Overview

Dataset statistics

Number of variables10
Number of observations104
Missing cells24
Missing cells (%)2.3%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory8.7 KiB
Average record size in memory85.3 B

Variable types

Numeric3
Text5
Categorical1
DateTime1

Dataset

Description충청남도 보령시의 대기배출시설현황(업체명, 소재지 주소, 업종, 종별, 전화번호 등의 항목을 제공)에 대한 데이터입니다.
URLhttps://www.data.go.kr/data/15083824/fileData.do

Alerts

데이터기준일자 has constant value ""Constant
도로명주소 has 12 (11.5%) missing valuesMissing
전화번호 has 12 (11.5%) missing valuesMissing
연번 has unique valuesUnique

Reproduction

Analysis started2023-12-12 20:03:28.075748
Analysis finished2023-12-12 20:03:30.210257
Duration2.13 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

연번
Real number (ℝ)

UNIQUE 

Distinct104
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean52.5
Minimum1
Maximum104
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.0 KiB
2023-12-13T05:03:30.291363image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile6.15
Q126.75
median52.5
Q378.25
95-th percentile98.85
Maximum104
Range103
Interquartile range (IQR)51.5

Descriptive statistics

Standard deviation30.166206
Coefficient of variation (CV)0.5745944
Kurtosis-1.2
Mean52.5
Median Absolute Deviation (MAD)26
Skewness0
Sum5460
Variance910
MonotonicityStrictly increasing
2023-12-13T05:03:30.444826image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1 1
 
1.0%
54 1
 
1.0%
78 1
 
1.0%
77 1
 
1.0%
76 1
 
1.0%
75 1
 
1.0%
74 1
 
1.0%
73 1
 
1.0%
72 1
 
1.0%
71 1
 
1.0%
Other values (94) 94
90.4%
ValueCountFrequency (%)
1 1
1.0%
2 1
1.0%
3 1
1.0%
4 1
1.0%
5 1
1.0%
6 1
1.0%
7 1
1.0%
8 1
1.0%
9 1
1.0%
10 1
1.0%
ValueCountFrequency (%)
104 1
1.0%
103 1
1.0%
102 1
1.0%
101 1
1.0%
100 1
1.0%
99 1
1.0%
98 1
1.0%
97 1
1.0%
96 1
1.0%
95 1
1.0%

업체명
Text

Distinct102
Distinct (%)98.1%
Missing0
Missing (%)0.0%
Memory size964.0 B
2023-12-13T05:03:30.665008image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length35
Median length19
Mean length9.5865385
Min length3

Characters and Unicode

Total characters997
Distinct characters207
Distinct categories9 ?
Distinct scripts3 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique100 ?
Unique (%)96.2%

Sample

1st row영보연탄
2nd row보령자동차공업사
3rd row㈜보령레미콘
4th row해태스치로폴
5th row현대시멘트㈜
ValueCountFrequency (%)
주식회사 4
 
3.2%
삼원환경산업㈜ 2
 
1.6%
보령시 2
 
1.6%
한국가스공사 2
 
1.6%
전북지역본부 2
 
1.6%
만세보령농협쌀조합공동사업법인 2
 
1.6%
㈜케이디에프 1
 
0.8%
㈜대천리조트 1
 
0.8%
에디온 1
 
0.8%
씨엠디기술단 1
 
0.8%
Other values (107) 107
85.6%
2023-12-13T05:03:31.040700image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
㈜ 50
 
5.0%
업 34
 
3.4%
사 32
 
3.2%
보 30
 
3.0%
공 30
 
3.0%
령 26
 
2.6%
1 24
 
2.4%
동 22
 
2.2%
21
 
2.1%
스 21
 
2.1%
Other values (197) 707
70.9%

Most occurring categories

ValueCountFrequency (%)
Other Letter 811
81.3%
Decimal Number 82
 
8.2%
Other Symbol 50
 
5.0%
Space Separator 21
 
2.1%
Dash Punctuation 10
 
1.0%
Close Punctuation 10
 
1.0%
Open Punctuation 10
 
1.0%
Uppercase Letter 2
 
0.2%
Other Punctuation 1
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
업 34
 
