Overview

Dataset statistics

Number of variables11
Number of observations555
Missing cells278
Missing cells (%)4.6%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory49.5 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 139 (25.0%) missing valuesMissing
y has 139 (25.0%) missing valuesMissing
num has unique valuesUnique
mem has unique valuesUnique

Reproduction

Analysis started2024-04-17 02:22:33.187472
Analysis finished2024-04-17 02:22:34.650223
Duration1.46 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

num
Real number (ℝ)

UNIQUE 

Distinct555
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean278
Minimum1
Maximum555
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size5.0 KiB
2024-04-17T11:22:34.701330image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile28.7
Q1139.5
median278
Q3416.5
95-th percentile527.3
Maximum555
Range554
Interquartile range (IQR)277

Descriptive statistics

Standard deviation160.35897
Coefficient of variation (CV)0.57683084
Kurtosis-1.2
Mean278
Median Absolute Deviation (MAD)139
Skewness0
Sum154290
Variance25715
MonotonicityNot monotonic
2024-04-17T11:22:34.808041image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
507 1
 
0.2%
176 1
 
0.2%
170 1
 
0.2%
171 1
 
0.2%
172 1
 
0.2%
173 1
 
0.2%
174 1
 
0.2%
175 1
 
0.2%
177 1
 
0.2%
185 1
 
0.2%
Other values (545) 545
98.2%
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 (%)
555 1
0.2%
554 1
0.2%
553 1
0.2%
552 1
0.2%
551 1
0.2%
550 1
0.2%
549 1
0.2%
548 1
0.2%
547 1
0.2%
546 1
0.2%

name
Text

Distinct545
Distinct (%)98.2%
Missing0
Missing (%)0.0%
Memory size4.5 KiB
2024-04-17T11:22:34.988931image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length21
Median length18
Mean length8.8702703
Min length2

Characters and Unicode

Total characters4923
Distinct characters382
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

Unique537 ?
Unique (%)96.8%

Sample

1st row플로리시언어&상담센터
2nd row피아니스트노부스
3rd row하단창의숲
4th row하담아동발달센터
5th row하엘아동발달센터
ValueCountFrequency (%)
심리상담센터 6
 
0.9%
평생교육원 4
 
0.6%
펀펀짐 4
 
0.6%
킴즈포레교육원 3
 
0.5%
산학협력단 3
 
0.5%
안마지압원 3
 
0.5%
리더스 3
 
0.5%
사회서비스센터 3
 
0.5%
사단법인 3
 
0.5%
안마원 3
 
0.5%
Other values (602) 616
94.6%
2024-04-17T11:22:35.279117image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
센 240
 
4.9%
터 239
 
4.9%
리 152
 
3.1%
지 134
 
2.7%
원 134
 
2.7%
심 110
 
2.2%
마 102
 
2.1%
아 100
 
2.0%
96
 
2.0%
사 91
 
1.8%
Other values (372) 3525
71.6%

Most occurring categories

ValueCountFrequency (%)
Other Letter 4720
95.9%
Space Separator 96
 
2.0%
Uppercase Letter 36
 
0.7%
Close Punctuation 25
 
0.5%
Open Punctuation 25
 
0.5%
Lowercase Letter 11
 
0.2%
Decimal Number 7
 
0.1%
Other Punctuation 3
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
센 240
 
5.1%
터 239
 
5.1%
리 152
 
3.2%
지 134
 
2.8%
원 134
 
2.8%
심 110
 
2.3%
마 102
 
2.2%
아 100
 
2.1%
사 91
 
1.9%
상 89
 
1.9%
Other values (337) 3329
70.5%
Uppercase Letter
ValueCountFrequency (%)
I 5
13.9%
M 4
11.1%
S 4
11.1%
C 3
8.3%
A 3
8.3%
K 3
8.3%
P 2
 
5.6%
B 2
 
5.6%
E 2
 
5.6%
J 2
 
5.6%
Other values (5) 6
16.7%
Lowercase Letter
ValueCountFrequency (%)
e 3
27.3%
i 3
27.3%
h 2
18.2%
n 1
 
9.1%
d 1
 
9.1%
t 1
 
9.1%
Decimal Number
ValueCountFrequency (%)
1 2
28.6%
9 1
14.3%
3 1
14.3%
7 1
14.3%
5 1
14.3%
4 1
14.3%
Other Punctuation
ValueCountFrequency (%)
& 1
33.3%
· 1
33.3%
: 1
33.3%
Close Punctuation
ValueCountFrequency (%)
) 24
96.0%
] 1
 
