Overview

Dataset statistics

Number of variables7
Number of observations866
Missing cells47
Missing cells (%)0.8%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory49.2 KiB
Average record size in memory58.2 B

Variable types

Numeric2
Text4
Categorical1

Dataset

Description경기도 부천시 관내의 전문건설업 현황에 대한 데이터로 업체명, 업종, 소재지(도로명, 지번), 우편번호, 전화번호 등의 자료를 제공합니다.
Author경기도 부천시
URLhttps://www.data.go.kr/data/3079287/fileData.do

Alerts

전화번호 has 45 (5.2%) missing valuesMissing
번호 has unique valuesUnique

Reproduction

Analysis started2023-12-12 04:15:35.057317
Analysis finished2023-12-12 04:15:36.623278
Duration1.57 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

번호
Real number (ℝ)

UNIQUE 

Distinct866
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean433.5
Minimum1
Maximum866
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size7.7 KiB
2023-12-12T13:15:37.070255image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile44.25
Q1217.25
median433.5
Q3649.75
95-th percentile822.75
Maximum866
Range865
Interquartile range (IQR)432.5

Descriptive statistics

Standard deviation250.13696
Coefficient of variation (CV)0.57701721
Kurtosis-1.2
Mean433.5
Median Absolute Deviation (MAD)216.5
Skewness0
Sum375411
Variance62568.5
MonotonicityStrictly increasing
2023-12-12T13:15:37.258901image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1 1
 
0.1%
583 1
 
0.1%
572 1
 
0.1%
573 1
 
0.1%
574 1
 
0.1%
575 1
 
0.1%
576 1
 
0.1%
577 1
 
0.1%
578 1
 
0.1%
579 1
 
0.1%
Other values (856) 856
98.8%
ValueCountFrequency (%)
1 1
0.1%
2 1
0.1%
3 1
0.1%
4 1
0.1%
5 1
0.1%
6 1
0.1%
7 1
0.1%
8 1
0.1%
9 1
0.1%
10 1
0.1%
ValueCountFrequency (%)
866 1
0.1%
865 1
0.1%
864 1
0.1%
863 1
0.1%
862 1
0.1%
861 1
0.1%
860 1
0.1%
859 1
0.1%
858 1
0.1%
857 1
0.1%

업체명
Text

Distinct700
Distinct (%)80.8%
Missing0
Missing (%)0.0%
Memory size6.9 KiB
2023-12-12T13:15:37.578932image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length19
Median length16
Mean length7.3556582
Min length2

Characters and Unicode

Total characters6370
Distinct characters328
Distinct categories6 ?
Distinct scripts3 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique568 ?
Unique (%)65.6%

Sample

1st row(유)태양엔지니어링
2nd row(주)가나건설
3rd row(주)가화건설
4th row(주)강남건설
5th row(주)강남건설
ValueCountFrequency (%)
경기건설(주 5
 
0.6%
지성건설산업(주 5
 
0.6%
남경(주 4
 
0.5%
주)서원양행 4
 
0.5%
경일건설(주 4
 
0.5%
청호건설(주 4
 
0.5%
상무공영(주 3
 
0.3%
서환건설(주 3
 
0.3%
성마기업(주 3
 
0.3%
비케이건설(주 3
 
0.3%
Other values (690) 828
95.6%
2023-12-12T13:15:38.137617image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
주 676
 
10.6%
( 641
 
10.1%
) 641
 
10.1%
설 311
 
4.9%
건 278
 
4.4%
이 168
 
2.6%
스 104
 
1.6%
비 97
 
1.5%
지 95
 
1.5%
성 92
 
1.4%
Other values (318) 3267
51.3%

Most occurring categories

ValueCountFrequency (%)
Other Letter 5051
79.3%
Open Punctuation 641
 
10.1%
Close Punctuation 641
 
10.1%
Uppercase Letter 30
 
0.5%
Decimal Number 4
 
0.1%
Other Punctuation 3
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
주 676
 
