Overview

Dataset statistics

Number of variables24
Number of observations29
Missing cells31
Missing cells (%)4.5%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory5.8 KiB
Average record size in memory205.6 B

Variable types

Numeric6
Text7
Categorical10
DateTime1

Dataset

Description이 데이터는 서울특별시 동작구 소재의 등록공장현황입니다. 이 데이터에는 회사명, 주소,등록일, 업종 등이 포함되어 있습니다.
URLhttps://www.data.go.kr/data/3077867/fileData.do

Alerts

지목 has constant value ""Constant
소음진동여부 has constant value ""Constant
데이터갱신일자 has constant value ""Constant
설립구분 is highly imbalanced (78.4%)Imbalance
공장크기 is highly imbalanced (78.4%)Imbalance
자기자본액 has 9 (31.0%) missing valuesMissing
전화번호 has 4 (13.8%) missing valuesMissing
공장홈페이지 has 18 (62.1%) missing valuesMissing
순번 has unique valuesUnique
회사명 has unique valuesUnique
공장대표주소 has unique valuesUnique
등록일 has unique valuesUnique
생산품 has unique valuesUnique
용지면적 has 4 (13.8%) zerosZeros
종업원수 has 2 (6.9%) zerosZeros
자기자본액 has 14 (48.3%) zerosZeros

Reproduction

Analysis started2023-12-12 13:43:05.032381
Analysis finished2023-12-12 13:43:05.569683
Duration0.54 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

순번
Real number (ℝ)

UNIQUE 

Distinct29
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean15
Minimum1
Maximum29
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size393.0 B
2023-12-12T22:43:05.631232image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile2.4
Q18
median15
Q322
95-th percentile27.6
Maximum29
Range28
Interquartile range (IQR)14

Descriptive statistics

Standard deviation8.5146932
Coefficient of variation (CV)0.56764621
Kurtosis-1.2
Mean15
Median Absolute Deviation (MAD)7
Skewness0
Sum435
Variance72.5
MonotonicityStrictly increasing
2023-12-12T22:43:05.779414image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=29)
ValueCountFrequency (%)
1 1
 
3.4%
2 1
 
3.4%
29 1
 
3.4%
28 1
 
3.4%
27 1
 
3.4%
26 1
 
3.4%
25 1
 
3.4%
24 1
 
3.4%
23 1
 
3.4%
22 1
 
3.4%
Other values (19) 19
65.5%
ValueCountFrequency (%)
1 1
3.4%
2 1
3.4%
3 1
3.4%
4 1
3.4%
5 1
3.4%
6 1
3.4%
7 1
3.4%
8 1
3.4%
9 1
3.4%
10 1
3.4%
ValueCountFrequency (%)
29 1
3.4%
28 1
3.4%
27 1
3.4%
26 1
3.4%
25 1
3.4%
24 1
3.4%
23 1
3.4%
22 1
3.4%
21 1
3.4%
20 1
3.4%

회사명
Text

UNIQUE 

Distinct29
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size364.0 B
2023-12-12T22:43:06.022176image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length16
Median length10
Mean length7.8965517
Min length3

Characters and Unicode

Total characters229
Distinct characters94
Distinct categories5 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique29 ?
Unique (%)100.0%

Sample

1st row(주)나이테산업
2nd row(주)노디스
3rd row(주)대광메디텍
4th row(주)서광양행
5th row(주)서우시스템즈
ValueCountFrequency (%)
주식회사 3
 
9.1%
주)나이테산업 1
 
3.0%
미래미디어 1
 
3.0%
한국비전기술(주 1
 
3.0%
티엔에스식품 1
 
3.0%
코리아케어서프라이(주 1
 
3.0%
주식회사대신시앤에이 1
 
3.0%
한미이앤씨기술사사무소 1
 
3.0%
태성씨엔에쓰 1
 
3.0%
대성알에스 1
 
3.0%
Other values (21) 21
63.6%
2023-12-12T22:43:06.365001image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
주 21
 
9.2%
( 17
 
7.4%
) 17
 
7.4%
사 7
 
3.1%
스 6
 
2.6%
식 5
 
2.2%
에 5
 
2.2%
이 5
 
2.2%
업 4
 
1.7%
디 4
 
1.7%
Other values (84) 138
60.3%

Most occurring categories

ValueCountFrequency (%)
Other Letter 182
79.5%
Open Punctuation 17
 
7.4%
Close Punctuation 17
 
7.4%
Lowercase Letter 9
 
3.9%
Space Separator 4
 
1.7%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
주 21
 
11.5%
사 7
 
3.8%
스 6
 
3.3%
식 5
 
2.7%
에 5
 
2.7%
이 5
 
2.7%
업 4
 
2.2%
디 4
 
2.2%
산 4
 
2.2%
기 4
 
2.2%
Other values (72) 117
64.3%
Lowercase Letter
ValueCountFrequency (%)
k 1
11.1%
d 1
11.1%
u 1
11.1%
a 1
11.1%
l 1
11.1%
s 1
11.1%
h 1
11.1%
o 1
11.1%
c 1
11.1%
Open Punctuation
ValueCountFrequency (%)
( 17
100.0%
Close Punctuation
ValueCountFrequency (%)
) 17
100.0%
Space Separator
ValueCountFrequency (%)
4
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 182
79.5%
Common 38
 
16.6%
Latin 9
 
3.9%

Most frequent character per script

Hangul
ValueCountFrequency (%)
주 21
 
11.5%
사 7
 
3.8%
스 6
 
3.3%
식 5
 
2.7%
에 5
 
2.7%
이 5
 
2.7%
업 4
 
2.2%
디 4
 
2.2%
산 4
 
2.2%
기 4
 
2.2%
Other values (72) 117
64.3%
Latin
ValueCountFrequency (%)
k 1
11.1%
d 1
11.1%
u 1
11.1%
a 1
11.1%
l 1
11.1%
s 1
11.1%
h 1
11.1%
o 1
11.1%
c 1
11.1%
Common
ValueCountFrequency (%)
( 17
44.7%
) 17
44.7%
4
 