4.2%
사 32
 
3.9%
보 30
 
3.7%
공 30
 
3.7%
령 26
 
3.2%
동 22
 
2.7%
스 21
 
2.6%
이 17
 
2.1%
에 17
 
2.1%
산 16
 
2.0%
Other values (179) 566
69.8%
Decimal Number
ValueCountFrequency (%)
1 24
29.3%
0 19
23.2%
6 8
 
9.8%
9 8
 
9.8%
4 7
 
8.5%
5 6
 
7.3%
7 6
 
7.3%
2 4
 
4.9%
Close Punctuation
ValueCountFrequency (%)
) 9
90.0%
] 1
 
10.0%
Open Punctuation
ValueCountFrequency (%)
( 9
90.0%
[ 1
 
10.0%
Uppercase Letter
ValueCountFrequency (%)
A 1
50.0%
F 1
50.0%
Other Symbol
ValueCountFrequency (%)
㈜ 50
100.0%
Space Separator
ValueCountFrequency (%)
21
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 10
100.0%
Other Punctuation
ValueCountFrequency (%)
, 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 861
86.4%
Common 134
 
13.4%
Latin 2
 
0.2%

Most frequent character per script

Hangul
ValueCountFrequency (%)
㈜ 50
 
5.8%
업 34
 
3.9%
사 32
 
3.7%
보 30
 
3.5%
공 30
 
3.5%
령 26
 
3.0%
동 22
 
2.6%
스 21
 
2.4%
이 17
 
2.0%
에 17
 
2.0%
Other values (180) 582
67.6%
Common
ValueCountFrequency (%)
1 24
17.9%
21
15.7%
0 19
14.2%
- 10
7.5%
) 9
 
6.7%
( 9
 
6.7%
6 8
 
6.0%
9 8
 
6.0%
4 7
 
5.2%
5 6
 
4.5%
Other values (5) 13
9.7%
Latin
ValueCountFrequency (%)
A 1
50.0%
F 1
50.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 811
81.3%
ASCII 136
 
13.6%
None 50
 
5.0%

Most frequent character per block

None
ValueCountFrequency (%)
㈜ 50
100.0%
Hangul
ValueCountFrequency (%)
업 34
 
4.2%
사 32
 
3.9%
보 30
 
3.7%
공 30
 
3.7%
령 26
 
3.2%
동 22
 
2.7%
스 21
 
2.6%
이 17
 
2.1%
에 17
 
2.1%
산 16
 
2.0%
Other values (179) 566
69.8%
ASCII
ValueCountFrequency (%)
1 24
17.6%
21
15.4%
0 19
14.0%
- 10
7.4%
) 9
 
6.6%
( 9
 
6.6%
6 8
 
5.9%
9 8
 
5.9%
4 7
 
5.1%
5 6
 
4.4%
Other values (7) 15
11.0%

도로명주소
Text

MISSING 

Distinct91
Distinct (%)98.9%
Missing12
Missing (%)11.5%
Memory size964.0 B
2023-12-13T05:03:31.413332image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length30
Median length25
Mean length20.336957
Min length15

Characters and Unicode

Total characters1871
Distinct characters115
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

Unique90 ?
Unique (%)97.8%

Sample

1st row충청남도 보령시 청라면 냉풍욕장길 15
2nd row충청남도 보령시 중앙로 33
3rd row충청남도 보령시 미산면 도화담안길 62-12 한일레미콘
4th row충청남도 보령시 청소면 비야들길 59
5th row충청남도 보령시 웅천읍 구장터1길 57
ValueCountFrequency (%)
충청남도 92
21.3%
보령시 92
21.3%
남포면 12
 
