Overview

Dataset statistics

Number of variables6
Number of observations202
Missing cells2
Missing cells (%)0.2%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory9.8 KiB
Average record size in memory49.7 B

Variable types

Categorical2
Text2
DateTime1
Numeric1

Dataset

Description충청남도 공주시 산업단지입주기업현황에 대한 데이터로 (산업단지명, 기업명, 설립일자, 종업원수) 등의 항목을 제공합니다,
Author충청남도
URLhttps://alldam.chungnam.go.kr/index.chungnam?menuCd=DOM_000000201001001001&st=&cds=&orgCd=&apiType=&isOpen=Y&pageIndex=419&beforeMenuCd=DOM_000000201001001000&publicdatapk=15028943

Alerts

데이터기준일 has constant value ""Constant
종업원수 has 9 (4.5%) zerosZeros

Reproduction

Analysis started2024-01-09 21:25:30.901072
Analysis finished2024-01-09 21:25:31.353174
Duration0.45 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

단지명
Categorical

Distinct13
Distinct (%)6.4%
Missing0
Missing (%)0.0%
Memory size1.7 KiB
공주검상농공단지
40 
공주장기농공단지
40 
공주탄천일반산업단지
31 
공주정안제2농공단지
26 
공주정안농공단지
17 
Other values (8)
48 

Length

Max length13
Median length8
Mean length8.9752475
Min length8

Unique

Unique1 ?
Unique (%)0.5%

Sample

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

Common Values

ValueCountFrequency (%)
공주검상농공단지 40
19.8%
공주장기농공단지 40
19.8%
공주탄천일반산업단지 31
15.3%
공주정안제2농공단지 26
12.9%
공주정안농공단지 17
8.4%
공주월미농공단지 15
 
7.4%
공주유구자카드일반산업단지 11
 
5.4%
공주월미제2농공단지 7
 
3.5%
공주우성전문농공단지 5
 
2.5%
공주보물농공단지 4
 
2.0%
Other values (3) 6
 
3.0%

Length

2024-01-10T06:25:31.406157image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
공주검상농공단지 40
19.8%
공주장기농공단지 40
19.8%
공주탄천일반산업단지 31
15.3%
공주정안제2농공단지 26
12.9%
공주정안농공단지 17
8.4%
공주월미농공단지 15
 
7.4%
공주유구자카드일반산업단지 11
 
5.4%
공주월미제2농공단지 7
 
3.5%
공주우성전문농공단지 5
 
2.5%
공주보물농공단지 4
 
2.0%
Other values (3) 6
 
3.0%

회사명
Text

Distinct199
Distinct (%)98.5%
Missing0
Missing (%)0.0%
Memory size1.7 KiB
2024-01-10T06:25:31.618969image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length18
Median length15
Mean length8.5
Min length2

Characters and Unicode

Total characters1717
Distinct characters253
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

Unique196 ?
Unique (%)97.0%

Sample

1st row(주) 피엔제이 생활건강
2nd row(주)고려헬스팜
3rd row(주)고려화학엔지니어링
4th row(주)대덕바이오
5th row(주)신일팜글라스
ValueCountFrequency (%)
주식회사 19
 
7.5%
주)한엘 4
 
1.6%
솔브레인(주 4
 
1.6%
공주 4
 
1.6%
동원시스템즈(주 4
 
1.6%
주)엔씨켐 3
 
1.2%
공주공장 3
 
1.2%
제2공장 3
 
1.2%
주)대양이앤씨 2
 
0.8%
엠케이무역상사 2
 
0.8%
Other values (195) 205
81.0%
2024-01-10T06:25:31.943479image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
주 191
 
11.1%
( 152
 
8.9%
) 152
 
8.9%
이 54
 
3.1%
53
 
3.1%
공 48
 
2.8%
스 35
 
2.0%
장 31
 
1.8%
에 29
 
1.7%
사 29
 
1.7%
Other values (243) 943
54.9%

Most occurring categories

ValueCountFrequency (%)
Other Letter 1319
76.8%
Open Punctuation 152
 
8.9%
Close Punctuation 152
 
8.9%
Space Separator 53
 
3.1%
Decimal Number 21
 
1.2%
Uppercase Letter 12
 
0.7%
Dash Punctuation 5
 
0.3%
Other Punctuation 2
 
0.1%
Lowercase Letter 1
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
주 191
 
14.5%
이 54
 
4.1%
공 48
 
3.6%
스 35
 
2.7%
장 31
 
2.4%
에 29
 
2.2%
사 29
 
2.2%
식 27
 
2.0%
회 26
 
2.0%
제 25
 
1.9%
Other values (219) 824
62.5%
Uppercase Letter
ValueCountFrequency (%)
G 2
16.7%
S 2
16.7%
O 1
8.3%
K 1
8.3%
J 1
8.3%
B 1
8.3%
L 1
8.3%
C 1
8.3%
M 1
8.3%
F 1
8.3%
Decimal Number
ValueCountFrequency (%)
2 9
42.9%
1 4
19.0%
3 3
 