4.0%
Open Punctuation
ValueCountFrequency (%)
( 24
96.0%
[ 1
 
4.0%
Space Separator
ValueCountFrequency (%)
96
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 4720
95.9%
Common 156
 
3.2%
Latin 47
 
1.0%

Most frequent character per script

Hangul
ValueCountFrequency (%)
센 240
 
5.1%
터 239
 
5.1%
리 152
 
3.2%
지 134
 
2.8%
원 134
 
2.8%
심 110
 
2.3%
마 102
 
2.2%
아 100
 
2.1%
사 91
 
1.9%
상 89
 
1.9%
Other values (337) 3329
70.5%
Latin
ValueCountFrequency (%)
I 5
 
10.6%
M 4
 
8.5%
S 4
 
8.5%
C 3
 
6.4%
A 3
 
6.4%
e 3
 
6.4%
i 3
 
6.4%
K 3
 
6.4%
h 2
 
4.3%
P 2
 
4.3%
Other values (11) 15
31.9%
Common
ValueCountFrequency (%)
96
61.5%
) 24
 
15.4%
( 24
 
15.4%
1 2
 
1.3%
& 1
 
0.6%
[ 1
 
0.6%
· 1
 
0.6%
9 1
 
0.6%
: 1
 
0.6%
] 1
 
0.6%
Other values (4) 4
 
2.6%

Most occurring blocks

ValueCountFrequency (%)
Hangul 4720
95.9%
ASCII 202
 
4.1%
None 1
 
< 0.1%

Most frequent character per block

Hangul
ValueCountFrequency (%)
센 240
 
5.1%
터 239
 
5.1%
리 152
 
3.2%
지 134
 
2.8%
원 134
 
2.8%
심 110
 
2.3%
마 102
 
2.2%
아 100
 
2.1%
사 91
 
1.9%
상 89
 
1.9%
Other values (337) 3329
70.5%
ASCII
ValueCountFrequency (%)
96
47.5%
) 24
 
11.9%
( 24
 
11.9%
I 5
 
2.5%
M 4
 
2.0%
S 4
 
2.0%
C 3
 
1.5%
A 3
 
1.5%
e 3
 
1.5%
i 3
 
1.5%
Other values (24) 33
 
16.3%
None
ValueCountFrequency (%)
· 1
100.0%

mem
Text

UNIQUE 

Distinct555
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size4.5 KiB
2024-04-17T11:22:35.544780image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length5
Median length5
Mean length5
Min length5

Characters and Unicode

Total characters2775
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

Unique555 ?
Unique (%)100.0%

Sample

1st rowk0738
2nd rowk1091
3rd rowk0525
4th rowk0697
5th rowk0130
ValueCountFrequency (%)
k0738 1
 
0.2%
k0914 1
 
0.2%
k1105 1
 
0.2%
k1011 1
 
0.2%
k0934 1
 
0.2%
k0933 1
 
0.2%
k0932 1
 
0.2%
k0957 1
 
0.2%
k0795 1
 
0.2%
k0935 1
 
0.2%
Other values (545) 545
98.2%
2024-04-17T11:22:35.909593image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 665
24.0%
k 555
20.0%
1 289
10.4%
7 173
 
6.2%
9 172
 
6.2%
2 167
 
6.0%
5 161
 
5.8%
8 155
 
5.6%
4 147
 
5.3%
3 145
 
5.2%
Other values (2) 146
 
5.3%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 2219
80.0%
Lowercase Letter 556
 
20.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 665
30.0%
1 289
13.0%
7 173
 
7.8%
9 172
 
7.8%
2 167
 
7.5%
5 161
 
7.3%
8 155
 
7.0%
4 147
 
6.6%
3 145
 
6.5%
6 145
 
6.5%
Lowercase Letter
ValueCountFrequency (%)
k 555
99.8%
o 1
 
0.2%

Most occurring scripts

ValueCountFrequency (%)
Common 2219
80.0%
Latin 556
 
20.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 665
30.0%
1 289
13.0%
7 173
 
7.8%
9 172
 
7.8%
2 167
 
7.5%
5 161
 
7.3%
8 155
 
7.0%
4 147
 
6.6%
3 145
 
6.5%
6 145
 
6.5%
Latin
ValueCountFrequency (%)
k 555
99.8%
o 1
 
0.2%

Most occurring blocks

ValueCountFrequency (%)
ASCII 2775
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 665
24.0%
k 555
20.0%
1 289
10.4%
7 173
 
