Overview

Dataset statistics

Number of variables14
Number of observations351
Missing cells1755
Missing cells (%)35.7%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory41.3 KiB
Average record size in memory120.4 B

Variable types

Numeric3
Unsupported5
Text2
Categorical1
DateTime2
Boolean1

Alerts

data_day has constant value ""Constant
apr_at has constant value ""Constant
last_load_dttm has constant value ""Constant
gubun has 351 (100.0%) missing valuesMissing
tel has 351 (100.0%) missing valuesMissing
school_addr has 351 (100.0%) missing valuesMissing
inst_center has 351 (100.0%) missing valuesMissing
instt_code has 351 (100.0%) missing valuesMissing
skey has unique valuesUnique
gubun is an unsupported type, check if it needs cleaning or further analysisUnsupported
tel is an unsupported type, check if it needs cleaning or further analysisUnsupported
school_addr is an unsupported type, check if it needs cleaning or further analysisUnsupported
inst_center is an unsupported type, check if it needs cleaning or further analysisUnsupported
instt_code is an unsupported type, check if it needs cleaning or further analysisUnsupported

Reproduction

Analysis started2024-04-20 19:14:19.474820
Analysis finished2024-04-20 19:14:22.736806
Duration3.26 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

skey
Real number (ℝ)

UNIQUE 

Distinct351
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean4769
Minimum4594
Maximum4944
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size3.2 KiB
2024-04-21T04:14:22.864818image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum4594
5-th percentile4611.5
Q14681.5
median4769
Q34856.5
95-th percentile4926.5
Maximum4944
Range350
Interquartile range (IQR)175

Descriptive statistics

Standard deviation101.46921
Coefficient of variation (CV)0.021276831
Kurtosis-1.2
Mean4769
Median Absolute Deviation (MAD)88
Skewness0
Sum1673919
Variance10296
MonotonicityNot monotonic
2024-04-21T04:14:23.116506image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
4890 1
 
0.3%
4891 1
 
0.3%
4779 1
 
0.3%
4778 1
 
0.3%
4777 1
 
0.3%
4776 1
 
0.3%
4775 1
 
0.3%
4774 1
 
0.3%
4773 1
 
0.3%
4772 1
 
0.3%
Other values (341) 341
97.2%
ValueCountFrequency (%)
4594 1
0.3%
4595 1
0.3%
4596 1
0.3%
4597 1
0.3%
4598 1
0.3%
4599 1
0.3%
4600 1
0.3%
4601 1
0.3%
4602 1
0.3%
4603 1
0.3%
ValueCountFrequency (%)
4944 1
0.3%
4943 1
0.3%
4942 1
0.3%
4941 1
0.3%
4940 1
0.3%
4939 1
0.3%
4938 1
0.3%
4937 1
0.3%
4936 1
0.3%
4935 1
0.3%

gubun
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing351
Missing (%)100.0%
Memory size3.2 KiB

school_name
Text

Distinct342
Distinct (%)97.4%
Missing0
Missing (%)0.0%
Memory size2.9 KiB
2024-04-21T04:14:23.792247image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length16
Median length14
Mean length7.2364672
Min length5

Characters and Unicode

Total characters2540
Distinct characters294
Distinct categories6 ?
Distinct scripts4 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique333 ?
Unique (%)94.9%

Sample

1st row성은어린이집
2nd row신선어린이집
3rd row영도초등학교어린이집
4th row영선어린이집
5th row영지어린이집
ValueCountFrequency (%)
어린이집 10
 
2.7%
동심어린이집 2
 
0.5%
유치원 2
 
0.5%
한솔어린이집 2
 
0.5%
병설유치원 2
 
0.5%
늘푸른어린이집 2
 
0.5%
미래어린이집 2
 
0.5%
우신어린이집 2
 
0.5%
꿈나무유치원 2
 
0.5%
큰나무어린이집 2
 
0.5%
Other values (339) 342
92.4%
2024-04-21T04:14:24.914844image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
이 285
 
11.2%
린 275
 
10.8%
어 272
 
10.7%
집 272
 
10.7%
원 66
 
2.6%
치 53
 
2.1%
유 53
 
2.1%
동 39
 
1.5%
교 38
 
1.5%
초 38
 
1.5%
Other values (284) 1149
45.2%

Most occurring categories

ValueCountFrequency (%)
Other Letter 2466
97.1%
Space Separator 26
 
1.0%
Uppercase Letter 23
 
0.9%
Decimal Number 20
 
0.8%
Other Punctuation 3
 
0.1%
Lowercase Letter 2
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
이 285
 
