Overview

Dataset statistics

Number of variables8
Number of observations26
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory1.9 KiB
Average record size in memory74.1 B

Variable types

Numeric5
Text3

Dataset

Description충남지방경찰청에서 운전면허 학원 현황에 대한 데이터로 학원명, 전화번호, 주소, 총부지면적, 교육생정원, 수강생 등의 항목을 제공합니다.
URLhttps://www.data.go.kr/data/15029376/fileData.do

Alerts

수강료(1종보통) is highly overall correlated with 수강료(2종자동)High correlation
수강료(2종자동) is highly overall correlated with 수강료(1종보통)High correlation
연번 has unique valuesUnique
학원명 has unique valuesUnique
전화번호 has unique valuesUnique
주 소 has unique valuesUnique
총부지면적(제곱미터) has unique valuesUnique

Reproduction

Analysis started2023-12-12 10:39:51.888251
Analysis finished2023-12-12 10:39:55.668069
Duration3.78 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

연번
Real number (ℝ)

UNIQUE 

Distinct26
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean13.5
Minimum1
Maximum26
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size366.0 B
2023-12-12T19:39:56.077327image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile2.25
Q17.25
median13.5
Q319.75
95-th percentile24.75
Maximum26
Range25
Interquartile range (IQR)12.5

Descriptive statistics

Standard deviation7.6485293
Coefficient of variation (CV)0.56655772
Kurtosis-1.2
Mean13.5
Median Absolute Deviation (MAD)6.5
Skewness0
Sum351
Variance58.5
MonotonicityStrictly increasing
2023-12-12T19:39:56.225673image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=26)
ValueCountFrequency (%)
1 1
 
3.8%
15 1
 
3.8%
26 1
 
3.8%
25 1
 
3.8%
24 1
 
3.8%
23 1
 
3.8%
22 1
 
3.8%
21 1
 
3.8%
20 1
 
3.8%
19 1
 
3.8%
Other values (16) 16
61.5%
ValueCountFrequency (%)
1 1
3.8%
2 1
3.8%
3 1
3.8%
4 1
3.8%
5 1
3.8%
6 1
3.8%
7 1
3.8%
8 1
3.8%
9 1
3.8%
10 1
3.8%
ValueCountFrequency (%)
26 1
3.8%
25 1
3.8%
24 1
3.8%
23 1
3.8%
22 1
3.8%
21 1
3.8%
20 1
3.8%
19 1
3.8%
18 1
3.8%
17 1
3.8%

학원명
Text

UNIQUE 

Distinct26
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size340.0 B
2023-12-12T19:39:56.483965image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length8
Median length7
Mean length3.7692308
Min length2

Characters and Unicode

Total characters98
Distinct characters45
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique26 ?
Unique (%)100.0%

Sample

1st row반도
2nd row서산중앙
3rd row(주)당진
4th row(자)백제
5th row(주)건양
ValueCountFrequency (%)
반도 1
 
3.8%
서산중앙 1
 
3.8%
서해 1
 
3.8%
용화 1
 
3.8%
자)천안대성 1
 
3.8%
보령동양 1
 
3.8%
신홍성 1
 
3.8%
중앙삼성 1
 
3.8%
서산현대 1
 
3.8%
우석 1
 
3.8%
Other values (16) 16
61.5%
2023-12-12T19:39:56.977902image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
( 10
 
10.2%
) 10
 
10.2%
주 8
 
8.2%
서 5
 
5.1%
산 5
 
5.1%
성 4
 
4.1%
삼 3
 
3.1%
대 3
 
3.1%
천 2
 
2.0%
양 2
 
2.0%
Other values (35) 46
46.9%

Most occurring categories

ValueCountFrequency (%)
Other Letter 78
79.6%
Open Punctuation 10
 
10.2%
Close Punctuation 10
 
10.2%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
주 8
 
10.3%
서 5
 
6.4%
산 5
 
6.4%
성 4
 
5.1%
삼 3
 
3.8%
대 3
 
3.8%
천 2
 
2.6%
양 2
 
2.6%
령 2
 
2.6%
보 2
 
2.6%
Other values (33) 42
53.8%
Open Punctuation
ValueCountFrequency (%)
( 10
100.0%
Close Punctuation
ValueCountFrequency (%)
) 10
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 78
79.6%
Common 20
 