14.3%
4 2
 
9.5%
6 1
 
4.8%
7 1
 
4.8%
5 1
 
4.8%
Other Punctuation
ValueCountFrequency (%)
& 1
50.0%
· 1
50.0%
Open Punctuation
ValueCountFrequency (%)
( 152
100.0%
Close Punctuation
ValueCountFrequency (%)
) 152
100.0%
Space Separator
ValueCountFrequency (%)
53
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 5
100.0%
Lowercase Letter
ValueCountFrequency (%)
n 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 1319
76.8%
Common 385
 
22.4%
Latin 13
 
0.8%

Most frequent character per script

Hangul
ValueCountFrequency (%)
주 191
 
14.5%
이 54
 
4.1%
공 48
 
3.6%
스 35
 
2.7%
장 31
 
2.4%
에 29
 
2.2%
사 29
 
2.2%
식 27
 
2.0%
회 26
 
2.0%
제 25
 
1.9%
Other values (219) 824
62.5%
Common
ValueCountFrequency (%)
( 152
39.5%
) 152
39.5%
53
 
13.8%
2 9
 
2.3%
- 5
 
1.3%
1 4
 
1.0%
3 3
 
0.8%
4 2
 
0.5%
& 1
 
0.3%
6 1
 
0.3%
Other values (3) 3
 
0.8%
Latin
ValueCountFrequency (%)
G 2
15.4%
S 2
15.4%
O 1
7.7%
K 1
7.7%
J 1
7.7%
B 1
7.7%
n 1
7.7%
L 1
7.7%
C 1
7.7%
M 1
7.7%

Most occurring blocks

ValueCountFrequency (%)
Hangul 1319
76.8%
ASCII 397
 
23.1%
None 1
 
0.1%

Most frequent character per block

Hangul
ValueCountFrequency (%)
주 191
 
14.5%
이 54
 
4.1%
공 48
 
3.6%
스 35
 
2.7%
장 31
 
2.4%
에 29
 
2.2%
사 29
 
2.2%
식 27
 
2.0%
회 26
 
2.0%
제 25
 
1.9%
Other values (219) 824
62.5%
ASCII
ValueCountFrequency (%)
( 152
38.3%
) 152
38.3%
53
 
13.4%
2 9
 
2.3%
- 5
 
1.3%
1 4
 
1.0%
3 3
 
0.8%
G 2
 
0.5%
S 2
 
0.5%
4 2
 
0.5%
Other values (13) 13
 
3.3%
None
ValueCountFrequency (%)
· 1
100.0%

공장대표주소(도로명)
Text

Distinct174
Distinct (%)87.0%
Missing2
Missing (%)1.0%
Memory size1.7 KiB
2024-01-10T06:25:32.107893image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length47
Median length40
Mean length27.05
Min length16

Characters and Unicode

Total characters5410
Distinct characters127
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

Unique158 ?
Unique (%)79.0%

Sample

1st row충청남도 공주시 검상동 729-1
2nd row충청남도 공주시 공단길 33-7 (검상동, (주)고려양행)
3rd row충청남도 공주시 공단길 57 (검상동, (주)고려화학엔지니어)
4th row충청남도 공주시 공단길 33-42 (검상동, (주)대덕바이오)
5th row충청남도 공주시 공단길 75 (검상동, (주)신일유리)
ValueCountFrequency (%)
충청남도 200
18.2%
공주시 200
18.2%
정안면 46
 
4.2%
검상동 37
 
3.4%
공단길 36
 
3.3%
송선농공단지길 35
 
3.2%
정안농공단지길 32
 
2.9%
송선동 31
 
2.8%
탄천면 29
 
2.6%
외 27
 
2.5%
Other values (217) 427
38.8%
2024-01-10T06:25:32.388292image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
900
 
16.6%
공 316
 
5.8%
주 218
 
4.0%
시 201
 
3.7%
청 201
 
3.7%
충 200
 
3.7%
남 200
 
3.7%
도 200
 
3.7%
1 163
 
3.0%
지 157
 
2.9%
Other values (117) 2654
49.1%

Most occurring categories

ValueCountFrequency (%)
Other Letter 3336
61.7%
Space Separator 900
 
16.6%
Decimal Number 776
 
14.3%
Dash Punctuation 124
 
2.3%
Close Punctuation 118
 
2.2%
Open Punctuation 118
 
2.2%
Other Punctuation 30
 
0.6%
Uppercase Letter 6
 
0.1%
Other Symbol 2
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
공 316
 
9.5%
주 218
 
6.5%
시 201
 
6.0%
청 201
 
6.0%
충 200
 
6.0%
남 200
 
6.0%
도 200
 
6.0%
지 157
 
4.7%
길 146
 
4.4%
단 140
 
4.2%
Other values (97) 1357
40.7%
Decimal Number
ValueCountFrequency (%)
1 163
21.0%
2 135
17.4%
3 125
16.1%
4 86
11.1%
5 62
 