2.8%
주교면 11
 
2.5%
웅천읍 11
 
2.5%
천북면 8
 
1.9%
청소면 6
 
1.4%
관창공단길 6
 
1.4%
보령남로 5
 
1.2%
산업단지길 5
 
1.2%
Other values (137) 184
42.6%
2023-12-13T05:03:31.915507image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
341
18.2%
남 110
 
5.9%
청 102
 
5.5%
보 101
 
5.4%
령 98
 
5.2%
충 96
 
5.1%
도 95
 
5.1%
시 92
 
4.9%
1 53
 
2.8%
면 51
 
2.7%
Other values (105) 732
39.1%

Most occurring categories

ValueCountFrequency (%)
Other Letter 1216
65.0%
Space Separator 341
 
18.2%
Decimal Number 293
 
15.7%
Dash Punctuation 21
 
1.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
남 110
 
9.0%
청 102
 
8.4%
보 101
 
8.3%
령 98
 
8.1%
충 96
 
7.9%
도 95
 
7.8%
시 92
 
7.6%
면 51
 
4.2%
길 46
 
3.8%
로 46
 
3.8%
Other values (93) 379
31.2%
Decimal Number
ValueCountFrequency (%)
1 53
18.1%
2 45
15.4%
3 38
13.0%
4 33
11.3%
6 27
9.2%
7 22
7.5%
5 22
7.5%
9 21
 
7.2%
0 16
 
5.5%
8 16
 
5.5%
Space Separator
ValueCountFrequency (%)
341
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 21
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 1216
65.0%
Common 655
35.0%

Most frequent character per script

Hangul
ValueCountFrequency (%)
남 110
 
9.0%
청 102
 
8.4%
보 101
 
8.3%
령 98
 
8.1%
충 96
 
7.9%
도 95
 
7.8%
시 92
 
7.6%
면 51
 
4.2%
길 46
 
3.8%
로 46
 
3.8%
Other values (93) 379
31.2%
Common
ValueCountFrequency (%)
341
52.1%
1 53
 
8.1%
2 45
 
6.9%
3 38
 
5.8%
4 33
 
5.0%
6 27
 
4.1%
7 22
 
3.4%
5 22
 
3.4%
- 21
 
3.2%
9 21
 
3.2%
Other values (2) 32
 
4.9%

Most occurring blocks

ValueCountFrequency (%)
Hangul 1216
65.0%
ASCII 655
35.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
341
52.1%
1 53
 
8.1%
2 45
 
6.9%
3 38
 
5.8%
4 33
 
5.0%
6 27
 
4.1%
7 22
 
3.4%
5 22
 
3.4%
- 21
 
3.2%
9 21
 
3.2%
Other values (2) 32
 
4.9%
Hangul
ValueCountFrequency (%)
남 110
 
9.0%
청 102
 
8.4%
보 101
 
8.3%
령 98
 
8.1%
충 96
 
7.9%
도 95
 
7.8%
시 92
 
7.6%
면 51
 
4.2%
길 46
 
3.8%
로 46
 
3.8%
Other values (93) 379
31.2%

지번주소
Text

Distinct103
Distinct (%)99.0%
Missing0
Missing (%)0.0%
Memory size964.0 B
2023-12-13T05:03:32.243767image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length50
Median length33
Mean length21.653846
Min length15

Characters and Unicode

Total characters2252
Distinct characters95
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

Unique102 ?
Unique (%)98.1%

Sample

1st row충청남도 보령시 청라면 의평리 238-1
2nd row충청남도 보령시 동대동 835-5
3rd row충청남도 보령시 미산면 도화담 310-2
4th row충청남도 보령시 청소면 야현리 35-4
5th row충청남도 보령시 주산면 창암리 산49
ValueCountFrequency (%)
충청남도 104
20.6%
보령시 104
20.6%
웅천읍 13
 