13.4%
설 311
 
6.2%
건 278
 
5.5%
이 168
 
3.3%
스 104
 
2.1%
비 97
 
1.9%
지 95
 
1.9%
성 92
 
1.8%
에 88
 
1.7%
엔 77
 
1.5%
Other values (303) 3065
60.7%
Uppercase Letter
ValueCountFrequency (%)
G 8
26.7%
N 6
20.0%
E 6
20.0%
S 2
 
6.7%
D 2
 
6.7%
I 2
 
6.7%
H 1
 
3.3%
O 1
 
3.3%
K 1
 
3.3%
W 1
 
3.3%
Decimal Number
ValueCountFrequency (%)
1 2
50.0%
2 2
50.0%
Open Punctuation
ValueCountFrequency (%)
( 641
100.0%
Close Punctuation
ValueCountFrequency (%)
) 641
100.0%
Other Punctuation
ValueCountFrequency (%)
， 3
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 5051
79.3%
Common 1289
 
20.2%
Latin 30
 
0.5%

Most frequent character per script

Hangul
ValueCountFrequency (%)
주 676
 
13.4%
설 311
 
6.2%
건 278
 
5.5%
이 168
 
3.3%
스 104
 
2.1%
비 97
 
1.9%
지 95
 
1.9%
성 92
 
1.8%
에 88
 
1.7%
엔 77
 
1.5%
Other values (303) 3065
60.7%
Latin
ValueCountFrequency (%)
G 8
26.7%
N 6
20.0%
E 6
20.0%
S 2
 
6.7%
D 2
 
6.7%
I 2
 
6.7%
H 1
 
3.3%
O 1
 
3.3%
K 1
 
3.3%
W 1
 
3.3%
Common
ValueCountFrequency (%)
( 641
49.7%
) 641
49.7%
， 3
 
0.2%
1 2
 
0.2%
2 2
 
0.2%

Most occurring blocks

ValueCountFrequency (%)
Hangul 5051
79.3%
ASCII 1316
 
20.7%
None 3
 
< 0.1%

Most frequent character per block

Hangul
ValueCountFrequency (%)
주 676
 
13.4%
설 311
 
6.2%
건 278
 
5.5%
이 168
 
3.3%
스 104
 
2.1%
비 97
 
1.9%
지 95
 
1.9%
성 92
 
1.8%
에 88
 
1.7%
엔 77
 
1.5%
Other values (303) 3065
60.7%
ASCII
ValueCountFrequency (%)
( 641
48.7%
) 641
48.7%
G 8
 
0.6%
N 6
 
0.5%
E 6
 
0.5%
1 2
 
0.2%
2 2
 
0.2%
S 2
 
0.2%
D 2
 
0.2%
I 2
 
0.2%
Other values (4) 4
 
0.3%
None
ValueCountFrequency (%)
， 3
100.0%

업종
Categorical

Distinct14
Distinct (%)1.6%
Missing0
Missing (%)0.0%
Memory size6.9 KiB
가스난방공사업
200 
기계가스설비공사업
113 
실내건축공사업
99 
지반조성ㆍ포장공사업
80 
금속창호ㆍ지붕건축물조립공사업
70 
Other values (9)
304 

Length

Max length15
Median length13
Mean length9.4549654
Min length7

Unique

Unique1 ?
Unique (%)0.1%

Sample

1st row가스난방공사업
2nd row실내건축공사업
3rd row실내건축공사업
4th row구조물해체ㆍ비계공사업
5th row지반조성ㆍ포장공사업

Common Values

ValueCountFrequency (%)
가스난방공사업 200
23.1%
기계가스설비공사업 113
13.0%
실내건축공사업 99
11.4%
지반조성ㆍ포장공사업 80
 