6.2%
9 172
 
6.2%
2 167
 
6.0%
5 161
 
5.8%
8 155
 
5.6%
4 147
 
5.3%
3 145
 
5.2%
Other values (2) 146
 
5.3%

x
Real number (ℝ)

HIGH CORRELATION  MISSING 

Distinct396
Distinct (%)95.2%
Missing139
Missing (%)25.0%
Infinite0
Infinite (%)0.0%
Mean129.06502
Minimum128.87781
Maximum129.2352
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size5.0 KiB
2024-04-17T11:22:36.026819image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum128.87781
5-th percentile128.95872
Q1129.01714
median129.07502
Q3129.10595
95-th percentile129.17509
Maximum129.2352
Range0.35738827
Interquartile range (IQR)0.088806398

Descriptive statistics

Standard deviation0.065514481
Coefficient of variation (CV)0.00050760834
Kurtosis0.038856046
Mean129.06502
Median Absolute Deviation (MAD)0.040441281
Skewness-0.14869876
Sum53691.049
Variance0.0042921473
MonotonicityNot monotonic
2024-04-17T11:22:36.371357image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
128.92208896606314 3
 
0.5%
129.093614415887 2
 
0.4%
129.08127824526937 2
 
0.4%
129.00868706249742 2
 
0.4%
129.0790882928673 2
 
0.4%
129.086227115795 2
 
0.4%
129.072226586557 2
 
0.4%
129.10062174337517 2
 
0.4%
129.0762189938991 2
 
0.4%
129.1776796648616 2
 
0.4%
Other values (386) 395
71.2%
(Missing) 139
 
25.0%
ValueCountFrequency (%)
128.87781291076843 1
0.2%
128.8973623855151 1
0.2%
128.9016895641785 1
0.2%
128.90298405919896 1
0.2%
128.909237606778 1
0.2%
128.9178877245894 1
0.2%
128.91800907742393 1
0.2%
128.91838738818112 1
0.2%
128.91860368470296 1
0.2%
128.9198337080121 1
0.2%
ValueCountFrequency (%)
129.2352011778335 1
0.2%
129.222805630865 1
0.2%
129.2178933534697 1
0.2%
129.2169575291174 1
0.2%
129.21680184350737 1
0.2%
129.21627777733863 1
0.2%
129.21528504388652 1
0.2%
129.214113798439 1
0.2%
129.212584343816 1
0.2%
129.19705513883454 1
0.2%

y
Real number (ℝ)

HIGH CORRELATION  MISSING 

Distinct396
Distinct (%)95.2%
Missing139
Missing (%)25.0%
Infinite0
Infinite (%)0.0%
Mean35.173011
Minimum35.048771
Maximum35.33581
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size5.0 KiB
2024-04-17T11:22:36.480080image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum35.048771
5-th percentile35.093952
Q135.136979
median35.171643
Q335.204002
95-th percentile35.257436
Maximum35.33581
Range0.28703908
Interquartile range (IQR)0.067023536

Descriptive statistics

Standard deviation0.054402295
Coefficient of variation (CV)0.0015467056
Kurtosis0.41513475
Mean35.173011
Median Absolute Deviation (MAD)0.03346726
Skewness0.45589653
Sum14631.973
Variance0.0029596097
MonotonicityNot monotonic
2024-04-17T11:22:36.592223image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
35.09751481338803 3
 
0.5%
35.1224973584867 2
 
0.4%
35.20547596521364 2
 
0.4%
35.19427357851371 2
 
0.4%
35.141243127174015 2
 
0.4%
35.2402959450991 2
 
0.4%
35.1658498304458 2
 
0.4%
35.13697860996388 2
 
0.4%
35.181325409865714 2
 
0.4%
35.16957635051104 2
 
0.4%
Other values (386) 395
71.2%
(Missing) 139
 
25.0%
ValueCountFrequency (%)
35.0487712466506 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%
35.0799666865452 1
0.2%
35.08012486245978 1
0.2%
35.08159279172671 1
0.2%
35.08277456588757 1
0.2%
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

Distinct551
Distinct (%)99.3%
Missing0
Missing (%)0.0%
Memory size4.5 KiB
2024-04-17T11:22:36.794373image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length13
Median length12
Mean length12.079279
Min length12