20.4%

Most frequent character per script

Hangul
ValueCountFrequency (%)
주 8
 
10.3%
서 5
 
6.4%
산 5
 
6.4%
성 4
 
5.1%
삼 3
 
3.8%
대 3
 
3.8%
천 2
 
2.6%
양 2
 
2.6%
령 2
 
2.6%
보 2
 
2.6%
Other values (33) 42
53.8%
Common
ValueCountFrequency (%)
( 10
50.0%
) 10
50.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 78
79.6%
ASCII 20
 
20.4%

Most frequent character per block

ASCII
ValueCountFrequency (%)
( 10
50.0%
) 10
50.0%
Hangul
ValueCountFrequency (%)
주 8
 
10.3%
서 5
 
6.4%
산 5
 
6.4%
성 4
 
5.1%
삼 3
 
3.8%
대 3
 
3.8%
천 2
 
2.6%
양 2
 
2.6%
령 2
 
2.6%
보 2
 
2.6%
Other values (33) 42
53.8%

전화번호
Text

UNIQUE 

Distinct26
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size340.0 B
2023-12-12T19:39:57.262340image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length12
Median length12
Mean length12
Min length12

Characters and Unicode

Total characters312
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

Unique26 ?
Unique (%)100.0%

Sample

1st row041-675-3040
2nd row041-665-2676
3rd row041-355-3523
4th row041-835-0708
5th row041-742-7500
ValueCountFrequency (%)
041-675-3040 1
 
3.8%
041-665-2676 1
 
3.8%
041-953-3468 1
 
3.8%
041-549-8891 1
 
3.8%
041-568-7070 1
 
3.8%
041-931-3000 1
 
3.8%
041-634-7077 1
 
3.8%
041-563-0001 1
 
3.8%
041-663-5555 1
 
3.8%
041-548-3601 1
 
3.8%
Other values (16) 16
61.5%
2023-12-12T19:39:57.694653image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
- 52
16.7%
0 49
15.7%
1 45
14.4%
4 37
11.9%
5 37
11.9%
3 28
9.0%
6 19
 
6.1%
7 14
 
4.5%
2 14
 
4.5%
8 11
 
3.5%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 260
83.3%
Dash Punctuation 52
 
16.7%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 49
18.8%
1 45
17.3%
4 37
14.2%
5 37
14.2%
3 28
10.8%
6 19
 
7.3%
7 14
 
5.4%
2 14
 
5.4%
8 11
 
4.2%
9 6
 
2.3%
Dash Punctuation
ValueCountFrequency (%)
- 52
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 312
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
- 52
16.7%
0 49
15.7%
1 45
14.4%
4 37
11.9%
5 37
11.9%
3 28
9.0%
6 19
 
6.1%
7 14
 
4.5%
2 14
 
4.5%
8 11
 
3.5%

Most occurring blocks

ValueCountFrequency (%)
ASCII 312
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
- 52
16.7%
0 49
15.7%
1 45
14.4%
4 37
11.9%
5 37
11.9%
3 28
9.0%
6 19
 
6.1%
7 14
 
4.5%
2 14
 
4.5%
8 11
 
3.5%

주 소
Text

UNIQUE 

Distinct26
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size340.0 B
2023-12-12T19:39:57.981954image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length39
Median length32.5
Mean length25.038462
Min length18

Characters and Unicode

Total characters651
Distinct characters107
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

Unique26 ?
Unique (%)100.0%

Sample

1st row충남 태안군 태안읍 서해로 2120
2nd row충남 서산시 쌍연북3길 17, (동문동)
3rd row충남 당진시 송악읍 광명길 27, (당진자동차운전전문학원)
4th row충남 부여군 부여읍 왕릉로 244-7
5th row충남 논산 은진 탑정로 332-22
ValueCountFrequency (%)
충남 26
 
18.2%
천안시 5
 
3.5%
서북구 4
 
2.8%
서산시 3
 
2.1%
보령시 3
 
2.1%
당진시 3
 
2.1%
아산시 3
 
2.1%
17 2
 
1.4%
중앙로 2
 
1.4%
27 2
 
1.4%
Other values (90) 90
62.9%
2023-12-12T19:39:58.419952image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
117
 