9.2%
금속창호ㆍ지붕건축물조립공사업 70
 
8.1%
도장ㆍ습식ㆍ방수ㆍ석공사업 67
 
7.7%
상ㆍ하수도설비공사업 58
 
6.7%
철근ㆍ콘크리트공사업 46
 
5.3%
조경식재ㆍ시설물공사업 40
 
4.6%
구조물해체ㆍ비계공사업 38
 
4.4%
Other values (4) 55
 
6.4%

Length

2023-12-12T13:15:38.310690image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
가스난방공사업 200
23.1%
기계가스설비공사업 113
13.0%
실내건축공사업 99
11.4%
지반조성ㆍ포장공사업 80
 
9.2%
금속창호ㆍ지붕건축물조립공사업 70
 
8.1%
도장ㆍ습식ㆍ방수ㆍ석공사업 67
 
7.7%
상ㆍ하수도설비공사업 58
 
6.7%
철근ㆍ콘크리트공사업 46
 
5.3%
조경식재ㆍ시설물공사업 40
 
4.6%
구조물해체ㆍ비계공사업 38
 
4.4%
Other values (4) 55
 
6.4%

소재지(도로명)
Text

Distinct697
Distinct (%)80.6%
Missing1
Missing (%)0.1%
Memory size6.9 KiB
2023-12-12T13:15:38.622752image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length54
Median length44
Mean length29.652023
Min length19

Characters and Unicode

Total characters25649
Distinct characters235
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

Unique569 ?
Unique (%)65.8%

Sample

1st row경기도 부천시 계남로 277 (중동)
2nd row경기도 부천시 중동로147번길 39 102호 (중동)
3rd row경기도 부천시 상동로 109, 202호 (상동)
4th row경기도 부천시 은성로117번길 5-14 (괴안동)
5th row경기도 부천시 은성로117번길 5-14 (괴안동)
ValueCountFrequency (%)
경기도 864
 
15.8%
부천시 864
 
15.8%
상동 165
 
3.0%
중동 134
 
2.5%
1층 90
 
1.6%
심곡동 60
 
1.1%
길주로 60
 
1.1%
삼정동 53
 
1.0%
춘의동 47
 
0.9%
송내동 42
 
0.8%
Other values (991) 3076
56.4%
2023-12-12T13:15:39.134925image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
4590
 
17.9%
1 1134
 
4.4%
부 1060
 
4.1%
동 1040
 
4.1%
천 1015
 
4.0%
도 932
 
3.6%
경 896
 
3.5%
( 883
 
3.4%
) 883
 
3.4%
로 873
 
3.4%
Other values (225) 12343
48.1%

Most occurring categories

ValueCountFrequency (%)
Other Letter 13596
53.0%
Decimal Number 5384
 
21.0%
Space Separator 4590
 
17.9%
Open Punctuation 883
 
3.4%
Close Punctuation 883
 
3.4%
Dash Punctuation 172
 
0.7%
Other Punctuation 126
 
0.5%
Uppercase Letter 14
 
0.1%
Math Symbol 1
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
부 1060
 
7.8%
동 1040
 
7.6%
천 1015
 
7.5%
도 932
 
6.9%
경 896
 
6.6%
로 873
 
6.4%
시 870
 
6.4%
기 870
 
6.4%
길 563
 
4.1%
호 525
 
3.9%
Other values (200) 4952
36.4%
Decimal Number
ValueCountFrequency (%)
1 1134
21.1%
2 731
13.6%
0 687
12.8%
3 624
11.6%
4 492
9.1%
5 449
 