Characters and Unicode

Total characters6704
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

Unique548 ?
Unique (%)98.7%

Sample

1st row051-758-7942
2nd row010-5575-1524
3rd row051-201-5459
4th row051-201-0075
5th row051-337-7562
ValueCountFrequency (%)
051-208-1110 3
 
0.5%
051-711-0137 2
 
0.4%
051-515-7200 2
 
0.4%
051-521-7100 1
 
0.2%
051-418-8566 1
 
0.2%
051-703-3636 1
 
0.2%
051-514-0437 1
 
0.2%
051-202-7570 1
 
0.2%
051-206-4778 1
 
0.2%
051-868-6477 1
 
0.2%
Other values (541) 541
97.5%
2024-04-17T11:22:37.097266image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
- 1110
16.6%
0 1032
15.4%
5 998
14.9%
1 896
13.4%
7 501
7.5%
2 459
6.8%
3 412
 
6.1%
6 365
 
5.4%
8 336
 
5.0%
9 303
 
4.5%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 5594
83.4%
Dash Punctuation 1110
 
16.6%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 1032
18.4%
5 998
17.8%
1 896
16.0%
7 501
9.0%
2 459
8.2%
3 412
 
7.4%
6 365
 
6.5%
8 336
 
6.0%
9 303
 
5.4%
4 292
 
5.2%
Dash Punctuation
ValueCountFrequency (%)
- 1110
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 6704
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
- 1110
16.6%
0 1032
15.4%
5 998
14.9%
1 896
13.4%
7 501
7.5%
2 459
6.8%
3 412
 
6.1%
6 365
 
5.4%
8 336
 
5.0%
9 303
 
4.5%

Most occurring blocks

ValueCountFrequency (%)
ASCII 6704
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
- 1110
16.6%
0 1032
15.4%
5 998
14.9%
1 896
13.4%
7 501
7.5%
2 459
6.8%
3 412
 
6.1%
6 365
 
5.4%
8 336
 
5.0%
9 303
 
4.5%

addr
Text

Distinct553
Distinct (%)99.6%
Missing0
Missing (%)0.0%
Memory size4.5 KiB
2024-04-17T11:22:37.393738image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length63
Median length46
Mean length32.437838
Min length16

Characters and Unicode

Total characters18003
Distinct characters367
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

Unique551 ?
Unique (%)99.3%

Sample

1st row부산광역시 수영구 망미번영로52번길 59 (수영동)
2nd row부산광역시 서구 대티로 159 (서대신동3가 협성르네상스. 117-306)
3rd row부산광역시 사하구 하신번영로 326 2층 (하단동)
4th row부산광역시 사하구 낙동대로 271 105호 (괴정동 신동양상가)
5th row부산광역시 북구 덕천동 만덕대로 126 흥산빌딜 6층
ValueCountFrequency (%)
부산광역시 526
 
14.9%
2층 91
 
2.6%
3층 70
 
2.0%
해운대구 69
 
1.9%
북구 52
 
1.5%
부산진구 50
 
1.4%
4층 49
 
1.4%
동래구 48
 
1.4%
연제구 44
 
1.2%
남구 39
 
1.1%
Other values (1180) 2503
70.7%
2024-04-17T11:22:37.819684image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
3528
 
19.6%
동 684
 
3.8%
산 665
 
3.7%
부 643
 
3.6%
시 575
 
3.2%
구 571
 
3.2%
1 569
 
3.2%
광 560
 
3.1%
역 527
 
2.9%
로 505
 
2.8%
Other values (357) 9176
51.0%

Most occurring categories

ValueCountFrequency (%)
Other Letter 10478
58.2%
Space Separator 3528
 
19.6%
Decimal Number 2943
 
16.3%
Open Punctuation 466
 
2.6%
Close Punctuation 464
 
2.6%
Dash Punctuation 90
 
0.5%
Uppercase Letter 21
 
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 684
 
6.5%
산 665
 
6.3%
부 643
 
6.1%
시 575
 
5.5%
구 571
 
5.4%
광 560
 
5.3%
역 527
 
5.0%
로 505
 
4.8%
층 311
 
3.0%
대 284
 
2.7%
Other values (325) 5153
49.2%
Uppercase Letter
ValueCountFrequency (%)
B 5
23.8%
A 3
14.3%
S 3
14.3%
T 2
 