18.0%
충 28
 
4.3%
남 28
 
4.3%
동 21
 
3.2%
시 21
 
3.2%
로 20
 
3.1%
1 19
 
2.9%
, 19
 
2.9%
2 16
 
2.5%
) 15
 
2.3%
Other values (97) 347
53.3%

Most occurring categories

ValueCountFrequency (%)
Other Letter 382
58.7%
Space Separator 117
 
18.0%
Decimal Number 93
 
14.3%
Other Punctuation 19
 
2.9%
Close Punctuation 15
 
2.3%
Open Punctuation 15
 
2.3%
Dash Punctuation 10
 
1.5%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
충 28
 
7.3%
남 28
 
7.3%
동 21
 
5.5%
시 21
 
5.5%
로 20
 
5.2%
서 12
 
3.1%
산 11
 
2.9%
천 11
 
2.9%
원 10
 
2.6%
학 10
 
2.6%
Other values (82) 210
55.0%
Decimal Number
ValueCountFrequency (%)
1 19
20.4%
2 16
17.2%
6 11
11.8%
3 11
11.8%
7 10
10.8%
0 8
8.6%
4 7
 
7.5%
8 5
 
5.4%
9 4
 
4.3%
5 2
 
2.2%
Space Separator
ValueCountFrequency (%)
117
100.0%
Other Punctuation
ValueCountFrequency (%)
, 19
100.0%
Close Punctuation
ValueCountFrequency (%)
) 15
100.0%
Open Punctuation
ValueCountFrequency (%)
( 15
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 10
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 382
58.7%
Common 269
41.3%

Most frequent character per script

Hangul
ValueCountFrequency (%)
충 28
 
7.3%
남 28
 
7.3%
동 21
 
5.5%
시 21
 
5.5%
로 20
 
5.2%
서 12
 
3.1%
산 11
 
2.9%
천 11
 
2.9%
원 10
 
2.6%
학 10
 
2.6%
Other values (82) 210
55.0%
Common
ValueCountFrequency (%)
117
43.5%
1 19
 
7.1%
, 19
 
7.1%
2 16
 
5.9%
) 15
 
5.6%
( 15
 
5.6%
6 11
 
4.1%
3 11
 
4.1%
7 10
 
3.7%
- 10
 
3.7%
Other values (5) 26
 
9.7%

Most occurring blocks

ValueCountFrequency (%)
Hangul 382
58.7%
ASCII 269
41.3%

Most frequent character per block

ASCII
ValueCountFrequency (%)
117
43.5%
1 19
 
7.1%
, 19
 
7.1%
2 16
 
5.9%
) 15
 
5.6%
( 15
 
5.6%
6 11
 
4.1%
3 11
 
4.1%
7 10
 
3.7%
- 10
 
3.7%
Other values (5) 26
 
9.7%
Hangul
ValueCountFrequency (%)
충 28
 
7.3%
남 28
 
7.3%
동 21
 
5.5%
시 21
 
5.5%
로 20
 
5.2%
서 12
 
3.1%
산 11
 
2.9%
천 11
 
2.9%
원 10
 
2.6%
학 10
 
2.6%
Other values (82) 210
55.0%

총부지면적(제곱미터)
Real number (ℝ)

UNIQUE 

Distinct26
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean11850.192
Minimum6618
Maximum21608
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size366.0 B
2023-12-12T19:39:58.607837image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum6618
5-th percentile6980.25
Q19210.5
median10139
Q313370
95-th percentile20556.25
Maximum21608
Range14990
Interquartile range (IQR)4159.5

Descriptive statistics

Standard deviation4310.2054
Coefficient of variation (CV)0.36372451
Kurtosis0.076374932
Mean11850.192
Median Absolute Deviation (MAD)2013.5
Skewness1.0303548
Sum308105
Variance18577871
MonotonicityNot monotonic
2023-12-12T19:39:58.769368image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=26)
ValueCountFrequency (%)
9994 1
 
3.8%
10900 1
 
3.8%
9413 1
 
3.8%
9934 1
 
3.8%
8269 1
 
3.8%
10284 1
 
3.8%
16165 1
 
3.8%
9717 1
 
3.8%
6618 1
 
3.8%
21136 1
 
3.8%
Other values (16) 16
61.5%
ValueCountFrequency (%)
6618 1
3.8%
6817 1
3.8%
7470 1
3.8%
7982 1
3.8%
8269 1
3.8%
8324 1
3.8%
9143 1
3.8%
9413 1
3.8%
9717 1
3.8%
9740 1
3.8%
ValueCountFrequency (%)
21608 1
3.8%
21136 1
3.8%
18817 1
3.8%
17791 1
3.8%
16841 1
3.8%
16165 1
3.8%
13554 1
3.8%
12818 1
3.8%
12808 1
3.8%
11650 1
3.8%

교육생정원
Real number (ℝ)

Distinct8
Distinct (%)30.8%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean214.03846
Minimum126
Maximum392
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size366.0 B
2023-12-12T19:39:58.934726image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum126
5-th percentile192
Q1192.75
median196
Q3196
95-th percentile384.5
Maximum392
Range266
Interquartile range (IQR)3.25