8.3%
7 389
 
7.2%
6 327
 
6.1%
8 285
 
5.3%
9 266
 
4.9%
Uppercase Letter
ValueCountFrequency (%)
B 6
42.9%
A 3
21.4%
C 2
 
14.3%
D 1
 
7.1%
T 1
 
7.1%
F 1
 
7.1%
Other Punctuation
ValueCountFrequency (%)
, 114
90.5%
， 10
 
7.9%
. 1
 
0.8%
/ 1
 
0.8%
Space Separator
ValueCountFrequency (%)
4590
100.0%
Open Punctuation
ValueCountFrequency (%)
( 883
100.0%
Close Punctuation
ValueCountFrequency (%)
) 883
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 172
100.0%
Math Symbol
ValueCountFrequency (%)
~ 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 13596
53.0%
Common 12039
46.9%
Latin 14
 
0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
부 1060
 
7.8%
동 1040
 
7.6%
천 1015
 
7.5%
도 932
 
6.9%
경 896
 
6.6%
로 873
 
6.4%
시 870
 
6.4%
기 870
 
6.4%
길 563
 
4.1%
호 525
 
3.9%
Other values (200) 4952
36.4%
Common
ValueCountFrequency (%)
4590
38.1%
1 1134
 
9.4%
( 883
 
7.3%
) 883
 
7.3%
2 731
 
6.1%
0 687
 
5.7%
3 624
 
5.2%
4 492
 
4.1%
5 449
 
3.7%
7 389
 
3.2%
Other values (9) 1177
 
9.8%
Latin
ValueCountFrequency (%)
B 6
42.9%
A 3
21.4%
C 2
 
14.3%
D 1
 
7.1%
T 1
 
7.1%
F 1
 
7.1%

Most occurring blocks

ValueCountFrequency (%)
Hangul 13596
53.0%
ASCII 12043
47.0%
None 10
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
4590
38.1%
1 1134
 
9.4%
( 883
 
7.3%
) 883
 
7.3%
2 731
 
6.1%
0 687
 
5.7%
3 624
 
5.2%
4 492
 
4.1%
5 449
 
3.7%
7 389
 
3.2%
Other values (14) 1181
 
9.8%
Hangul
ValueCountFrequency (%)
부 1060
 
7.8%
동 1040
 
7.6%
천 1015
 
7.5%
도 932
 
6.9%
경 896
 
6.6%
로 873
 
6.4%
시 870
 
6.4%
기 870
 
6.4%
길 563
 
4.1%
호 525
 
3.9%
Other values (200) 4952
36.4%
None
ValueCountFrequency (%)
， 10
100.0%

소재지(지번)
Text

Distinct703
Distinct (%)81.2%
Missing0
Missing (%)0.0%
Memory size6.9 KiB
2023-12-12T13:15:39.459862image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length43
Median length35
Mean length22.988453
Min length12

Characters and Unicode

Total characters19908
Distinct characters218
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

Unique576 ?
Unique (%)66.5%

Sample

1st row경기도 부천시 중동 1073-16
2nd row경기도 부천시 중동 768-12 102호
3rd row경기도 부천시 상동 534-3, 202호
4th row경기도 부천시 괴안동 236-2
5th row경기도 부천시 괴안동 236-2
ValueCountFrequency (%)
부천시 865
 
18.9%
경기도 686
 
15.0%
경기 177
 
3.9%
상동 165
 
3.6%
중동 136
 
3.0%
1층 91
 
2.0%
심곡동 56
 
1.2%
삼정동 54
 
1.2%
춘의동 49
 
1.1%
송내동 40
 
0.9%
Other values (948) 2252
49.3%
2023-12-12T13:15:39.964292image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
3705
18.6%
1 1316
 
6.6%
동 971
 
4.9%
부 902
 
4.5%
천 899
 
4.5%
시 872
 
4.4%
기 869
 
4.4%
경 865
 
4.3%
- 774
 
3.9%
도 728
 
3.7%
Other values (208) 8007
40.2%

Most occurring categories

ValueCountFrequency (%)
Other Letter 9795
49.2%
Decimal Number 5490
27.6%
Space Separator 3705
 