11.6%
린 275
 
11.2%
어 272
 
11.0%
집 272
 
11.0%
원 66
 
2.7%
치 53
 
2.1%
유 53
 
2.1%
동 39
 
1.6%
교 38
 
1.5%
초 38
 
1.5%
Other values (263) 1075
43.6%
Uppercase Letter
ValueCountFrequency (%)
G 5
21.7%
L 5
21.7%
B 3
13.0%
K 3
13.0%
C 2
 
8.7%
I 2
 
8.7%
F 1
 
4.3%
R 1
 
4.3%
A 1
 
4.3%
Decimal Number
ValueCountFrequency (%)
2 6
30.0%
1 5
25.0%
4 4
20.0%
5 2
 
10.0%
6 1
 
5.0%
7 1
 
5.0%
3 1
 
5.0%
Other Punctuation
ValueCountFrequency (%)
? 2
66.7%
! 1
33.3%
Lowercase Letter
ValueCountFrequency (%)
k 1
50.0%
s 1
50.0%
Space Separator
ValueCountFrequency (%)
26
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 2463
97.0%
Common 49
 
1.9%
Latin 25
 
1.0%
Han 3
 
0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
이 285
 
11.6%
린 275
 
11.2%
어 272
 
11.0%
집 272
 
11.0%
원 66
 
2.7%
치 53
 
2.2%
유 53
 
2.2%
동 39
 
1.6%
교 38
 
1.5%
초 38
 
1.5%
Other values (260) 1072
43.5%
Latin
ValueCountFrequency (%)
G 5
20.0%
L 5
20.0%
B 3
12.0%
K 3
12.0%
C 2
 
8.0%
I 2
 
8.0%
k 1
 
4.0%
F 1
 
4.0%
R 1
 
4.0%
s 1
 
4.0%
Common
ValueCountFrequency (%)
26
53.1%
2 6
 
12.2%
1 5
 
10.2%
4 4
 
8.2%
5 2
 
4.1%
? 2
 
4.1%
! 1
 
2.0%
6 1
 
2.0%
7 1
 
2.0%
3 1
 
2.0%
Han
ValueCountFrequency (%)
訣 1
33.3%
低 1
33.3%
恃 1
33.3%

Most occurring blocks

ValueCountFrequency (%)
Hangul 2463
97.0%
ASCII 74
 
2.9%
CJK 3
 
0.1%

Most frequent character per block

Hangul
ValueCountFrequency (%)
이 285
 
11.6%
린 275
 
11.2%
어 272
 
11.0%
집 272
 
11.0%
원 66
 
2.7%
치 53
 
2.2%
유 53
 
2.2%
동 39
 
1.6%
교 38
 
1.5%
초 38
 
1.5%
Other values (260) 1072
43.5%
ASCII
ValueCountFrequency (%)
26
35.1%
2 6
 
8.1%
G 5
 
6.8%
L 5
 
6.8%
1 5
 
6.8%
4 4
 
5.4%
B 3
 
4.1%
K 3
 
4.1%
C 2
 
2.7%
5 2
 
2.7%
Other values (11) 13
17.6%
CJK
ValueCountFrequency (%)
訣 1
33.3%
低 1
33.3%
恃 1
33.3%

student_num
Text

Distinct138
Distinct (%)39.3%
Missing0
Missing (%)0.0%
Memory size2.9 KiB
2024-04-21T04:14:26.053948image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length6
Median length2
Mean length2.2022792
Min length1

Characters and Unicode

Total characters773
Distinct characters13
Distinct categories4 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique60 ?
Unique (%)17.1%

Sample

1st row50
2nd row72
3rd row47
4th row60
5th row75
ValueCountFrequency (%)
20 17
 
4.8%
19 9
 
2.6%
46 8
 
2.3%
65 8
 
2.3%
45 8
 
2.3%
60 7
 
2.0%
16 7
 
2.0%
49 7
 
2.0%
40 7
 
2.0%
13 6
 
1.7%
Other values (128) 267
76.1%
2024-04-21T04:14:27.582991image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 115
14.9%
2 85
11.0%
3 85
11.0%
6 80
10.3%
4 79
10.2%
0 77
10.0%
5 73
9.4%
7 70
9.1%
8 56
7.2%
9 49
6.3%
Other values (3) 4
 
0.5%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 769
99.5%
Other Punctuation 2
 