Descriptive statistics

Standard deviation63.934642
Coefficient of variation (CV)0.29870632
Kurtosis4.4786078
Mean214.03846
Median Absolute Deviation (MAD)1
Skewness2.3036681
Sum5565
Variance4087.6385
MonotonicityNot monotonic
2023-12-12T19:39:59.092313image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=8)
ValueCountFrequency (%)
196 12
46.2%
192 6
23.1%
195 3
 
11.5%
392 1
 
3.8%
200 1
 
3.8%
126 1
 
3.8%
368 1
 
3.8%
390 1
 
3.8%
ValueCountFrequency (%)
126 1
 
3.8%
192 6
23.1%
195 3
 
11.5%
196 12
46.2%
200 1
 
3.8%
368 1
 
3.8%
390 1
 
3.8%
392 1
 
3.8%
ValueCountFrequency (%)
392 1
 
3.8%
390 1
 
3.8%
368 1
 
3.8%
200 1
 
3.8%
196 12
46.2%
195 3
 
11.5%
192 6
23.1%
126 1
 
3.8%

수강료(1종보통)
Real number (ℝ)

HIGH CORRELATION 

Distinct21
Distinct (%)80.8%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean692703.15
Minimum483000
Maximum765000
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size366.0 B
2023-12-12T19:39:59.243026image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum483000
5-th percentile540750
Q1668250
median728500
Q3753800
95-th percentile761136.5
Maximum765000
Range282000
Interquartile range (IQR)85550

Descriptive statistics

Standard deviation79442.219
Coefficient of variation (CV)0.11468436
Kurtosis0.81433693
Mean692703.15
Median Absolute Deviation (MAD)26500
Skewness-1.3237772
Sum18010282
Variance6.3110661 × 109
MonotonicityNot monotonic
2023-12-12T19:39:59.400340image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=21)
ValueCountFrequency (%)
755000 4
 
15.4%
730000 3
 
11.5%
765000 1
 
3.8%
664000 1
 
3.8%
595000 1
 
3.8%
754100 1
 
3.8%
561000 1
 
3.8%
580000 1
 
3.8%
749100 1
 
3.8%
695000 1
 
3.8%
Other values (11) 11
42.3%
ValueCountFrequency (%)
483000 1
3.8%
534000 1
3.8%
561000 1
3.8%
580000 1
3.8%
595000 1
3.8%
641000 1
3.8%
664000 1
3.8%
681000 1
3.8%
690000 1
3.8%
695000 1
3.8%
ValueCountFrequency (%)
765000 1
 
3.8%
763182 1
 
3.8%
755000 4
15.4%
754100 1
 
3.8%
752900 1
 
3.8%
750000 1
 
3.8%
749100 1
 
3.8%
730000 3
11.5%
727000 1
 
3.8%
710000 1
 
3.8%

수강료(2종자동)
Real number (ℝ)

HIGH CORRELATION 

Distinct21
Distinct (%)80.8%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean692703.15
Minimum483000
Maximum765000
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size366.0 B
2023-12-12T19:39:59.541905image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum483000
5-th percentile540750
Q1668250
median728500
Q3753800
95-th percentile761136.5
Maximum765000
Range282000
Interquartile range (IQR)85550

Descriptive statistics

Standard deviation79442.219
Coefficient of variation (CV)0.11468436
Kurtosis0.81433693
Mean692703.15
Median Absolute Deviation (MAD)26500
Skewness-1.3237772
Sum18010282
Variance6.3110661 × 109
MonotonicityNot monotonic
2023-12-12T19:39:59.670469image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=21)
ValueCountFrequency (%)
755000 4
 
15.4%
730000 3
 
11.5%
765000 1
 
3.8%
664000 1
 
3.8%
595000 1
 
3.8%
754100 1
 
3.8%
561000 1
 
3.8%
580000 1
 
3.8%
749100 1
 
3.8%
695000 1
 
3.8%
Other values (11) 11
42.3%
ValueCountFrequency (%)
483000 1
3.8%
534000 1
3.8%
561000 1
3.8%
580000 1
3.8%
595000 1
3.8%
641000 1
3.8%
664000 1
3.8%
681000 1
3.8%
690000 1
3.8%
695000 1
3.8%
ValueCountFrequency (%)
765000 1
 