18.6%
Dash Punctuation 774
 
3.9%
Other Punctuation 82
 
0.4%
Close Punctuation 25
 
0.1%
Open Punctuation 23
 
0.1%
Uppercase Letter 13
 
0.1%
Math Symbol 1
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
동 971
 
9.9%
부 902
 
9.2%
천 899
 
9.2%
시 872
 
8.9%
기 869
 
8.9%
경 865
 
8.8%
도 728
 
7.4%
호 515
 
5.3%
층 234
 
2.4%
상 201
 
2.1%
Other values (183) 2739
28.0%
Decimal Number
ValueCountFrequency (%)
1 1316
24.0%
0 699
12.7%
2 662
12.1%
3 659
12.0%
5 528
9.6%
4 525
 
9.6%
6 348
 
6.3%
7 275
 
5.0%
8 275
 
5.0%
9 203
 
3.7%
Uppercase Letter
ValueCountFrequency (%)
B 6
46.2%
C 2
 
15.4%
A 2
 
15.4%
D 1
 
7.7%
F 1
 
7.7%
T 1
 
7.7%
Other Punctuation
ValueCountFrequency (%)
, 73
89.0%
， 7
 
8.5%
. 1
 
1.2%
/ 1
 
1.2%
Space Separator
ValueCountFrequency (%)
3705
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 774
100.0%
Close Punctuation
ValueCountFrequency (%)
) 25
100.0%
Open Punctuation
ValueCountFrequency (%)
( 23
100.0%
Math Symbol
ValueCountFrequency (%)
~ 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 10100
50.7%
Hangul 9795
49.2%
Latin 13
 
0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
동 971
 
9.9%
부 902
 
9.2%
천 899
 
9.2%
시 872
 
8.9%
기 869
 
8.9%
경 865
 
8.8%
도 728
 
7.4%
호 515
 
5.3%
층 234
 
2.4%
상 201
 
2.1%
Other values (183) 2739
28.0%
Common
ValueCountFrequency (%)
3705
36.7%
1 1316
 
13.0%
- 774
 
7.7%
0 699
 
6.9%
2 662
 
6.6%
3 659
 
6.5%
5 528
 
5.2%
4 525
 
5.2%
6 348
 
3.4%
7 275
 
2.7%
Other values (9) 609
 
6.0%
Latin
ValueCountFrequency (%)
B 6
46.2%
C 2
 
15.4%
A 2
 
15.4%
D 1
 
7.7%
F 1
 
7.7%
T 1
 
7.7%

Most occurring blocks

ValueCountFrequency (%)
ASCII 10106
50.8%
Hangul 9795
49.2%
None 7
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
3705
36.7%
1 1316
 
13.0%
- 774
 
7.7%
0 699
 
6.9%
2 662
 
6.6%
3 659
 
6.5%
5 528
 
5.2%
4 525
 
5.2%
6 348
 
3.4%
7 275
 
2.7%
Other values (14) 615
 
6.1%
Hangul
ValueCountFrequency (%)
동 971
 
9.9%
부 902
 
9.2%
천 899
 
9.2%
시 872
 
8.9%
기 869
 
8.9%
경 865
 
8.8%
도 728
 
7.4%
호 515
 
5.3%
층 234
 
2.4%
상 201
 
2.1%
Other values (183) 2739
28.0%
None
ValueCountFrequency (%)
， 7
100.0%

우편번호
Real number (ℝ)

Distinct254
Distinct (%)29.4%
Missing1
Missing (%)0.1%
Infinite0
Infinite (%)0.0%
Mean14568.398
Minimum11111
Maximum14786
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size7.7 KiB
2023-12-12T13:15:40.129936image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum11111
5-th percentile14428
Q114518
median14552
Q314634
95-th percentile14755
Maximum14786
Range3675
Interquartile range (IQR)116