0.3%
Open Punctuation 1
 
0.1%
Close Punctuation 1
 
0.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 115
15.0%
2 85
11.1%
3 85
11.1%
6 80
10.4%
4 79
10.3%
0 77
10.0%
5 73
9.5%
7 70
9.1%
8 56
7.3%
9 49
6.4%
Other Punctuation
ValueCountFrequency (%)
, 2
100.0%
Open Punctuation
ValueCountFrequency (%)
( 1
100.0%
Close Punctuation
ValueCountFrequency (%)
) 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 773
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
1 115
14.9%
2 85
11.0%
3 85
11.0%
6 80
10.3%
4 79
10.2%
0 77
10.0%
5 73
9.4%
7 70
9.1%
8 56
7.2%
9 49
6.3%
Other values (3) 4
 
0.5%

Most occurring blocks

ValueCountFrequency (%)
ASCII 773
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 115
14.9%
2 85
11.0%
3 85
11.0%
6 80
10.3%
4 79
10.2%
0 77
10.0%
5 73
9.4%
7 70
9.1%
8 56
7.2%
9 49
6.3%
Other values (3) 4
 
0.5%

tel
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing351
Missing (%)100.0%
Memory size3.2 KiB

school_addr
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing351
Missing (%)100.0%
Memory size3.2 KiB

school_kind
Categorical

Distinct4
Distinct (%)1.1%
Missing0
Missing (%)0.0%
Memory size2.9 KiB
기존
232 
신규
99 
기존
 
14
신규
 
6

Length

Max length4
Median length2
Mean length2.1139601
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row기존
2nd row기존
3rd row신규
4th row기존
5th row기존

Common Values

ValueCountFrequency (%)
기존 232
66.1%
신규 99
28.2%
기존 14
 
4.0%
신규 6
 
1.7%

Length

2024-04-21T04:14:28.030123image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-21T04:14:28.384040image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
기존 246
70.1%
신규 105
29.9%

inst_center
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing351
Missing (%)100.0%
Memory size3.2 KiB

lat
Real number (ℝ)

Distinct338
Distinct (%)96.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean35.167686
Minimum35.048085
Maximum35.359696
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size3.2 KiB
2024-04-21T04:14:28.731050image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum35.048085
5-th percentile35.079911
Q135.116449
median35.165397
Q335.207792
95-th percentile35.274063
Maximum35.359696
Range0.31161114
Interquartile range (IQR)0.0913425

Descriptive statistics

Standard deviation0.064138594
Coefficient of variation (CV)0.0018237934
Kurtosis0.0053679008
Mean35.167686
Median Absolute Deviation (MAD)0.04469317
Skewness0.56197293
Sum12343.858
Variance0.0041137592
MonotonicityNot monotonic
2024-04-21T04:14:29.163723image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
35.17966779 2
 
0.6%
35.18959425 2
 
0.6%
35.22468839 2
 
0.6%
35.24953561 2
 
0.6%
35.18408371 2
 
0.6%
35.15574257 2
 
0.6%
35.19830366 2
 
0.6%
35.238226 2
 
0.6%
35.20578417 2
 
0.6%
35.05726776 2
 
0.6%
Other values (328) 331
94.3%
ValueCountFrequency (%)
35.04808475 1
0.3%
35.05592626 1
0.3%
35.05726776 2
0.6%
35.05929192 1
0.3%
35.06376481 1
0.3%
35.06688592 1
0.3%
35.06924079 1
0.3%
35.07221265 1
0.3%
35.07278202 1
0.3%
35.07420253 1
0.3%
ValueCountFrequency (%)
35.35969589 1
0.3%
35.34187953 1
0.3%
35.33968266 1
0.3%
35.33953009 1
0.3%
35.3368807 1
0.3%
35.33196448 1
0.3%
35.33055974 1
0.3%
35.32925993 1
0.3%
35.32847728 1
0.3%
35.32632973 1
0.3%

lng
Real number (ℝ)

Distinct338
Distinct (%)96.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean129.06409
Minimum128.83574
Maximum129.28265
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size3.2 KiB
2024-04-21T04:14:29.587590image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum128.83574
5-th percentile128.97147
Q1129.01904
median129.06339
Q3129.103
95-th percentile129.18315
Maximum129.28265
Range0.4469053
Interquartile range (IQR)0.0839608

Descriptive statistics

Standard deviation0.06749857
Coefficient of variation (CV)0.0005229849
Kurtosis0.58662828
Mean129.06409
Median Absolute Deviation (MAD)0.0429989
Skewness0.14380377
Sum45301.495
Variance0.0045560569
MonotonicityNot monotonic
2024-04-21T04:14:30.016099image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
129.1275334 2
 