10.5%

Most occurring blocks

ValueCountFrequency (%)
Hangul 182
79.5%
ASCII 47
 
20.5%

Most frequent character per block

Hangul
ValueCountFrequency (%)
주 21
 
11.5%
사 7
 
3.8%
스 6
 
3.3%
식 5
 
2.7%
에 5
 
2.7%
이 5
 
2.7%
업 4
 
2.2%
디 4
 
2.2%
산 4
 
2.2%
기 4
 
2.2%
Other values (72) 117
64.3%
ASCII
ValueCountFrequency (%)
( 17
36.2%
) 17
36.2%
4
 
8.5%
k 1
 
2.1%
d 1
 
2.1%
u 1
 
2.1%
a 1
 
2.1%
l 1
 
2.1%
s 1
 
2.1%
h 1
 
2.1%
Other values (2) 2
 
4.3%

공장대표주소
Text

UNIQUE 

Distinct29
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size364.0 B
2023-12-12T22:43:06.609045image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length44
Median length36
Mean length31.827586
Min length22

Characters and Unicode

Total characters923
Distinct characters92
Distinct categories8 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique29 ?
Unique (%)100.0%

Sample

1st row서울특별시 동작구 양녕로20길 43 (상도동)
2nd row서울특별시 동작구 사당로17나길 2, 3층 (사당동)
3rd row서울특별시 동작구 동작대로35길 5, 대광빌딩 5층 (사당동)
4th row서울특별시 동작구 여의대방로22카길 43 (신대방동)
5th row서울특별시 동작구 상도로45길 31, 지하2층 (상도1동, 하이탑독서실)
ValueCountFrequency (%)
서울특별시 29
 
16.3%
동작구 29
 
16.3%
신대방동 8
 
4.5%
대방동 7
 
3.9%
사당동 5
 
2.8%
상도동 4
 
2.2%
여의대방로24길 3
 
1.7%
상도로 3
 
1.7%
2층 3
 
1.7%
지층 3
 
1.7%
Other values (77) 84
47.2%
2023-12-12T22:43:06.991284image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
149
 
16.1%
동 66
 
7.2%
작 33
 
3.6%
( 31
 
3.4%
) 31
 
3.4%
서 30
 
3.3%
시 30
 
3.3%
, 30
 
3.3%
특 29
 
3.1%
별 29
 
3.1%
Other values (82) 465
50.4%

Most occurring categories

ValueCountFrequency (%)
Other Letter 556
60.2%
Space Separator 149
 
16.1%
Decimal Number 122
 
13.2%
Open Punctuation 31
 
3.4%
Close Punctuation 31
 
3.4%
Other Punctuation 30
 
3.3%
Dash Punctuation 3
 
0.3%
Uppercase Letter 1
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
동 66
 
11.9%
작 33
 
5.9%
서 30
 
5.4%
시 30
 
5.4%
특 29
 
5.2%
별 29
 
5.2%
구 29
 
5.2%
대 29
 
5.2%
울 29
 
5.2%
로 27
 
4.9%
Other values (66) 225
40.5%
Decimal Number
ValueCountFrequency (%)
2 26
21.3%
1 19
15.6%
3 18
14.8%
4 16
13.1%
5 15
12.3%
8 7
 
5.7%
6 6
 
4.9%
0 6
 
4.9%
9 5
 
4.1%
7 4
 
3.3%
Space Separator
ValueCountFrequency (%)
149
100.0%
Open Punctuation
ValueCountFrequency (%)
( 31
100.0%
Close Punctuation
ValueCountFrequency (%)
) 31
100.0%
Other Punctuation
ValueCountFrequency (%)
, 30
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 3
100.0%
Uppercase Letter
ValueCountFrequency (%)
B 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 556
60.2%
Common 366
39.7%
Latin 1
 
0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
동 66
 
11.9%
작 33
 
5.9%
서 30
 
5.4%
시 30
 
5.4%
특 29
 
5.2%
별 29
 
5.2%
구 29
 
5.2%
대 29
 
5.2%
울 29
 
5.2%
로 27
 
4.9%
Other values (66) 225
40.5%
Common
ValueCountFrequency (%)
149
40.7%
( 31
 
8.5%
) 31
 
8.5%
, 30
 
8.2%
2 26
 
7.1%
1 19
 
5.2%
3 18
 
4.9%
4 16
 
4.4%
5 15
 
4.1%
8 7
 
1.9%
Other values (5) 24
 
6.6%
Latin
ValueCountFrequency (%)
B 1
100.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 556
60.2%
ASCII 367
39.8%

Most frequent character per block

ASCII
ValueCountFrequency (%)
149
40.6%
( 31
 
8.4%
) 31
 
8.4%
, 30
 
8.2%
2 26
 
7.1%
1 19
 
5.2%
3 18
 
4.9%
4 16
 
4.4%
5 15
 
4.1%
8 7
 
1.9%
Other values (6) 25
 
6.8%
Hangul
ValueCountFrequency (%)
동 66
 
11.9%
작 33
 
5.9%
서 30
 
5.4%
시 30
 
5.4%
특 29
 
5.2%
별 29
 
5.2%
구 29
 
5.2%
대 29
 
5.2%
울 29
 
5.2%
로 27
 
4.9%
Other values (66) 225
40.5%

설립구분
Categorical

IMBALANCE 

Distinct2
Distinct (%)6.9%
Missing0
Missing (%)0.0%
Memory size364.0 B
일반
28 
창업
 
1

Length

Max length2
Median length2
Mean length2
Min length2

Unique

Unique1 ?
Unique (%)3.4%

Sample

1st row일반
2nd row일반
3rd row일반
4th row일반
5th row일반

Common Values

ValueCountFrequency (%)
일반 28
96.6%
창업 1
 
3.4%

Length

2023-12-12T22:43:07.114865image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T22:43:07.219823image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
일반 28
96.6%
창업 1
 
3.4%

용지면적
Real number (ℝ)

ZEROS 

Distinct25
Distinct (%)86.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean285.27034
Minimum0
Maximum4428
Zeros4
Zeros (%)13.8%
Negative0
Negative (%)0.0%
Memory size393.0 B
2023-12-12T22:43:07.310953image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q152
median121.12
Q3205
95-th percentile385.564
Maximum4428
Range4428
Interquartile range (IQR)153