Descriptive statistics

Standard deviation191.71135
Coefficient of variation (CV)0.013159399
Kurtosis243.71933
Mean14568.398
Median Absolute Deviation (MAD)65
Skewness-13.530063
Sum12601664
Variance36753.242
MonotonicityNot monotonic
2023-12-12T13:15:40.281374image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
14548 56
 
6.5%
14544 43
 
5.0%
14543 42
 
4.8%
14449 18
 
2.1%
14786 17
 
2.0%
14542 16
 
1.8%
14623 11
 
1.3%
14555 11
 
1.3%
14720 11
 
1.3%
14582 10
 
1.2%
Other values (244) 630
72.7%
ValueCountFrequency (%)
11111 2
0.2%
14401 3
0.3%
14405 2
0.2%
14406 3
0.3%
14407 1
 
0.1%
14408 1
 
0.1%
14409 3
0.3%
14412 1
 
0.1%
14414 1
 
0.1%
14415 1
 
0.1%
ValueCountFrequency (%)
14786 17
2.0%
14785 3
 
0.3%
14783 1
 
0.1%
14781 1
 
0.1%
14780 1
 
0.1%
14774 1
 
0.1%
14771 1
 
0.1%
14770 1
 
0.1%
14769 1
 
0.1%
14767 1
 
0.1%

전화번호
Text

MISSING 

Distinct655
Distinct (%)79.8%
Missing45
Missing (%)5.2%
Memory size6.9 KiB
2023-12-12T13:15:40.582985image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length14
Median length12
Mean length12.0743
Min length11

Characters and Unicode

Total characters9913
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

Unique523 ?
Unique (%)63.7%

Sample

1st row032-326-9002
2nd row032-656-2277
3rd row032-329-0095
4th row032-612-8801
5th row032-612-8801
ValueCountFrequency (%)
032-327-0991 5
 
0.6%
032-341-9867 5
 
0.6%
032-348-1050 4
 
0.5%
032-328-0681 4
 
0.5%
032-677-5500 4
 
0.5%
032-684-0027 4
 
0.5%
032-663-0033 4
 
0.5%
032-666-2142 3
 
0.4%
032-666-9500 3
 
0.4%
032-677-5111 3
 
0.4%
Other values (645) 782
95.2%
2023-12-12T13:15:41.140430image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
- 1642
16.6%
0 1491
15.0%
3 1471
14.8%
2 1435
14.5%
6 874
8.8%
7 613
 
6.2%
1 595
 
6.0%
5 541
 
5.5%
4 492
 
5.0%
8 447
 
4.5%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 8271
83.4%
Dash Punctuation 1642
 
16.6%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 1491
18.0%
3 1471
17.8%
2 1435
17.3%
6 874
10.6%
7 613
7.4%
1 595
 
7.2%
5 541
 
6.5%
4 492
 
5.9%
8 447
 
5.4%
9 312
 
3.8%
Dash Punctuation
ValueCountFrequency (%)
- 1642
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 9913
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
- 1642
16.6%
0 1491
15.0%
3 1471
14.8%
2 1435
14.5%
6 874
8.8%
7 613
 
6.2%
1 595
 
6.0%
5 541
 
5.5%
4 492
 
5.0%
8 447
 
4.5%

Most occurring blocks

ValueCountFrequency (%)
ASCII 9913
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
- 1642
16.6%
0 1491
15.0%
3 1471
14.8%
2 1435
14.5%
6 874
8.8%
7 613
 
6.2%
1 595
 
6.0%
5 541
 
5.5%
4 492
 
5.0%
8 447
 
4.5%

Interactions

2023-12-12T13:15:35.963181image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:15:35.734659image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:15:36.079167image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:15:35.830896image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-12T13:15:41.271546image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
번호업종우편번호
번호1.0000.3270.049
업종0.3271.0000.134
우편번호0.0490.1341.000
2023-12-12T13:15:41.399820image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
번호우편번호업종
번호1.000-0.0210.137
우편번호-0.0211.0000.012
업종0.1370.0121.000