9.5%
C 2
 
9.5%
P 1
 
4.8%
K 1
 
4.8%
Y 1
 
4.8%
E 1
 
4.8%
I 1
 
4.8%
Decimal Number
ValueCountFrequency (%)
1 569
19.3%
2 486
16.5%
3 365
12.4%
0 331
11.2%
4 320
10.9%
5 249
8.5%
6 167
 
5.7%
7 161
 
5.5%
8 150
 
5.1%
9 145
 
4.9%
Open Punctuation
ValueCountFrequency (%)
( 465
99.8%
[ 1
 
0.2%
Close Punctuation
ValueCountFrequency (%)
) 463
99.8%
] 1
 
0.2%
Other Punctuation
ValueCountFrequency (%)
. 3
75.0%
/ 1
 
25.0%
Space Separator
ValueCountFrequency (%)
3528
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 90
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 10478
58.2%
Common 7503
41.7%
Latin 22
 
0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
동 684
 
6.5%
산 665
 
6.3%
부 643
 
6.1%
시 575
 
5.5%
구 571
 
5.4%
광 560
 
5.3%
역 527
 
5.0%
로 505
 
4.8%
층 311
 
3.0%
대 284
 
2.7%
Other values (325) 5153
49.2%
Common
ValueCountFrequency (%)
3528
47.0%
1 569
 
7.6%
2 486
 
6.5%
( 465
 
6.2%
) 463
 
6.2%
3 365
 
4.9%
0 331
 
4.4%
4 320
 
4.3%
5 249
 
3.3%
6 167
 
2.2%
Other values (10) 560
 
7.5%
Latin
ValueCountFrequency (%)
B 5
22.7%
A 3
13.6%
S 3
13.6%
T 2
 
9.1%
C 2
 
9.1%
P 1
 
4.5%
K 1
 
4.5%
Y 1
 
4.5%
E 1
 
4.5%
I 1
 
4.5%
Other values (2) 2
 
9.1%

Most occurring blocks

ValueCountFrequency (%)
Hangul 10478
58.2%
ASCII 7525
41.8%

Most frequent character per block

ASCII
ValueCountFrequency (%)
3528
46.9%
1 569
 
7.6%
2 486
 
6.5%
( 465
 
6.2%
) 463
 
6.2%
3 365
 
4.9%
0 331
 
4.4%
4 320
 
4.3%
5 249
 
3.3%
6 167
 
2.2%
Other values (22) 582
 
7.7%
Hangul
ValueCountFrequency (%)
동 684
 
6.5%
산 665
 
6.3%
부 643
 
6.1%
시 575
 
5.5%
구 571
 
5.4%
광 560
 
5.3%
역 527
 
5.0%
로 505
 
4.8%
층 311
 
3.0%
대 284
 
2.7%
Other values (325) 5153
49.2%

depart
Categorical

HIGH CORRELATION 

Distinct16
Distinct (%)2.9%
Missing0
Missing (%)0.0%
Memory size4.5 KiB
해운대구
69 
북구
51 
부산진구
49 
동래구
48 
연제구
44 
Other values (11)
294 

Length

Max length4
Median length3
Mean length2.9747748
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row수영구
2nd row서구
3rd row사하구
4th row사하구
5th row북구

Common Values

ValueCountFrequency (%)
해운대구 69
12.4%
북구 51
9.2%
부산진구 49
8.8%
동래구 48
8.6%
연제구 44
7.9%
남구 39
 
7.0%
사하구 38
 
6.8%
금정구 38
 
6.8%
수영구 35
 
6.3%
사상구 35
 
6.3%
Other values (6) 109
19.6%

Length

2024-04-17T11:22:37.933930image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
해운대구 69
12.4%
북구 51
9.2%
부산진구 49
8.8%
동래구 48
8.6%
연제구 44
7.9%
남구 39
 
7.0%
사하구 38
 
6.8%
금정구 38
 
6.8%
수영구 35
 
6.3%
사상구 35
 
6.3%
Other values (6) 109
19.6%

s_gubun
Categorical

HIGH CORRELATION 

Distinct6
Distinct (%)1.1%
Missing0
Missing (%)0.0%
Memory size4.5 KiB
청소년아동,
369 
노인,
139 
아동,
 
35
성인가족,
 
7
청소년아동장애인,
 
3

Length

Max length9
Median length6
Mean length5.0558559
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
청소년아동, 369
66.5%
노인, 139
 