Descriptive statistics

Standard deviation804.18893
Coefficient of variation (CV)2.8190414
Kurtosis27.825192
Mean285.27034
Median Absolute Deviation (MAD)72.12
Skewness5.2284651
Sum8272.84
Variance646719.83
MonotonicityNot monotonic
2023-12-12T22:43:07.422549image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=25)
ValueCountFrequency (%)
0.0 4
 
13.8%
49.0 2
 
6.9%
132.23 1
 
3.4%
157.5 1
 
3.4%
235.0 1
 
3.4%
205.0 1
 
3.4%
378.91 1
 
3.4%
121.12 1
 
3.4%
185.63 1
 
3.4%
112.35 1
 
3.4%
Other values (15) 15
51.7%
ValueCountFrequency (%)
0.0 4
13.8%
17.44 1
 
3.4%
49.0 2
6.9%
52.0 1
 
3.4%
66.18 1
 
3.4%
68.89 1
 
3.4%
99.0 1
 
3.4%
100.0 1
 
3.4%
104.12 1
 
3.4%
112.35 1
 
3.4%
ValueCountFrequency (%)
4428.0 1
3.4%
390.0 1
3.4%
378.91 1
3.4%
349.1 1
3.4%
240.0 1
3.4%
235.0 1
3.4%
214.02 1
3.4%
205.0 1
3.4%
204.75 1
3.4%
185.63 1
3.4%

건축면적
Real number (ℝ)

Distinct28
Distinct (%)96.6%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean322.58241
Minimum17.44
Maximum4617
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size393.0 B
2023-12-12T22:43:07.538523image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum17.44
5-th percentile37.6
Q199.17
median157.5
Q3216.26
95-th percentile472.924
Maximum4617
Range4599.56
Interquartile range (IQR)117.09

Descriptive statistics

Standard deviation834.0707
Coefficient of variation (CV)2.585605
Kurtosis27.759833
Mean322.58241
Median Absolute Deviation (MAD)58.76
Skewness5.220985
Sum9354.89
Variance695673.94
MonotonicityNot monotonic
2023-12-12T22:43:07.673926image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=28)
ValueCountFrequency (%)
49.0 2
 
6.9%
190.54 1
 
3.4%
157.5 1
 
3.4%
235.0 1
 
3.4%
98.1 1
 
3.4%
378.91 1
 
3.4%
167.97 1
 
3.4%
121.12 1
 
3.4%
185.63 1
 
3.4%
112.35 1
 
3.4%
Other values (18) 18
62.1%
ValueCountFrequency (%)
17.44 1
3.4%
36.0 1
3.4%
40.0 1
3.4%
49.0 2
6.9%
66.18 1
3.4%
98.1 1
3.4%
99.17 1
3.4%
100.0 1
3.4%
101.87 1
3.4%
103.6 1
3.4%
ValueCountFrequency (%)
4617.0 1
3.4%
495.36 1
3.4%
439.27 1
3.4%
378.91 1
3.4%
282.0 1
3.4%
240.11 1
3.4%
235.0 1
3.4%
216.26 1
3.4%
214.02 1
3.4%
194.98 1
3.4%

종업원수
Real number (ℝ)

ZEROS 

Distinct17
Distinct (%)58.6%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean10.931034
Minimum0
Maximum93
Zeros2
Zeros (%)6.9%
Negative0
Negative (%)0.0%
Memory size393.0 B
2023-12-12T22:43:07.836998image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0.4
Q14
median7
Q312
95-th percentile23.2
Maximum93
Range93
Interquartile range (IQR)8

Descriptive statistics

Standard deviation16.970418
Coefficient of variation (CV)1.5524988
Kurtosis20.921759
Mean10.931034
Median Absolute Deviation (MAD)4
Skewness4.3062482
Sum317
Variance287.99507
MonotonicityNot monotonic
2023-12-12T22:43:07.980309image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=17)
ValueCountFrequency (%)
4 3
10.3%
2 3
10.3%
16 3
10.3%
5 3
10.3%
10 3
10.3%
8 2
 
6.9%
0 2
 
6.9%
12 1
 
3.4%
3 1
 
3.4%
1 1
 
3.4%
Other values (7) 7
24.1%
ValueCountFrequency (%)
0 2
6.9%
1 1
 
3.4%
2 3
10.3%
3 1
 
3.4%
4 3
10.3%
5 3
10.3%
6 1
 
3.4%
7 1
 
3.4%
8 2
6.9%
9 1
 
3.4%
ValueCountFrequency (%)
93 1
 
3.4%
24 1
 
3.4%
22 1
 
3.4%
16 3
10.3%
13 1
 
3.4%
12 1
 
3.4%
10 3
10.3%
9 1
 
3.4%
8 2
6.9%
7 1
 
3.4%

공장크기
Categorical

IMBALANCE 

Distinct2
Distinct (%)6.9%
Missing0
Missing (%)0.0%
Memory size364.0 B
소기업
28 
중기업
 
1

Length

Max length3
Median length3
Mean length3
Min length3

Unique

Unique1 ?
Unique (%)3.4%

Sample

1st row소기업
2nd row소기업
3rd row소기업
4th row소기업
5th row소기업

Common Values

ValueCountFrequency (%)
소기업 28
96.6%
중기업 1
 
3.4%

Length

2023-12-12T22:43:08.095928image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T22:43:08.187036image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
소기업 28
96.6%
중기업 1
 
3.4%

등록일
Real number (ℝ)

UNIQUE 

Distinct29
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean20141957
Minimum19960111
Maximum20230316
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size393.0 B
2023-12-12T22:43:08.292730image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum19960111
5-th percentile20058588
Q120100906
median20150624
Q320190128
95-th percentile20220435
Maximum20230316
Range270205
Interquartile range (IQR)89222

Descriptive statistics

Standard deviation61691.906
Coefficient of variation (CV)0.0030628555
Kurtosis1.1036238
Mean20141957
Median Absolute Deviation (MAD)49718
Skewness-0.82890538
Sum5.8411677 × 108
Variance3.8058912 × 109
MonotonicityNot monotonic
2023-12-12T22:43:08.483039image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=29)
ValueCountFrequency (%)
19960111 1
 