2.6%
남포면 12
 
2.4%
주교면 12
 
2.4%
오천면 10
 
2.0%
관창리 9
 
1.8%
천북면 9
 
1.8%
청소면 8
 
1.6%
명천동 8
 
1.6%
Other values (163) 217
42.9%
2023-12-13T05:03:32.808812image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
402
17.9%
남 117
 
5.2%
청 115
 
5.1%
보 111
 
4.9%
도 106
 
4.7%
령 105
 
4.7%
충 104
 
4.6%
시 104
 
4.6%
- 88
 
3.9%
1 83
 
3.7%
Other values (85) 917
40.7%

Most occurring categories

ValueCountFrequency (%)
Other Letter 1309
58.1%
Decimal Number 436
 
19.4%
Space Separator 402
 
17.9%
Dash Punctuation 88
 
3.9%
Other Punctuation 7
 
0.3%
Open Punctuation 5
 
0.2%
Close Punctuation 5
 
0.2%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
남 117
 
8.9%
청 115
 
8.8%
보 111
 
8.5%
도 106
 
8.1%
령 105
 
8.0%
충 104
 
7.9%
시 104
 
7.9%
리 79
 
6.0%
면 66
 
5.0%
천 46
 
3.5%
Other values (70) 356
27.2%
Decimal Number
ValueCountFrequency (%)
1 83
19.0%
2 64
14.7%
4 48
11.0%
3 46
10.6%
5 44
10.1%
0 37
8.5%
7 31
 
7.1%
6 30
 
6.9%
9 29
 
6.7%
8 24
 
5.5%
Space Separator
ValueCountFrequency (%)
402
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 88
100.0%
Other Punctuation
ValueCountFrequency (%)
, 7
100.0%
Open Punctuation
ValueCountFrequency (%)
( 5
100.0%
Close Punctuation
ValueCountFrequency (%)
) 5
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 1309
58.1%
Common 943
41.9%

Most frequent character per script

Hangul
ValueCountFrequency (%)
남 117
 
8.9%
청 115
 
8.8%
보 111
 
8.5%
도 106
 
8.1%
령 105
 
8.0%
충 104
 
7.9%
시 104
 
7.9%
리 79
 
6.0%
면 66
 
5.0%
천 46
 
3.5%
Other values (70) 356
27.2%
Common
ValueCountFrequency (%)
402
42.6%
- 88
 
9.3%
1 83
 
8.8%
2 64
 
6.8%
4 48
 
5.1%
3 46
 
4.9%
5 44
 
4.7%
0 37
 
3.9%
7 31
 
3.3%
6 30
 
3.2%
Other values (5) 70
 
7.4%

Most occurring blocks

ValueCountFrequency (%)
Hangul 1309
58.1%
ASCII 943
41.9%

Most frequent character per block

ASCII
ValueCountFrequency (%)
402
42.6%
- 88
 
9.3%
1 83
 
8.8%
2 64
 
6.8%
4 48
 
5.1%
3 46
 
4.9%
5 44
 
4.7%
0 37
 
3.9%
7 31
 
3.3%
6 30
 
3.2%
Other values (5) 70
 
7.4%
Hangul
ValueCountFrequency (%)
남 117
 
8.9%
청 115
 
8.8%
보 111
 
8.5%
도 106
 
8.1%
령 105
 
8.0%
충 104
 
7.9%
시 104
 
7.9%
리 79
 
6.0%
면 66
 
5.0%
천 46
 
3.5%
Other values (70) 356
27.2%

위도
Real number (ℝ)

Distinct103
Distinct (%)99.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean36.351087
Minimum36.197793
Maximum36.497344
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.0 KiB
2023-12-13T05:03:33.301496image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum36.197793
5-th percentile36.217901
Q136.302651
median36.356026
Q336.404652
95-th percentile36.472251
Maximum36.497344
Range0.29955072
Interquartile range (IQR)0.10200121

