
37 
노인건강관리서비스
 
27
Other values (12)
98 

Length

Max length26
Median length25
Mean length18.549206
Min length7

Unique

Unique5 ?
Unique (%)0.8%

Sample

1st row아동청소년심리치유서비스(우리아이가달라졌어요!)
2nd row아동청소년심리치유서비스(우리아이가달라졌어요!)
3rd row시각장애인 안마서비스
4th row아동청소년심리치유서비스(우리아이가달라졌어요!)
5th row아동건강관리서비스

Common Values

ValueCountFrequency (%)
아동청소년심리치유서비스(우리아이가달라졌어요!) 324
51.4%
시각장애인 안마서비스 97
 
15.4%
산모신생아건강관리지원사업 47
 
7.5%
아동건강관리서비스 37
 
5.9%
노인건강관리서비스 27
 
4.3%
동화야 놀~자(스토리텔링) 25
 
4.0%
가사간병 방문 지원사업 22
 
3.5%
뇌에 기(氣)가 팍팍 16
 
2.5%
아동정서발달지원서비스 10
 
1.6%
자녀의 성공을 돕는 부모코칭(키울 MOM난다!) 8
 
1.3%
Other values (7) 17
 
2.7%

Length

2024-04-17T11:22:24.610964image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
아동청소년심리치유서비스(우리아이가달라졌어요 324
36.6%
안마서비스 97
 
11.0%
시각장애인 97
 
11.0%
산모신생아건강관리지원사업 47
 
5.3%
아동건강관리서비스 37
 
4.2%
노인건강관리서비스 27
 
3.1%
동화야 25
 
2.8%
놀~자(스토리텔링 25
 
2.8%
가사간병 22
 
2.5%
지원사업 22
 
2.5%
Other values (29) 162
18.3%

last_load_dttm
Categorical

CONSTANT 

Distinct1
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size5.1 KiB
2021-05-01 05:35:03
630 

Length

Max length19
Median length19
Mean length19
Min length19

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row2021-05-01 05:35:03
2nd row2021-05-01 05:35:03
3rd row2021-05-01 05:35:03
4th row2021-05-01 05:35:03
5th row2021-05-01 05:35:03

Common Values

ValueCountFrequency (%)
2021-05-01 05:35:03 630
100.0%

Length

2024-04-17T11:22:24.712409image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T11:22:24.790946image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2021-05-01 630
50.0%
05:35:03 630
50.0%

Interactions

2024-04-17T11:22:20.411658image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T11:22:19.952367image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T11:22:20.180730image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T11:22:20.483869image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T11:22:20.023025image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T11:22:20.253313image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T11:22:20.562756image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T11:22:20.105266image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T11:22:20.332772image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-04-17T11:22:24.838207image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
numxydeparts_gubuns_code
num1.0000.2620.0840.1750.2510.220
x0.2621.0000.6630.8970.1590.000
y0.0840.6631.0000.8890.1370.000
depart0.1750.8970.8891.0000.2170.101
s_gubun0.2510.1590.1370.2171.0001.000
s_code0.2200.0000.0000.1011.0001.000
2024-04-17T11:22:24.918231image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
departs_gubuns_code
depart1.0000.1110.032
s_gubun0.1111.0000.992
s_code0.0320.9921.000
2024-04-17T11:22:25.000734image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
numxydeparts_gubuns_code
num1.0000.031-0.0110.0690.1060.086
x0.0311.0000.4960.6360.0780.000
y-0.0110.4961.0000.6380.0790.000
depart0.0690.6360.6381.0000.1110.032
s_gubun0.1060.0780.0790.1111.0000.992
s_code0.0860.0000.0000.0320.9921.000