3.4%
20160108 1
 
3.4%
20150323 1
 
3.4%
20150624 1
 
3.4%
20171010 1
 
3.4%
20101013 1
 
3.4%
20110705 1
 
3.4%
20220516 1
 
3.4%
20200408 1
 
3.4%
20140724 1
 
3.4%
Other values (19) 19
65.5%
ValueCountFrequency (%)
19960111 1
3.4%
20050512 1
3.4%
20070703 1
3.4%
20070808 1
3.4%
20090804 1
3.4%
20090923 1
3.4%
20100426 1
3.4%
20100906 1
3.4%
20101013 1
3.4%
20110705 1
3.4%
ValueCountFrequency (%)
20230316 1
3.4%
20220516 1
3.4%
20220314 1
3.4%
20220111 1
3.4%
20201125 1
3.4%
20200625 1
3.4%
20200408 1
3.4%
20190128 1
3.4%
20180822 1
3.4%
20171010 1
3.4%

용도지역
Categorical

Distinct6
Distinct (%)20.7%
Missing0
Missing (%)0.0%
Memory size364.0 B
도시지역/주거지역/제3종일반주거지역
11 
도시지역/주거지역/제2종일반주거지역
8 
도시지역/주거지역
6 
도시지역/상업지역/일반상업지역/미관지구
2 
도시지역/주거지역/제1종일반주거지역
 
1

Length

Max length24
Median length19
Mean length17.241379
Min length9

Unique

Unique2 ?
Unique (%)6.9%

Sample

1st row도시지역/주거지역
2nd row도시지역/주거지역/제3종일반주거지역
3rd row도시지역/주거지역/제3종일반주거지역
4th row도시지역/주거지역/제2종일반주거지역
5th row도시지역/주거지역/제2종일반주거지역

Common Values

ValueCountFrequency (%)
도시지역/주거지역/제3종일반주거지역 11
37.9%
도시지역/주거지역/제2종일반주거지역 8
27.6%
도시지역/주거지역 6
20.7%
도시지역/상업지역/일반상업지역/미관지구 2
 
6.9%
도시지역/주거지역/제1종일반주거지역 1
 
3.4%
도시지역/주거지역/제3종일반주거지역/미관지구 1
 
3.4%

Length

2023-12-12T22:43:08.627228image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T22:43:08.803471image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
도시지역/주거지역/제3종일반주거지역 11
37.9%
도시지역/주거지역/제2종일반주거지역 8
27.6%
도시지역/주거지역 6
20.7%
도시지역/상업지역/일반상업지역/미관지구 2
 
6.9%
도시지역/주거지역/제1종일반주거지역 1
 
3.4%
도시지역/주거지역/제3종일반주거지역/미관지구 1
 
3.4%

지목
Categorical

CONSTANT 

Distinct1
Distinct (%)3.4%
Missing0
Missing (%)0.0%
Memory size364.0 B
대
29 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row대
2nd row대
3rd row대
4th row대
5th row대

Common Values

ValueCountFrequency (%)
대 29
100.0%

Length

2023-12-12T22:43:09.000030image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T22:43:09.132710image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
대 29
100.0%

업종번호
Text

Distinct28
Distinct (%)96.6%
Missing0
Missing (%)0.0%
Memory size364.0 B
2023-12-12T22:43:09.365695image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length68
Median length61
Mean length17.413793
Min length7

Characters and Unicode

Total characters505
Distinct characters12
Distinct categories3 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique27 ?
Unique (%)93.1%

Sample

1st row27214, 27215
2nd row13229,
3rd row20499, 20495
4th row26329,
5th row29172,
ValueCountFrequency (%)
18113 3
 
3.9%
26421 3
 
3.9%
26410 3
 
3.9%
28123 2
 
2.6%
33910 2
 
2.6%
14111 2
 
2.6%
13229 2
 
2.6%
14192 2
 
2.6%
18129 2
 
2.6%
14491 2
 
2.6%
Other values (45) 54
70.1%
2023-12-12T22:43:09.813020image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 101
20.0%
2 86
17.0%
, 60
11.9%
60
11.9%
9 51
10.1%
4 40
 
7.9%
3 31
 
6.1%
0 26
 
5.1%
8 21
 
4.2%
6 13
 
2.6%
Other values (2) 16
 
3.2%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 385
76.2%
Other Punctuation 60
 
11.9%
Space Separator 60
 
11.9%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 101
26.2%
2 86
22.3%
9 51
13.2%
4 40
 
10.4%
3 31
 
8.1%
0 26
 
6.8%
8 21
 
5.5%
6 13
 
3.4%
5 9
 
2.3%
7 7
 
1.8%
Other Punctuation
ValueCountFrequency (%)
, 60
100.0%
Space Separator
ValueCountFrequency (%)
60
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 505
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
1 101
20.0%
2 86
17.0%
, 60
11.9%
60
11.9%
9 51
10.1%
4 40
 
7.9%
3 31
 
6.1%
0 26
 
5.1%
8 21
 
4.2%
6 13
 
2.6%
Other values (2) 16
 
3.2%

Most occurring blocks

ValueCountFrequency (%)
ASCII 505
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 101
20.0%
2 86
17.0%
, 60
11.9%
60
11.9%
9 51
10.1%
4 40
 
7.9%
3 31
 
6.1%
0 26
 
5.1%
8 21
 
4.2%
6 13
 
2.6%
Other values (2) 16
 
3.2%

업종명
Text

Distinct28
Distinct (%)96.6%
Missing0
Missing (%)0.0%
Memory size364.0 B
2023-12-12T22:43:10.089791image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length30
Median length24
Mean length16.896552
Min length10

Characters and Unicode

Total characters490
Distinct characters97
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

Unique27 ?
Unique (%)93.1%

Sample

1st row속도계 및 적산계기 제조업 외 1 종
2nd row기타 직물제품 제조업
3rd row그 외 기타 분류 안된 화학제품 제조업 외 1 종
4th row기타 주변기기 제조업
5th row공기 조화장치 제조업
ValueCountFrequency (%)
제조업 25
15.0%
외 22
 