Descriptive statistics

Standard deviation0.07756019
Coefficient of variation (CV)0.0021336415
Kurtosis-0.72787624
Mean36.351087
Median Absolute Deviation (MAD)0.052610931
Skewness-0.13759008
Sum3780.5131
Variance0.006015583
MonotonicityNot monotonic
2023-12-13T05:03:33.490318image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
36.2995916487 2
 
1.9%
36.3879868468 1
 
1.0%
36.3772422022 1
 
1.0%
36.455994 1
 
1.0%
36.332424 1
 
1.0%
36.414154 1
 
1.0%
36.4421862457 1
 
1.0%
36.457355733 1
 
1.0%
36.394041 1
 
1.0%
36.4887742457 1
 
1.0%
Other values (93) 93
89.4%
ValueCountFrequency (%)
36.1977928044 1
1.0%
36.199365 1
1.0%
36.201375 1
1.0%
36.210834 1
1.0%
36.2168951684 1
1.0%
36.2169872557 1
1.0%
36.2230777158 1
1.0%
36.227977741 1
1.0%
36.2287550328 1
1.0%
36.2343372413 1
1.0%
ValueCountFrequency (%)
36.4973435251 1
1.0%
36.4956313372 1
1.0%
36.4932689385 1
1.0%
36.4917317339 1
1.0%
36.4887742457 1
1.0%
36.4734901397 1
1.0%
36.4652312903 1
1.0%
36.457355733 1
1.0%
36.4566644455 1
1.0%
36.455994 1
1.0%

경도
Real number (ℝ)

Distinct103
Distinct (%)99.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean126.57325
Minimum126.44143
Maximum126.675
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.0 KiB
2023-12-13T05:03:33.661737image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum126.44143
5-th percentile126.49323
Q1126.55579
median126.57784
Q3126.59842
95-th percentile126.64557
Maximum126.675
Range0.23356574
Interquartile range (IQR)0.042631844

Descriptive statistics

Standard deviation0.043168345
Coefficient of variation (CV)0.00034105426
Kurtosis0.29082369
Mean126.57325
Median Absolute Deviation (MAD)0.021304849
Skewness-0.38554473
Sum13163.618
Variance0.001863506
MonotonicityNot monotonic
2023-12-13T05:03:33.809116image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
126.5604491666 2
 
1.9%
126.6582210717 1
 
1.0%
126.5742392826 1
 
1.0%
126.588305 1
 
1.0%
126.622748 1
 
1.0%
126.496255 1
 
1.0%
126.586467289 1
 
1.0%
126.5903931731 1
 
1.0%
126.576237 1
 
1.0%
126.5244968907 1
 
1.0%
Other values (93) 93
89.4%
ValueCountFrequency (%)
126.4414312643 1
1.0%
126.487797 1
1.0%
126.4883974495 1
1.0%
126.4885333715 1
1.0%
126.4910538991 1
1.0%
126.4926908005 1
1.0%
126.496255 1
1.0%
126.5020966973 1
1.0%
126.5061924342 1
1.0%
126.5064696178 1
1.0%
ValueCountFrequency (%)
126.674997 1
1.0%
126.6582210717 1
1.0%
126.6560471459 1
1.0%
126.6530049525 1
1.0%
126.6525452202 1
1.0%
126.6483242787 1
1.0%
126.6299771069 1
1.0%
126.6262019598 1
1.0%
126.625427129 1
1.0%
126.625131 1
1.0%

업종
Text

Distinct68
Distinct (%)65.4%
Missing0
Missing (%)0.0%
Memory size964.0 B
2023-12-13T05:03:34.027295image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length31
Median length21
Mean length13.288462
Min length3

Characters and Unicode

Total characters1382
Distinct characters151
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

Unique52 ?
Unique (%)50.0%

Sample

1st row코크스 및 연탄제조시설
2nd row기타 비금속 광물제품 제조시설
3rd row비료 및 질소화합물제조시설
4th row운수장비 수선 및 세차또는 세척시설
5th row운수장비 수선 및 세차또는 세척시설
ValueCountFrequency (%)
및 41
 