25.0%
아동, 35
 
6.3%
성인가족, 7
 
1.3%
청소년아동장애인, 3
 
0.5%
<NA> 2
 
0.4%

Length

2024-04-17T11:22:38.043981image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T11:22:38.143807image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
청소년아동 369
66.5%
노인 139
 
25.0%
아동 35
 
6.3%
성인가족 7
 
1.3%
청소년아동장애인 3
 
0.5%
na 2
 
0.4%

s_code
Categorical

HIGH CORRELATION 

Distinct15
Distinct (%)2.7%
Missing0
Missing (%)0.0%
Memory size4.5 KiB
아동청소년심리치유서비스(우리아이가달라졌어요!)
324 
시각장애인 안마서비스
95 
아동건강관리서비스
35 
노인건강관리서비스
 
27
동화야 놀~자(스토리텔링)
 
25
Other values (10)
49 

Length

Max length26
Median length25
Mean length19.338739
Min length7

Unique

Unique5 ?
Unique (%)0.9%

Sample

1st row아동청소년심리치유서비스(우리아이가달라졌어요!)
2nd row뇌에 기(氣)가 팍팍
3rd row아동청소년심리치유서비스(우리아이가달라졌어요!)
4th row아동청소년심리치유서비스(우리아이가달라졌어요!)
5th row아동청소년심리치유서비스(우리아이가달라졌어요!)

Common Values

ValueCountFrequency (%)
아동청소년심리치유서비스(우리아이가달라졌어요!) 324
58.4%
시각장애인 안마서비스 95
 
17.1%
아동건강관리서비스 35
 
6.3%
노인건강관리서비스 27
 
4.9%
동화야 놀~자(스토리텔링) 25
 
4.5%
뇌에 기(氣)가 팍팍 16
 
2.9%
해양역사문화체험 아카데미 9
 
1.6%
아동정서발달지원서비스 9
 
1.6%
자녀의 성공을 돕는 부모코칭(키울 MOM난다!) 7
 
1.3%
장애인 보조기기 렌탈서비스 3
 
0.5%
Other values (5) 5
 
0.9%

Length

2024-04-17T11:22:38.242812image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
아동청소년심리치유서비스(우리아이가달라졌어요 324
42.7%
안마서비스 95
 
12.5%
시각장애인 95
 
12.5%
아동건강관리서비스 35
 
4.6%
노인건강관리서비스 27
 
3.6%
동화야 25
 
3.3%
놀~자(스토리텔링 25
 
3.3%
뇌에 16
 
2.1%
기(氣)가 16
 
2.1%
팍팍 16
 
2.1%
Other values (25) 85
 
11.2%

last_load_dttm
Categorical

CONSTANT 

Distinct1
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size4.5 KiB
2021-03-01 05:35:03
555 

Length

Max length19
Median length19
Mean length19
Min length19

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
2021-03-01 05:35:03 555
100.0%

Length

2024-04-17T11:22:38.339840image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T11:22:38.409433image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2021-03-01 555
50.0%
05:35:03 555
50.0%

Interactions

2024-04-17T11:22:34.174139image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T11:22:33.747790image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T11:22:33.950380image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T11:22:34.240144image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T11:22:33.811605image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T11:22:34.027229image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T11:22:34.313810image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T11:22:33.883891image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T11:22:34.099428image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-04-17T11:22:38.454543image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
numxydeparts_gubuns_code
num1.0000.2620.0570.1330.1530.136
x0.2621.0000.7030.9040.1450.000
y0.0570.7031.0000.8910.0870.000
depart0.1330.9040.8911.0000.1680.129
s_gubun0.1530.1450.0870.1681.0001.000
s_code0.1360.0000.0000.1291.0001.000
2024-04-17T11:22:38.532848image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
departs_gubuns_code
depart1.0000.0850.043
s_gubun0.0851.0000.993
s_code0.0430.9931.000
2024-04-17T11:22:38.619013image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
numxydeparts_gubuns_code
num1.0000.016-0.0130.0520.0630.050
x0.0161.0000.4790.6510.0630.000
y-0.0130.4791.0000.6420.0490.000
depart0.0520.6510.6421.0000.0850.043
s_gubun0.0630.0630.0490.0851.0000.993
s_code0.0500.0000.0000.0430.9931.000