13.2%
종 17
 
10.2%
기타 12
 
7.2%
및 10
 
6.0%
1 10
 
6.0%
그 5
 
3.0%
제품 3
 
1.8%
인쇄업 3
 
1.8%
플라스틱 2
 
1.2%
Other values (51) 58
34.7%
2023-12-12T22:43:10.490861image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
138
28.2%
제 33
 
6.7%
업 30
 
6.1%
조 26
 
5.3%
외 22
 
4.5%
기 18
 
3.7%
종 17
 
3.5%
타 12
 
2.4%
및 10
 
2.0%
품 10
 
2.0%
Other values (87) 174
35.5%

Most occurring categories

ValueCountFrequency (%)
Other Letter 333
68.0%
Space Separator 138
28.2%
Decimal Number 17
 
3.5%
Other Punctuation 2
 
0.4%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
제 33
 
9.9%
업 30
 
9.0%
조 26
 
7.8%
외 22
 
6.6%
기 18
 
5.4%
종 17
 
5.1%
타 12
 
3.6%
및 10
 
3.0%
품 10
 
3.0%
비 6
 
1.8%
Other values (77) 149
44.7%
Decimal Number
ValueCountFrequency (%)
1 10
58.8%
2 1
 
5.9%
7 1
 
5.9%
4 1
 
5.9%
9 1
 
5.9%
8 1
 
5.9%
5 1
 
5.9%
3 1
 
5.9%
Space Separator
ValueCountFrequency (%)
138
100.0%
Other Punctuation
ValueCountFrequency (%)
, 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 333
68.0%
Common 157
32.0%

Most frequent character per script

Hangul
ValueCountFrequency (%)
제 33
 
9.9%
업 30
 
9.0%
조 26
 
7.8%
외 22
 
6.6%
기 18
 
5.4%
종 17
 
5.1%
타 12
 
3.6%
및 10
 
3.0%
품 10
 
3.0%
비 6
 
1.8%
Other values (77) 149
44.7%
Common
ValueCountFrequency (%)
138
87.9%
1 10
 
6.4%
, 2
 
1.3%
2 1
 
0.6%
7 1
 
0.6%
4 1
 
0.6%
9 1
 
0.6%
8 1
 
0.6%
5 1
 
0.6%
3 1
 
0.6%

Most occurring blocks

ValueCountFrequency (%)
Hangul 333
68.0%
ASCII 157
32.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
138
87.9%
1 10
 
6.4%
, 2
 
1.3%
2 1
 
0.6%
7 1
 
0.6%
4 1
 
0.6%
9 1
 
0.6%
8 1
 
0.6%
5 1
 
0.6%
3 1
 
0.6%
Hangul
ValueCountFrequency (%)
제 33
 
9.9%
업 30
 
9.0%
조 26
 
7.8%
외 22
 
6.6%
기 18
 
5.4%
종 17
 
5.1%
타 12
 
3.6%
및 10
 
3.0%
품 10
 
3.0%
비 6
 
1.8%
Other values (77) 149
44.7%

생산품
Text

UNIQUE 

Distinct29
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size364.0 B
2023-12-12T22:43:10.711729image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length30
Median length14
Mean length9.3448276
Min length2

Characters and Unicode

Total characters271
Distinct characters133
Distinct categories8 ?
Distinct scripts4 ?
Distinct blocks4 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique29 ?
Unique (%)100.0%

Sample

1st row로타리스위치,유량계
2nd row방연마스크제조
3rd row큐?脚㈇？硫囹
4th row레이저프린터토너카트리지
5th row항온항습기
ValueCountFrequency (%)
및 2
 
4.4%
로타리스위치,유량계 1
 
2.2%
방연마스크제조 1
 
2.2%
cctv 1
 
2.2%
영상음향기기 1
 
2.2%
인쇄(광고현수막)등 1
 
2.2%
포라스고무제품 1
 
2.2%
철도신호용품 1
 
2.2%
자동제어반 1
 
2.2%
배전선로 1
 
2.2%
Other values (34) 34
75.6%
2023-12-12T22:43:11.088290image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
16
 
5.9%
, 13
 
4.8%
기 9
 
3.3%
제 8
 
3.0%
C 8
 
3.0%
스 5
 
1.8%
품 5
 
1.8%
조 4
 
1.5%
카 4
 
1.5%
장 4
 
1.5%
Other values (123) 195
72.0%

Most occurring categories

ValueCountFrequency (%)
Other Letter 214
79.0%
Uppercase Letter 18
 
6.6%
Space Separator 16
 
5.9%
Other Punctuation 15
 
5.5%
Open Punctuation 3
 
1.1%
Close Punctuation 3
 
1.1%
Other Symbol 1
 
0.4%
Decimal Number 1
 
0.4%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
기 9
 
4.2%
제 8
 
3.7%
스 5
 
2.3%
품 5
 
2.3%
조 4
 
1.9%
카 4
 
1.9%
장 4
 
1.9%
관 4
 
1.9%
물 4
 
1.9%
고 3
 
1.4%
Other values (110) 164
76.6%
Uppercase Letter
ValueCountFrequency (%)
C 8
44.4%
T 4
22.2%
V 4
22.2%
R 1
 
5.6%
F 1
 
5.6%
Other Punctuation
ValueCountFrequency (%)
, 13
86.7%
？ 1
 
6.7%
? 1
 
6.7%
Space Separator
ValueCountFrequency (%)
16
100.0%
Open Punctuation
ValueCountFrequency (%)
( 3
100.0%
Close Punctuation
ValueCountFrequency (%)
) 3
100.0%
Other Symbol
ValueCountFrequency (%)
㈇ 1
100.0%
Decimal Number
ValueCountFrequency (%)
4 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 212
78.2%
Common 38
 
14.0%
Latin 18
 
6.6%
Han 3
 
1.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
기 9
 
4.2%
제 8
 
3.8%
스 5
 
2.4%
품 5
 
2.4%
조 4
 
1.9%
카 4
 
1.9%
장 4
 
1.9%
관 4
 
1.9%
물 4
 
1.9%
고 3
 
1.4%
Other values (108) 162
76.4%
Common
ValueCountFrequency (%)
16
42.1%
, 13
34.2%
( 3
 