14.1%
세척시설 12
 
4.1%
제조업 12
 
4.1%
운수장비 11
 
3.8%
수선 10
 
3.4%
세차또는 10
 
3.4%
기타 9
 
3.1%
제조시설 7
 
2.4%
그 6
 
2.1%
비금속 5
 
1.7%
Other values (109) 167
57.6%
2023-12-13T05:03:34.400327image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
186
 
13.5%
제 81
 
5.9%
업 72
 
5.2%
조 53
 
3.8%
및 46
 
3.3%
물 37
 
2.7%
수 35
 
2.5%
기 32
 
2.3%
비 32
 
2.3%
시 31
 
2.2%
Other values (141) 777
56.2%

Most occurring categories

ValueCountFrequency (%)
Other Letter 1158
83.8%
Space Separator 186
 
13.5%
Other Punctuation 12
 
0.9%
Open Punctuation 9
 
0.7%
Close Punctuation 9
 
0.7%
Decimal Number 6
 
0.4%
Math Symbol 2
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
제 81
 
7.0%
업 72
 
6.2%
조 53
 
4.6%
및 46
 
4.0%
물 37
 
3.2%
수 35
 
3.0%
기 32
 
2.8%
비 32
 
2.8%
시 31
 
2.7%
품 31
 
2.7%
Other values (133) 708
61.1%
Other Punctuation
ValueCountFrequency (%)
, 11
91.7%
. 1
 
8.3%
Decimal Number
ValueCountFrequency (%)
2 4
66.7%
3 2
33.3%
Space Separator
ValueCountFrequency (%)
186
100.0%
Open Punctuation
ValueCountFrequency (%)
( 9
100.0%
Close Punctuation
ValueCountFrequency (%)
) 9
100.0%
Math Symbol
ValueCountFrequency (%)
+ 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 1158
83.8%
Common 224
 
16.2%

Most frequent character per script

Hangul
ValueCountFrequency (%)
제 81
 
7.0%
업 72
 
6.2%
조 53
 
4.6%
및 46
 
4.0%
물 37
 
3.2%
수 35
 
3.0%
기 32
 
2.8%
비 32
 
2.8%
시 31
 
2.7%
품 31
 
2.7%
Other values (133) 708
61.1%
Common
ValueCountFrequency (%)
186
83.0%
, 11
 
4.9%
( 9
 
4.0%
) 9
 
4.0%
2 4
 
1.8%
3 2
 
0.9%
+ 2
 
0.9%
. 1
 
0.4%

Most occurring blocks

ValueCountFrequency (%)
Hangul 1158
83.8%
ASCII 224
 
16.2%

Most frequent character per block

ASCII
ValueCountFrequency (%)
186
83.0%
, 11
 
4.9%
( 9
 
4.0%
) 9
 
4.0%
2 4
 
1.8%
3 2
 
0.9%
+ 2
 
0.9%
. 1
 
0.4%
Hangul
ValueCountFrequency (%)
제 81
 
7.0%
업 72
 
6.2%
조 53
 
4.6%
및 46
 
4.0%
물 37
 
3.2%
수 35
 
3.0%
기 32
 
2.8%
비 32
 
2.8%
시 31
 
2.7%
품 31
 
2.7%
Other values (133) 708
61.1%

종별
Categorical

Distinct3
Distinct (%)2.9%
Missing0
Missing (%)0.0%
Memory size964.0 B
5
54 
4
47 
3
 
3

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row5
2nd row5
3rd row4
4th row4
5th row5

Common Values

ValueCountFrequency (%)
5 54
51.9%
4 47
45.2%
3 3
 
2.9%

Length

2023-12-13T05:03:34.559458image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T05:03:34.685836image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
5 54
51.9%
4 47
45.2%
3 3
 
2.9%

전화번호
Text

MISSING 

Distinct89
Distinct (%)96.7%
Missing12
Missing (%)11.5%
Memory size964.0 B
2023-12-13T05:03:34.942844image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length12
Median length12
Mean length12
Min length12