Missing values

2024-04-17T11:22:34.410485image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-04-17T11:22:34.524451image/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.
2024-04-17T11:22:34.610029image/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
0507플로리시언어&상담센터k0738129.11211535.170273051-758-7942부산광역시 수영구 망미번영로52번길 59 (수영동)수영구청소년아동,아동청소년심리치유서비스(우리아이가달라졌어요!)2021-03-01 05:35:03
1508피아니스트노부스k1091129.01053835.113097010-5575-1524부산광역시 서구 대티로 159 (서대신동3가 협성르네상스. 117-306)서구노인,뇌에 기(氣)가 팍팍2021-03-01 05:35:03
2509하단창의숲k0525128.95921835.109998051-201-5459부산광역시 사하구 하신번영로 326 2층 (하단동)사하구청소년아동,아동청소년심리치유서비스(우리아이가달라졌어요!)2021-03-01 05:35:03
3510하담아동발달센터k0697<NA><NA>051-201-0075부산광역시 사하구 낙동대로 271 105호 (괴정동 신동양상가)사하구청소년아동,아동청소년심리치유서비스(우리아이가달라졌어요!)2021-03-01 05:35:03
4511하엘아동발달센터k0130<NA><NA>051-337-7562부산광역시 북구 덕천동 만덕대로 126 흥산빌딜 6층북구청소년아동,아동청소년심리치유서비스(우리아이가달라졌어요!)2021-03-01 05:35:03
5512하은언어심리센터k0714129.17508935.321348051-722-6003부산광역시 기장군 정관읍 정관로 560 4층 401호기장군청소년아동,아동청소년심리치유서비스(우리아이가달라졌어요!)2021-03-01 05:35:03
6513하은언어심리센터k0974129.06028335.152321051-995-6003부산광역시 부산진구 중앙대로666번길 17 6층 (부전동 시연빌딩)부산진구청소년아동,아동청소년심리치유서비스(우리아이가달라졌어요!)2021-03-01 05:35:03
7514하이브레인k0975129.14652435.167177051-731-7001부산광역시 해운대구 해운대로469번가길 91 상가동 1011호 (우동 센텀마리나아파트)해운대구노인,뇌에 기(氣)가 팍팍2021-03-01 05:35:03
8515학장종합사회복지관k0011<NA><NA>051-312-4017부산광역시 사상구 학장동 168-7 사회복지법인 부산생명의전화사상구청소년아동,아동청소년심리치유서비스(우리아이가달라졌어요!)2021-03-01 05:35:03
9516한국전통지압원k0118<NA><NA>051-507-2116부산광역시 동래구 사직2동 42-9동래구노인,시각장애인 안마서비스2021-03-01 05:35:03
numnamememxyteladdrdeparts_gubuns_codelast_load_dttm
54542광안건강안마원k0944129.11404635.157363051-728-1844부산광역시 수영구 광안로7번길 8 3층 (광안동)수영구노인,시각장애인 안마서비스2021-03-01 05:35:03
54643교대첨단인지브레인k0651129.08151435.196471051-506-3523부산광역시 연제구 명륜로 13 2층 (거제동) 교대 첨단인지브레인연제구청소년아동,아동청소년심리치유서비스(우리아이가달라졌어요!)2021-03-01 05:35:03
54744구남역언어심리상담센터k1042128.99508635.197818051-333-1250부산광역시 북구 백양대로 1025 2층 217호 (구포동 협진태양프라자)북구청소년아동,아동청소년심리치유서비스(우리아이가달라졌어요!)2021-03-01 05:35:03
54845구서첨단인지브레인k0537129.08791535.25366051-515-5689부산광역시 금정구 금강로 518 2층 (구서동)금정구청소년아동,아동청소년심리치유서비스(우리아이가달라졌어요!)2021-03-01 05:35:03
54946국민복지재단 국민사회서비스지원단k0183129.10295535.200001051-743-0031부산광역시 동래구 안락로 53 (안락동)동래구노인,뇌에 기(氣)가 팍팍2021-03-01 05:35:03
55047국제렘포레k0858128.91788835.097917051-204-9994부산광역시 강서구 명지국제8로 230 9층 901호 (명지동)강서구청소년아동,아동청소년심리치유서비스(우리아이가달라졌어요!)2021-03-01 05:35:03
55148국제맑음언어심리클리닉k0945128.91983435.098416051-203-7753부산광역시 강서구 명지국제8로 245 5층 503호 (명지동 명지뉴타워)강서구청소년아동,아동청소년심리치유서비스(우리아이가달라졌어요!)2021-03-01 05:35:03
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