Missing values

2023-12-12T13:15:36.252845image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-12T13:15:36.412559image/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.
2023-12-12T13:15:36.554173image/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

번호업체명업종소재지(도로명)소재지(지번)우편번호전화번호
01(유)태양엔지니어링가스난방공사업경기도 부천시 계남로 277 (중동)경기도 부천시 중동 1073-1614533032-326-9002
12(주)가나건설실내건축공사업경기도 부천시 중동로147번길 39 102호 (중동)경기도 부천시 중동 768-12 102호14608032-656-2277
23(주)가화건설실내건축공사업경기도 부천시 상동로 109, 202호 (상동)경기도 부천시 상동 534-3, 202호14543032-329-0095
34(주)강남건설구조물해체ㆍ비계공사업경기도 부천시 은성로117번길 5-14 (괴안동)경기도 부천시 괴안동 236-214698032-612-8801
45(주)강남건설지반조성ㆍ포장공사업경기도 부천시 은성로117번길 5-14 (괴안동)경기도 부천시 괴안동 236-214698032-612-8801
56(주)거륜에너텍지반조성ㆍ포장공사업경기도 부천시 부일로 287-26 우성빌딩 401호 (상동)경기도 부천시 상동 318 우성빌딩 401호14621032-653-8971
67(주)거륜에너텍기계가스설비공사업경기도 부천시 부일로 287-26 우성빌딩 401호 (상동)경기도 부천시 상동 318 우성빌딩 401호14621032-653-8971
78(주)건일이엔지기계가스설비공사업경기도 부천시 중동로254번길 64 신일아르디세 203호 (중동)경기도 부천시 중동 1143 신일아르디세 203호14548032-652-4059
89(주)건흥이엔씨지반조성ㆍ포장공사업경기도 부천시 길주로 81 706호 (상동)경기도 부천시 상동 534-9 706호14543032-715-5071
910(주)경남씨엔에스금속창호ㆍ지붕건축물조립공사업경기도 부천시 도약로 261 B동1208호 (도당동, 부천대우테크노파크)경기도 부천시 도당동 187-7 부천대우테크노파크 B동1208호14523032-672-7420
번호업체명업종소재지(도로명)소재지(지번)우편번호전화번호
856857형제설비2대행사가스난방공사업경기도 부천시 석천로44번길 36 101호 (상동)경기 부천시 상동 244-12 101호14620032-612-7268
857858홈뚜라미가스난방공사업경기도 부천시 옥산로 280 1층 (내동)경기도 부천시 내동 195 1층14490032-675-9002
858859홈시스인테리어가스난방공사업경기도 부천시 수도로 227-5 에이동 (내동)경기 부천시 내동 355 에이동14457032-684-9000
859860홍익건업가스난방공사업경기도 부천시 부일로380번길 34, 1층 102호 (중동)경기도 부천시 중동 895 1층, 102호14627032-614-8479
860861화남설비가스난방공사업경기도 부천시 은성로 30 (소사본동)경기 부천시 소사본1동 177-314758032-344-8881
861862화성설비가스난방공사업경기도 부천시 신흥로59번길 41 나동 101호 (심곡동)경기도 부천시 심곡동 339-9 나동 101호14616032-666-2766
862863화인이앤씨(주)구조물해체ㆍ비계공사업경기도 부천시 평천로738번길 5 403호 (삼정동)경기도 부천시 삼정동 350-3 403호14516032-672-7773
863864효성설비공사가스난방공사업경기도 부천시 역곡로 49 (역곡동)경기도 부천시 역곡동 67-714664032-344-2958
864865희진산업(주)상ㆍ하수도설비공사업경기도 부천시 부흥로 260 (중동)경기 부천시 중동 1208-314610032-661-6439
865866희진산업(주)지반조성ㆍ포장공사업경기도 부천시 부흥로 260 (중동)경기 부천시 중동 1208-314610032-661-6439