Characters and Unicode

Total characters1104
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

Unique87 ?
Unique (%)94.6%

Sample

1st row041-932-8050
2nd row041-933-3454
3rd row041-933-6413
4th row041-934-2568
5th row041-934-4665
ValueCountFrequency (%)
041-931-1345 3
 
3.3%
041-931-2513 2
 
2.2%
041-931-7291 1
 
1.1%
041-932-5959 1
 
1.1%
041-930-9862 1
 
1.1%
041-931-6320 1
 
1.1%
041-932-9994 1
 
1.1%
041-932-2212 1
 
1.1%
041-934-0142 1
 
1.1%
041-931-2476 1
 
1.1%
Other values (79) 79
85.9%
2023-12-13T05:03:35.447016image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
- 184
16.7%
1 167
15.1%
4 143
13.0%
0 140
12.7%
3 137
12.4%
9 118
10.7%
2 55
 
5.0%
5 51
 
4.6%
6 44
 
4.0%
8 42
 
3.8%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 920
83.3%
Dash Punctuation 184
 
16.7%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 167
18.2%
4 143
15.5%
0 140
15.2%
3 137
14.9%
9 118
12.8%
2 55
 
6.0%
5 51
 
5.5%
6 44
 
4.8%
8 42
 
4.6%
7 23
 
2.5%
Dash Punctuation
ValueCountFrequency (%)
- 184
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 1104
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
- 184
16.7%
1 167
15.1%
4 143
13.0%
0 140
12.7%
3 137
12.4%
9 118
10.7%
2 55
 
5.0%
5 51
 
4.6%
6 44
 
4.0%
8 42
 
3.8%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1104
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
- 184
16.7%
1 167
15.1%
4 143
13.0%
0 140
12.7%
3 137
12.4%
9 118
10.7%
2 55
 
5.0%
5 51
 
4.6%
6 44
 
4.0%
8 42
 
3.8%

데이터기준일자
Date

CONSTANT 

Distinct1
Distinct (%)1.0%
Missing0
Missing (%)0.0%
Memory size964.0 B
Minimum2023-05-23 00:00:00
Maximum2023-05-23 00:00:00
2023-12-13T05:03:35.627695image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T05:03:35.750433image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=1)

Interactions

2023-12-13T05:03:29.602352image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T05:03:28.981092image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T05:03:29.293244image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T05:03:29.686518image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T05:03:29.071542image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T05:03:29.394536image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T05:03:29.774692image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T05:03:29.187303image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T05:03:29.492709image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-13T05:03:35.842340image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
연번도로명주소위도경도업종종별전화번호
연번1.0000.9500.0000.0250.9110.0910.972
도로명주소0.9501.0001.0001.0001.0001.0001.000
위도0.0001.0001.0000.6900.7480.1260.862
경도0.0251.0000.6901.0000.6360.3550.000
업종0.9111.0000.7480.6361.0000.9070.998
종별0.0911.0000.1260.3550.9071.0000.847
전화번호0.9721.0000.8620.0000.9980.8471.000
2023-12-13T05:03:35.991467image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
연번위도경도종별
연번1.0000.062-0.1800.043
위도0.0621.000-0.3140.066
경도-0.180-0.3141.0000.218
종별0.0430.0660.2181.000

Missing values

2023-12-13T05:03:29.899197image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-13T05:03:30.059764image/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.
2023-12-13T05:03:30.159639image/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