7.9%
) 3
 
7.9%
？ 1
 
2.6%
? 1
 
2.6%
4 1
 
2.6%
Latin
ValueCountFrequency (%)
C 8
44.4%
T 4
22.2%
V 4
22.2%
R 1
 
5.6%
F 1
 
5.6%
Han
ValueCountFrequency (%)
囹 1
33.3%
硫 1
33.3%
脚 1
33.3%

Most occurring blocks

ValueCountFrequency (%)
Hangul 211
77.9%
ASCII 55
 
20.3%
CJK 3
 
1.1%
None 2
 
0.7%

Most frequent character per block

ASCII
ValueCountFrequency (%)
16
29.1%
, 13
23.6%
C 8
14.5%
T 4
 
7.3%
V 4
 
7.3%
( 3
 
5.5%
) 3
 
5.5%
? 1
 
1.8%
R 1
 
1.8%
4 1
 
1.8%
Hangul
ValueCountFrequency (%)
기 9
 
4.3%
제 8
 
3.8%
스 5
 
2.4%
품 5
 
2.4%
조 4
 
1.9%
카 4
 
1.9%
장 4
 
1.9%
관 4
 
1.9%
물 4
 
1.9%
고 3
 
1.4%
Other values (107) 161
76.3%
CJK
ValueCountFrequency (%)
囹 1
33.3%
硫 1
33.3%
脚 1
33.3%
None
ValueCountFrequency (%)
？ 1
50.0%
㈇ 1
50.0%

대기오염
Categorical

Distinct2
Distinct (%)6.9%
Missing0
Missing (%)0.0%
Memory size364.0 B
해당없음
17 
<NA>
12 

Length

Max length4
Median length4
Mean length4
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row해당없음
2nd row<NA>
3rd row해당없음
4th row해당없음
5th row<NA>

Common Values

ValueCountFrequency (%)
해당없음 17
58.6%
<NA> 12
41.4%

Length

2023-12-12T22:43:11.257968image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T22:43:11.389589image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
해당없음 17
58.6%
na 12
41.4%

수질오염
Categorical

Distinct2
Distinct (%)6.9%
Missing0
Missing (%)0.0%
Memory size364.0 B
해당없음
17 
<NA>
12 

Length

Max length4
Median length4
Mean length4
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row해당없음
2nd row<NA>
3rd row해당없음
4th row해당없음
5th row<NA>

Common Values

ValueCountFrequency (%)
해당없음 17
58.6%
<NA> 12
41.4%

Length

2023-12-12T22:43:11.915473image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T22:43:12.041387image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
해당없음 17
58.6%
na 12
41.4%

소음진동여부
Categorical

CONSTANT 

Distinct1
Distinct (%)3.4%
Missing0
Missing (%)0.0%
Memory size364.0 B
무
29 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row무
2nd row무
3rd row무
4th row무
5th row무

Common Values

ValueCountFrequency (%)
무 29
100.0%

Length

2023-12-12T22:43:12.171822image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T22:43:12.275579image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
무 29
100.0%

생활용수
Categorical

Distinct6
Distinct (%)20.7%
Missing0
Missing (%)0.0%
Memory size364.0 B
<NA>
14 
0
9 
1
3 
4
 
1
20
 
1

Length

Max length4
Median length2
Mean length2.4827586
Min length1

Unique

Unique3 ?
Unique (%)10.3%

Sample

1st row1
2nd row<NA>
3rd row0
4th row0
5th row<NA>

Common Values

ValueCountFrequency (%)
<NA> 14
48.3%
0 9
31.0%
1 3
 
10.3%
4 1
 
3.4%
20 1
 
3.4%
3 1
 
3.4%

Length

2023-12-12T22:43:12.422394image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T22:43:12.550075image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 14
48.3%
0 9
31.0%
1 3
 
10.3%
4 1
 
3.4%
20 1
 
3.4%
3 1
 
3.4%

산업용수
Categorical

Distinct2
Distinct (%)6.9%
Missing0
Missing (%)0.0%
Memory size364.0 B
0
15 
<NA>
14 

Length

Max length4
Median length1
Mean length2.4482759
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row<NA>
3rd row0
4th row0
5th row<NA>

Common Values

ValueCountFrequency (%)
0 15
51.7%
<NA> 14
48.3%

Length

2023-12-12T22:43:12.712108image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T22:43:12.850857image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 15
51.7%
na 14
48.3%

자기자본액
Real number (ℝ)

MISSING  ZEROS 

Distinct6
Distinct (%)30.0%
Missing9
Missing (%)31.0%
Infinite0
Infinite (%)0.0%
Mean23.55
Minimum0
Maximum200
Zeros14
Zeros (%)48.3%
Negative0
Negative (%)0.0%
Memory size393.0 B
2023-12-12T22:43:12.964035image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q313.25
95-th percentile105
Maximum200
Range200
Interquartile range (IQR)13.25

Descriptive statistics

Standard deviation50.684239
Coefficient of variation (CV)2.152197
Kurtosis7.5576746
Mean23.55
Median Absolute Deviation (MAD)0
Skewness2.6425046
Sum471
Variance2568.8921
MonotonicityNot monotonic
2023-12-12T22:43:13.093109image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=6)
ValueCountFrequency (%)
0 14
48.3%
50 2
 
6.9%
1 1
 
3.4%
70 1
 
3.4%
200 1
 
3.4%
100 1
 
3.4%
(Missing) 9
31.0%
ValueCountFrequency (%)
0 14
48.3%
1 1
 
3.4%
50 2
 
6.9%
70 1
 
3.4%
100 1
 
3.4%
200 1
 
3.4%
ValueCountFrequency (%)
200 1
 
3.4%
100 1
 
3.4%
70 1
 
3.4%
50 2
 
6.9%
1 1
 
3.4%
0 14
48.3%

타인자본액
Categorical

Distinct4
Distinct (%)13.8%
Missing0
Missing (%)0.0%
Memory size364.0 B
0
15 
<NA>
12 
1
 
1
20
 
1

Length

Max length4
Median length1
Mean length2.2758621
Min length1

Unique

Unique2 ?
Unique (%)6.9%

Sample

1st row0
2nd row<NA>
3rd row0
4th row0
5th row<NA>

Common Values

ValueCountFrequency (%)
0 15
51.7%
<NA> 12
41.4%
1 1
 
3.4%
20 1
 
3.4%

Length

2023-12-12T22:43:13.240485image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T22:43:13.373266image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 15
51.7%
na 12
41.4%
1 1
 