3.8%
763182 1
 
3.8%
755000 4
15.4%
754100 1
 
3.8%
752900 1
 
3.8%
750000 1
 
3.8%
749100 1
 
3.8%
730000 3
11.5%
727000 1
 
3.8%
710000 1
 
3.8%

Interactions

2023-12-12T19:39:54.866650image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T19:39:52.291629image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T19:39:52.909531image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T19:39:53.602615image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T19:39:54.237357image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T19:39:54.982730image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T19:39:52.410761image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T19:39:53.045352image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T19:39:53.724318image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T19:39:54.354568image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T19:39:55.130212image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T19:39:52.553546image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T19:39:53.188580image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T19:39:53.861493image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T19:39:54.496083image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T19:39:55.224518image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T19:39:52.668080image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T19:39:53.327657image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T19:39:53.978788image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T19:39:54.621068image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T19:39:55.316662image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T19:39:52.787625image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T19:39:53.461861image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T19:39:54.118356image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T19:39:54.738942image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-12T19:39:59.769562image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
연번학원명전화번호주 소총부지면적(제곱미터)교육생정원수강료(1종보통)수강료(2종자동)
연번1.0001.0001.0001.0000.5820.0000.0000.000
학원명1.0001.0001.0001.0001.0001.0001.0001.000
전화번호1.0001.0001.0001.0001.0001.0001.0001.000
주 소1.0001.0001.0001.0001.0001.0001.0001.000
총부지면적(제곱미터)0.5821.0001.0001.0001.0000.8670.1800.180
교육생정원0.0001.0001.0001.0000.8671.0000.2680.268
수강료(1종보통)0.0001.0001.0001.0000.1800.2681.0001.000
수강료(2종자동)0.0001.0001.0001.0000.1800.2681.0001.000
2023-12-12T19:39:59.903733image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
연번총부지면적(제곱미터)교육생정원수강료(1종보통)수강료(2종자동)
연번1.000-0.175-0.042-0.088-0.088
총부지면적(제곱미터)-0.1751.0000.324-0.066-0.066
교육생정원-0.0420.3241.0000.1600.160
수강료(1종보통)-0.088-0.0660.1601.0001.000
수강료(2종자동)-0.088-0.0660.1601.0001.000

Missing values

2023-12-12T19:39:55.448842image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-12T19:39:55.603561image/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

연번학원명전화번호주 소총부지면적(제곱미터)교육생정원수강료(1종보통)수강료(2종자동)
01반도041-675-3040충남 태안군 태안읍 서해로 21209994196765000765000
12서산중앙041-665-2676충남 서산시 쌍연북3길 17, (동문동)9802192690000690000
23(주)당진041-355-3523충남 당진시 송악읍 광명길 27, (당진자동차운전전문학원)9143196727000727000
34(자)백제041-835-0708충남 부여군 부여읍 왕릉로 244-718817196710000710000
45(주)건양041-742-7500충남 논산 은진 탑정로 332-2210510192730000730000
56천안041-551-2420충남 천안시 서북구 천안대로 962, (두정동, 천안자동차운전전문학원)21608392755000755000
67합덕041-362-6175충남 당진시 우강면 중방로 62-611650196730000730000
78(주)서부042-536-0112충남 계룡시 엄사면 계백로 3080-109740200681000681000
89제일041-931-1515충남 보령시 청소면 충서로 366012818195534000534000
910(유)서산041-665-7432충남 서산시 소탐1로 83, (수석동)17791196763182763182
연번학원명전화번호주 소총부지면적(제곱미터)교육생정원수강료(1종보통)수강료(2종자동)
1617영일041-585-0155충남 천안시 서북구 성환읍 성환2로 8-15, (영일자동차학원)7470126705000705000
1718우석041-548-3601충남 아산시 배방읍 배방로 19416841368750000750000
1819서산현대041-663-5555충남 서산시 음암면 중앙로 73421136192695000695000
1920중앙삼성041-563-0001충남 천안시 서북구 부대3길 7, (부대동, 중앙삼성자동차운전학원)6618196749100749100
2021신홍성041-634-7077충남 홍성군 홍성읍 충서로1216번길 6-169717196580000580000
2122보령동양041-931-3000충남 보령시 중앙로 187-66, (대천동)16165390561000561000
2223(자)천안대성041-568-7070충남 천안시 동남구 풍세로 839, (용곡동, 대성자동차운전전문학원)10284196754100754100
2324용화041-549-8891충남 아산시 시민로 215, (용화동, 용화자동차학원)8269195755000755000
2425서해041-953-3468충남 서천군 종천면 종판로 62, (서해자동차운전학원)9934196595000595000
2526(주)삼성041-531-2255충남 아산시 온천대로 1790-12, (남동)9413192755000755000