연번업체명도로명주소지번주소위도경도업종종별전화번호데이터기준일자
01영보연탄충청남도 보령시 청라면 냉풍욕장길 15충청남도 보령시 청라면 의평리 238-136.387987126.658221코크스 및 연탄제조시설5041-932-80502023-05-23
12보령자동차공업사충청남도 보령시 중앙로 33충청남도 보령시 동대동 835-536.374564126.598172기타 비금속 광물제품 제조시설5041-933-34542023-05-23
23㈜보령레미콘충청남도 보령시 미산면 도화담안길 62-12 한일레미콘충청남도 보령시 미산면 도화담 310-236.300744126.674997비료 및 질소화합물제조시설4041-933-64132023-05-23
34해태스치로폴충청남도 보령시 청소면 비야들길 59충청남도 보령시 청소면 야현리 35-436.440692126.594913운수장비 수선 및 세차또는 세척시설4041-934-25682023-05-23
45현대시멘트㈜<NA>충청남도 보령시 주산면 창암리 산4936.210834126.618764운수장비 수선 및 세차또는 세척시설5041-934-46652023-05-23
56한국다기화학충청남도 보령시 웅천읍 구장터1길 57충청남도 보령시 웅천읍 대천리 47-136.234337126.593663운수장비 수선 및 세차또는 세척시설5041-933-93082023-05-23
67제일레미콘㈜<NA>충청남도 보령시 오천면 교성리 산18-1(221-6)36.440108126.553499비알콜성 음료 및 얼음 제조시설5041-931-22312023-05-23
78㈜모헨즈보령공장<NA>충청남도 보령시 청소면 장곡리 759-4(750-4)36.430118126.576398운수장비 수선 및 세차또는 세척시설4041-934-71352023-05-23
89주식회사 한솔기업㈜충청남도 보령시 옥마로 124충청남도 보령시 명천동 1-136.342003126.625131운수장비 수선 및 세차또는 세척시설4041-934-76602023-05-23
910대왕자동차공업사충청남도 보령시 남포면 보령남로 472충청남도 보령시 남포면 옥동리 270-136.306585126.604503운수장비 수선 및 세차또는 세척시설5041-934-92002023-05-23
연번업체명도로명주소지번주소위도경도업종종별전화번호데이터기준일자
9495만세보령농협쌀조합공동사업법인-청소(164511-0009197)충청남도 보령시 청소면 통골길 1충청남도 보령시 청소면 야현리 528-136.439997126.588018곡물 도정업5041-931-13452023-05-23
9596만세보령농협쌀조합공동사업법인-청라(164511-0009197)<NA>충청남도 보령시 청라면 황룡리 832-836.416798126.656047곡물 도정업5041-931-13452023-05-23
9697㈜보난자마이닝충청남도 보령시 웅천읍 석재단지길 54충청남도 보령시 웅천읍 대창리 963-136.227978126.608348그 밖의 비금속광물제품 제조업5<NA>2023-05-23
9798중앙중공업충청남도 보령시 청룡굴길 46충청남도 보령시 명천동 742-1636.330735126.616767자동차종합수리업5041-932-37352023-05-23
9899보령시 하수처리시설충청남도 보령시 대천방조제로 322충청남도 보령시 대천동 845-236.355937126.556642하수처리4041-930-31142023-05-23
99100엠에스산업충청남도 보령시 성주면 성주산로 778충청남도 보령시 성주면 개화리 381-536.303286126.652545폐기물종합재활용업4<NA>2023-05-23
100101㈜케이디에프충청남도 보령시 주교면 관창공단길 129충청남도 보령시 주교면 관창리 1224-936.375937126.574539합성고무, 플라스틱물질 및 플라스틱제품 제조시설 등4041-549-03112023-05-23
101102주택관리공단㈜ 명천2관리소충청남도 보령시 주공로 50충청남도 보령시 명천동 41336.342553126.603428아파트(난방)4041-936-06532023-05-23
102103서울시교육청학생교육원충청남도 보령시 해수욕장3길 26충청남도 보령시 신흑동 205536.303545126.519216부동산업(임대)5041-931-25132023-05-23
103104충청북도해양교육원충청남도 보령시 해수욕장13길 14-17충청남도 보령시 신흑동 2218-136.319833126.510652부동산업(임대)4041-931-25132023-05-23