3.4%
20 1
 
3.4%

전화번호
Text

MISSING 

Distinct25
Distinct (%)100.0%
Missing4
Missing (%)13.8%
Memory size364.0 B
2023-12-12T22:43:13.595226image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length13
Median length11
Mean length11.12
Min length9

Characters and Unicode

Total characters278
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

Unique25 ?
Unique (%)100.0%

Sample

1st row02-822-3355
2nd row02-3477-9419
3rd row02-533-3700
4th row02-3273-6181
5th row02-814-8241
ValueCountFrequency (%)
02-822-3355 1
 
4.0%
208150407 1
 
4.0%
070-7013-0099 1
 
4.0%
02-826-0472 1
 
4.0%
02-824-0058 1
 
4.0%
02-701-8362 1
 
4.0%
02-882-5506 1
 
4.0%
02-812-4595 1
 
4.0%
02-813-5014 1
 
4.0%
02-826-7782 1
 
4.0%
Other values (15) 15
60.0%
2023-12-12T22:43:14.017316image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
- 48
17.3%
0 45
16.2%
2 41
14.7%
8 28
10.1%
1 27
9.7%
5 19
 
6.8%
7 19
 
6.8%
3 16
 
5.8%
6 13
 
4.7%
4 13
 
4.7%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 230
82.7%
Dash Punctuation 48
 
17.3%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 45
19.6%
2 41
17.8%
8 28
12.2%
1 27
11.7%
5 19
8.3%
7 19
8.3%
3 16
 
7.0%
6 13
 
5.7%
4 13
 
5.7%
9 9
 
3.9%
Dash Punctuation
ValueCountFrequency (%)
- 48
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 278
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
- 48
17.3%
0 45
16.2%
2 41
14.7%
8 28
10.1%
1 27
9.7%
5 19
 
6.8%
7 19
 
6.8%
3 16
 
5.8%
6 13
 
4.7%
4 13
 
4.7%

Most occurring blocks

ValueCountFrequency (%)
ASCII 278
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
- 48
17.3%
0 45
16.2%
2 41
14.7%
8 28
10.1%
1 27
9.7%
5 19
 
6.8%
7 19
 
6.8%
3 16
 
5.8%
6 13
 
4.7%
4 13
 
4.7%

공장홈페이지
Text

MISSING 

Distinct11
Distinct (%)100.0%
Missing18
Missing (%)62.1%
Memory size364.0 B
2023-12-12T22:43:14.214673image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length19
Median length17
Mean length15.909091
Min length13

Characters and Unicode

Total characters175
Distinct characters29
Distinct categories5 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique11 ?
Unique (%)100.0%

Sample

1st rowwww.nodis.co.kr
2nd rowwww.skrecycle.com
3rd rowwww.seowoo.com
4th rowwww.tmgf.co.kr
5th rowwww.hsafety.com
ValueCountFrequency (%)
www.nodis.co.kr 1
8.3%
www.skrecycle.com 1
8.3%
www.seowoo.com 1
8.3%
www.tmgf.co.kr 1
8.3%
www.hsafety.com 1
8.3%
www.dhe-av.co.kr 1
8.3%
www.sw0616.kr 1
8.3%
http://entcom.co.kr 1
8.3%
www.youngdoink.com 1
8.3%
www.kocas.co.kr 1
8.3%
Other values (2) 2
16.7%
2023-12-12T22:43:14.611691image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
w 32
18.3%
. 26
14.9%
o 18
10.3%
c 16
 
9.1%
k 9
 
5.1%
m 7
 
4.0%
e 7
 
4.0%
r 7
 
4.0%
t 6
 
3.4%
s 6
 
3.4%
Other values (19) 41
23.4%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 137
78.3%
Other Punctuation 29
 
16.6%
Control 4
 
2.3%
Decimal Number 4
 
2.3%
Dash Punctuation 1
 
0.6%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
w 32
23.4%
o 18
13.1%
c 16
11.7%
k 9
 
6.6%
m 7
 
5.1%
e 7
 
5.1%
r 7
 
5.1%
t 6
 
4.4%
s 6
 
4.4%
n 5
 
3.6%
Other values (11) 24
17.5%
Other Punctuation
ValueCountFrequency (%)
. 26
89.7%
/ 2
 
6.9%
: 1
 
3.4%
Decimal Number
ValueCountFrequency (%)
6 2
50.0%
0 1
25.0%
1 1
25.0%
Control
ValueCountFrequency (%)
4
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 137
78.3%
Common 38
 
21.7%

Most frequent character per script

Latin
ValueCountFrequency (%)
w 32
23.4%
o 18
13.1%
c 16
11.7%
k 9
 
6.6%
m 7
 
5.1%
e 7
 
5.1%
r 7
 
5.1%
t 6
 
4.4%
s 6
 
4.4%
n 5
 
3.6%
Other values (11) 24
17.5%
Common
ValueCountFrequency (%)
. 26
68.4%
4
 
10.5%
6 2
 
5.3%
/ 2
 
5.3%
- 1
 
2.6%
0 1
 
2.6%
1 1
 
2.6%
: 1
 
2.6%

Most occurring blocks

ValueCountFrequency (%)
ASCII 175
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
w 32
18.3%
. 26
14.9%
o 18
10.3%
c 16
 
9.1%
k 9
 
5.1%
m 7
 
4.0%
e 7
 
4.0%
r 7
 
4.0%
t 6
 
3.4%
s 6
 
3.4%
Other values (19) 41
23.4%

데이터갱신일자
Date

CONSTANT 

Distinct1
Distinct (%)3.4%
Missing0
Missing (%)0.0%
Memory size364.0 B
Minimum2023-07-03 00:00:00
Maximum2023-07-03 00:00:00
2023-12-12T22:43:14.765603image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T22:43:14.892956image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=1)