0.6%
129.2048929 2
 
0.6%
129.017144 2
 
0.6%
129.0144 2
 
0.6%
129.0802187 2
 
0.6%
128.9886692 2
 
0.6%
128.9999801 2
 
0.6%
129.2154125 2
 
0.6%
129.0333375 2
 
0.6%
128.9714738 2
 
0.6%
Other values (328) 331
94.3%
ValueCountFrequency (%)
128.83574 1
0.3%
128.8539364 1
0.3%
128.873589 1
0.3%
128.8762039 1
0.3%
128.9008223 1
0.3%
128.9070712 1
0.3%
128.916705 1
0.3%
128.9225434 1
0.3%
128.9241196 1
0.3%
128.9596068 1
0.3%
ValueCountFrequency (%)
129.2826453 1
0.3%
129.243607 1
0.3%
129.2238676 1
0.3%
129.2163239 1
0.3%
129.2154125 2
0.6%
129.2152822 1
0.3%
129.2127674 1
0.3%
129.2104953 1
0.3%
129.2103533 1
0.3%
129.206185 1
0.3%

data_day
Date

CONSTANT 

Distinct1
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Memory size2.9 KiB
Minimum2020-12-31 00:00:00
Maximum2020-12-31 00:00:00
2024-04-21T04:14:30.359844image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T04:14:30.658549image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=1)

apr_at
Boolean

CONSTANT 

Distinct1
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Memory size479.0 B
False
351 
ValueCountFrequency (%)
False 351
100.0%
2024-04-21T04:14:30.950488image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

instt_code
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing351
Missing (%)100.0%
Memory size3.2 KiB

last_load_dttm
Date

CONSTANT 

Distinct1
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Memory size2.9 KiB
Minimum2021-05-01 05:40:03
Maximum2021-05-01 05:40:03
2024-04-21T04:14:31.204561image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T04:14:31.501312image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=1)

Interactions

2024-04-21T04:14:21.187528image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T04:14:19.996810image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T04:14:20.477102image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T04:14:21.444256image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T04:14:20.162272image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T04:14:20.675198image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T04:14:21.695023image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T04:14:20.324621image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T04:14:20.934480image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-04-21T04:14:31.709406image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
skeyschool_kindlatlng
skey1.0000.5680.9030.871
school_kind0.5681.0000.5610.571
lat0.9030.5611.0000.721
lng0.8710.5710.7211.000
2024-04-21T04:14:31.958143image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
skeylatlngschool_kind
skey1.000-0.402-0.0440.374
lat-0.4021.0000.4920.367
lng-0.0440.4921.0000.376
school_kind0.3740.3670.3761.000

Missing values

2024-04-21T04:14:22.057808image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-04-21T04:14:22.620461image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Nullity matrix is a data-dense display which lets you quickly visually pick out patterns in data completion.

Sample

skeygubunschool_namestudent_numtelschool_addrschool_kindinst_centerlatlngdata_dayapr_atinstt_codelast_load_dttm
04890<NA>성은어린이집50<NA><NA>기존<NA>35.091868129.0622532020-12-31N<NA>2021-05-01 05:40:03
14891<NA>신선어린이집72<NA><NA>기존<NA>35.089174129.0445072020-12-31N<NA>2021-05-01 05:40:03
24892<NA>영도초등학교어린이집47<NA><NA>신규<NA>35.090123129.0462192020-12-31N<NA>2021-05-01 05:40:03
34893<NA>영선어린이집60<NA><NA>기존<NA>35.07961129.0465562020-12-31N<NA>2021-05-01 05:40:03
44894<NA>영지어린이집75<NA><NA>기존<NA>35.089916129.0576552020-12-31N<NA>2021-05-01 05:40:03
54895<NA>와치어린이집62<NA><NA>기존<NA>35.092021129.0570572020-12-31N<NA>2021-05-01 05:40:03
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skeygubunschool_namestudent_numtelschool_addrschool_kindinst_centerlatlngdata_dayapr_atinstt_codelast_load_dttm
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3434684<NA>IBK참!좋은어린이집25<NA><NA>기존<NA>35.136946129.0561672020-12-31N<NA>2021-05-01 05:40:03
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3464687<NA>범일어린이집68<NA><NA>기존<NA>35.141676129.0533432020-12-31N<NA>2021-05-01 05:40:03
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3484689<NA>수정 4동 어린이집48<NA><NA>기존<NA>35.127352129.0388072020-12-31N<NA>2021-05-01 05:40:03
3494690<NA>수정삼성어린이집122<NA><NA>기존<NA>35.131346129.0449582020-12-31N<NA>2021-05-01 05:40:03
3504691<NA>오션브릿지어린이집36<NA><NA>기존<NA>35.133414129.0590842020-12-31N<NA>2021-05-01 05:40:03