Missing values

2024-04-17T11:22:20.661774image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-04-17T11:22:20.788782image/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.
2024-04-17T11:22:20.871539image/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

numnamememxyteladdrdeparts_gubuns_codelast_load_dttm
0564토마토아동발달예술심리센터k1014129.11427835.114623051-626-6268부산광역시 남구 용호로197번길 58 2층 202호 (용호동 굿모닝빌딩) 토마토아동발달예술심리센터남구청소년아동,아동청소년심리치유서비스(우리아이가달라졌어요!)2021-05-01 05:35:03
1565토마토지역사회서비스센터k0891129.10705135.17735051-976-9669부산광역시 수영구 과정로 67 4층 (망미동)수영구청소년아동,아동청소년심리치유서비스(우리아이가달라졌어요!)2021-05-01 05:35:03
2566통증없는바른몸지압원k0103129.14765735.225569051-544-9675부산 해운대구 아랫반송로 13-1 주민센타 맞은편 2층해운대구노인,시각장애인 안마서비스2021-05-01 05:35:03
3567튼싹아동발달센터k0916129.10580935.180908051-755-9103부산광역시 연제구 토곡남로 11 상가동 201호 (연산동 연산부전타워)연제구청소년아동,아동청소년심리치유서비스(우리아이가달라졌어요!)2021-05-01 05:35:03
4568펀펀짐k0839<NA><NA>051-292-7655부산광역시 사하구 괴정로270번길 29 2동 지하1층 (괴정동 괴정동신동화아파트)사하구아동,아동건강관리서비스2021-05-01 05:35:03
5569펀펀짐k0973128.92310535.096702051-205-7655부산광역시 강서구 명지국제6로 238 (명지동 가온프라자 4층)강서구아동,아동건강관리서비스2021-05-01 05:35:03
6570펀펀짐k1087129.08660635.192966051-868-6115부산광역시 연제구 거제천로255번가길 31 지하1층 (거제동)연제구아동,아동건강관리서비스2021-05-01 05:35:03
7571펀펀짐 해운대점k1082129.12341335.208497051-532-9334부산광역시 해운대구 선수촌로 175 3층 (반여동)해운대구아동,아동건강관리서비스2021-05-01 05:35:03
8572포레뮤직(피아노연구소)k0737128.92208935.097515051-202-6808부산광역시 강서구 명지국제8로 270 8층 803호 (명지동 모아진빌딩)강서구청소년아동,동화야 놀~자(스토리텔링)2021-05-01 05:35:03
9573포레스트아동가족상담k0996129.06664535.19178051-501-0066부산광역시 연제구 여고로14번길 73-1 (거제동)연제구청소년아동,아동청소년심리치유서비스(우리아이가달라졌어요!)2021-05-01 05:35:03
numnamememxyteladdrdeparts_gubuns_codelast_load_dttm
620621화정종합사회복지관k0030129.01538935.253642051-362-0111부산광역시 북구 효열로 76 (금곡동 화정종합사회복지관)북구청소년아동,아동청소년심리치유서비스(우리아이가달라졌어요!)2021-05-01 05:35:03
621622효녀심청 사회서비스센터k0081<NA><NA>051-552-5557부산광역시 동래구 사직동 석사로 18번길 41 망고키즈수영장 2층 [효녀심청사회서비스센터]동래구노인,노인건강관리서비스2021-05-01 05:35:03
622623효사랑안마지압원k0698128.98534335.098723051-205-3331부산광역시 사하구 장평로449번길 26 1층 상가101호 (괴정동 천아하늘정원2차아파트)사하구노인,시각장애인 안마서비스2021-05-01 05:35:03
623624휴먼리더스k0978<NA><NA>051-610-0606부산광역시 남구 수영로 312 1202호 (대연동 21 센츄리시티 오피스텔)남구청소년아동,해양역사문화체험 아카데미2021-05-01 05:35:03
624625휴먼비전사회적협동조합k0594<NA><NA>051-904-9882부산광역시 해운대구 센텀동로 99 1503호 (재송동 벽산센텀이클래스원1차)해운대구청소년아동,해양역사문화체험 아카데미2021-05-01 05:35:03
625626희망그루터기사회서비스센터k0346129.08560735.238019051-516-1070부산 금정구 금강로335번길 16 장전동금정구청소년아동,아동청소년심리치유서비스(우리아이가달라졌어요!)2021-05-01 05:35:03
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