Sample

순번회사명공장대표주소설립구분용지면적건축면적종업원수공장크기등록일용도지역지목업종번호업종명생산품대기오염수질오염소음진동여부생활용수산업용수자기자본액타인자본액전화번호공장홈페이지데이터갱신일자
01(주)나이테산업서울특별시 동작구 양녕로20길 43 (상도동)일반132.23190.548소기업19960111도시지역/주거지역대27214, 27215속도계 및 적산계기 제조업 외 1 종로타리스위치,유량계해당없음해당없음무100002-822-3355<NA>2023-07-03
12(주)노디스서울특별시 동작구 사당로17나길 2, 3층 (사당동)일반49.049.05소기업20160108도시지역/주거지역/제3종일반주거지역대13229,기타 직물제품 제조업방연마스크제조<NA><NA>무<NA><NA><NA><NA>02-3477-9419www.nodis.co.kr2023-07-03
23(주)대광메디텍서울특별시 동작구 동작대로35길 5, 대광빌딩 5층 (사당동)일반214.02214.025소기업20070808도시지역/주거지역/제3종일반주거지역대20499, 20495그 외 기타 분류 안된 화학제품 제조업 외 1 종큐?脚㈇？硫囹해당없음해당없음무000002-533-3700<NA>2023-07-03
34(주)서광양행서울특별시 동작구 여의대방로22카길 43 (신대방동)일반390.0495.3622소기업20090804도시지역/주거지역/제2종일반주거지역대26329,기타 주변기기 제조업레이저프린터토너카트리지해당없음해당없음무000002-3273-6181www.skrecycle.com2023-07-03
45(주)서우시스템즈서울특별시 동작구 상도로45길 31, 지하2층 (상도1동, 하이탑독서실)일반349.1282.024소기업20201125도시지역/주거지역/제2종일반주거지역대29172,공기 조화장치 제조업항온항습기<NA><NA>무<NA><NA><NA><NA>02-814-8241www.seowoo.com2023-07-03
56(주)세일카드씨스템서울특별시 동작구 노량진로26길 39-4 (본동)일반68.89101.877소기업20111025도시지역/주거지역/제1종일반주거지역대22299,그 외 기타 플라스틱 제품 제조업RF카드제조<NA><NA>무<NA><NA>1102-814-4961<NA>2023-07-03
67(주)웅림물산서울특별시 동작구 대림로 56 (신대방동)일반0.0216.260소기업20070703도시지역/주거지역/제3종일반주거지역대18119, 18113기타 인쇄업 외 1 종금융기관예금통장<NA><NA>무000002-835-1803<NA>2023-07-03
78(주)정인애드서울특별시 동작구 동작대로33길 28, 정인빌딩 (사당동)일반0.0439.2713소기업20160127도시지역/주거지역/제2종일반주거지역대18111, 18113경 인쇄업 외 1 종연구보고서 외해당없음해당없음무000002-3486-6791<NA>2023-07-03
89(주)태림서울특별시 동작구 국사봉길 8 (신대방동)일반162.0194.989소기업20140611도시지역/주거지역대10749, 10743기타 식품 첨가물 제조업 외 1 종소스류,식품첨가물해당없음해당없음무400002-827-0577www.tmgf.co.kr2023-07-03
910(주)한성세이프티서울특별시 동작구 상도로 52 (대방동)일반49.049.016소기업20100906도시지역/주거지역대22299, 20202그 외 기타 플라스틱 제품 제조업 외 1 종안전모해당없음해당없음무100002-821-1665www.hsafety.com2023-07-03
순번회사명공장대표주소설립구분용지면적건축면적종업원수공장크기등록일용도지역지목업종번호업종명생산품대기오염수질오염소음진동여부생활용수산업용수자기자본액타인자본액전화번호공장홈페이지데이터갱신일자
1920알림기획서울특별시 동작구 상도로 49, 395-21 (대방동, 황금빌딩)일반52.036.02소기업20220111도시지역/주거지역/제3종일반주거지역/미관지구대18111, 18112, 18113, 18119, 18121, 18122, 18129, 33910경 인쇄업 외 7 종인쇄(광고현수막)등해당없음해당없음무<NA><NA>7020<NA><NA>2023-07-03
2021영도기업(주)서울특별시 동작구 등용로 109-1 (대방동, 영도기업(주))일반100.0100.01소기업20160408도시지역/주거지역대33920,사무 및 회화용품 제조업포라스고무제품해당없음해당없음무100002-813-5014www.youngdoink.com2023-07-03
2122주식회사 대성알에스서울특별시 동작구 여의대방로24길 30, 3층 (신대방동)일반151.6151.62소기업20140724도시지역/주거지역/제3종일반주거지역대28903, 31202교통 신호장치 제조업 외 1 종철도신호용품<NA><NA>무<NA><NA><NA><NA>02-812-4595<NA>2023-07-03
2223주식회사 태성씨엔에쓰서울특별시 동작구 보라매로 78, 2층 (신대방) (신대방동, 성진빌딩)일반112.35112.3516소기업20200408도시지역/주거지역/제3종일반주거지역대28123,배전반 및 전기 자동제어반 제조업자동제어반<NA><NA>무<NA><NA><NA><NA>02-882-5506<NA>2023-07-03
2324주식회사 한미이앤씨기술사사무소서울특별시 동작구 노량진로 206, 2층 (노량진동, 백명트렌디타워)일반185.63185.6310소기업20220516도시지역/상업지역/일반상업지역/미관지구대28123,배전반 및 전기 자동제어반 제조업배전선로 전기분산 제어장치<NA><NA>무<NA><NA><NA><NA><NA><NA>2023-07-03
2425주식회사대신시앤에이서울특별시 동작구 상도로15길 83, 영우사빌딩 2층 (상도동)일반121.12121.123소기업20110705도시지역/주거지역/제3종일반주거지역대33910,간판 및 광고물 제조업간판,표지판,플래카드,배너<NA><NA>무<NA><NA>200<NA><NA><NA>2023-07-03
2526코리아케어서프라이(주)서울특별시 동작구 대방동15가길 23 (대방동, 한성빌딩)일반0.0167.972소기업20101013도시지역/주거지역/제2종일반주거지역대33999, 31991그 외 기타 달리 분류되지 않은 제품 제조업 외 1 종보행차(성인보행기)해당없음해당없음무0050002-701-8362www.kocas.co.kr2023-07-03
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