8.0%
6 60
 
7.7%
0 47
 
6.1%
8 35
 
4.5%
7 32
 
4.1%
9 31
 
4.0%
Uppercase Letter
ValueCountFrequency (%)
B 3
50.0%
T 1
 
16.7%
N 1
 
16.7%
E 1
 
16.7%
Space Separator
ValueCountFrequency (%)
900
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 124
100.0%
Close Punctuation
ValueCountFrequency (%)
) 118
100.0%
Open Punctuation
ValueCountFrequency (%)
( 118
100.0%
Other Punctuation
ValueCountFrequency (%)
, 30
100.0%
Other Symbol
ValueCountFrequency (%)
㈜ 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 3338
61.7%
Common 2066
38.2%
Latin 6
 
0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
공 316
 
9.5%
주 218
 
6.5%
시 201
 
6.0%
청 201
 
6.0%
충 200
 
6.0%
남 200
 
6.0%
도 200
 
6.0%
지 157
 
4.7%
길 146
 
4.4%
단 140
 
4.2%
Other values (98) 1359
40.7%
Common
ValueCountFrequency (%)
900
43.6%
1 163
 
7.9%
2 135
 
6.5%
3 125
 
6.1%
- 124
 
6.0%
) 118
 
5.7%
( 118
 
5.7%
4 86
 
4.2%
5 62
 
3.0%
6 60
 
2.9%
Other values (5) 175
 
8.5%
Latin
ValueCountFrequency (%)
B 3
50.0%
T 1
 
16.7%
N 1
 
16.7%
E 1
 
16.7%

Most occurring blocks

ValueCountFrequency (%)
Hangul 3336
61.7%
ASCII 2072
38.3%
None 2
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
900
43.4%
1 163
 
7.9%
2 135
 
6.5%
3 125
 
6.0%
- 124
 
6.0%
) 118
 
5.7%
( 118
 
5.7%
4 86
 
4.2%
5 62
 
3.0%
6 60
 
2.9%
Other values (9) 181
 
8.7%
Hangul
ValueCountFrequency (%)
공 316
 
9.5%
주 218
 
6.5%
시 201
 
6.0%
청 201
 
6.0%
충 200
 
6.0%
남 200
 
6.0%
도 200
 
6.0%
지 157
 
4.7%
길 146
 
4.4%
단 140
 
4.2%
Other values (97) 1357
40.7%
None
ValueCountFrequency (%)
㈜ 2
100.0%

등록일
Date

Distinct181
Distinct (%)89.6%
Missing0
Missing (%)0.0%
Memory size1.7 KiB
Minimum1999-10-02 00:00:00
Maximum2022-09-16 00:00:00
2024-01-10T06:25:32.493784image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T06:25:32.597627image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

종업원수
Real number (ℝ)

ZEROS 

Distinct66
Distinct (%)32.7%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean31.30198
Minimum0
Maximum928
Zeros9
Zeros (%)4.5%
Negative0
Negative (%)0.0%
Memory size1.9 KiB
2024-01-10T06:25:32.705584image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile1.05
Q16
median14
Q328
95-th percentile109.35
Maximum928
Range928
Interquartile range (IQR)22

Descriptive statistics

Standard deviation78.188781
Coefficient of variation (CV)2.4978861
Kurtosis89.147508
Mean31.30198
Median Absolute Deviation (MAD)9
Skewness8.4845525
Sum6323
Variance6113.4855
MonotonicityNot monotonic
2024-01-10T06:25:32.811133image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
4 13
 
6.4%
12 12
 
5.9%
6 10
 
5.0%
10 10
 
5.0%
5 10
 
5.0%
3 10
 
5.0%
0 9
 
4.5%
14 8
 
4.0%
9 6
 
3.0%
20 6
 
3.0%
Other values (56) 108
53.5%
ValueCountFrequency (%)
0 9
4.5%
1 2
 
1.0%
2 3
 
1.5%
3 10
5.0%
4 13
6.4%
5 10
5.0%
6 10
5.0%
7 4
 
2.0%
8 5
 
2.5%
9 6
3.0%
ValueCountFrequency (%)
928 1
0.5%
372 1
0.5%
339 1
0.5%
250 1
0.5%
164 1
0.5%
149 1
0.5%
140 1
0.5%
129 1
0.5%
120 1
0.5%
113 1
0.5%

데이터기준일
Categorical

CONSTANT 

Distinct1
Distinct (%)0.5%
Missing0
Missing (%)0.0%
Memory size1.7 KiB
2022-09-19
202 

Length

Max length10
Median length10
Mean length10
Min length10

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row2022-09-19
2nd row2022-09-19
3rd row2022-09-19
4th row2022-09-19
5th row2022-09-19

Common Values

ValueCountFrequency (%)
2022-09-19 202
100.0%

Length

2024-01-10T06:25:32.904245image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-01-10T06:25:32.983528image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2022-09-19 202
100.0%

Interactions

2024-01-10T06:25:31.159820image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-01-10T06:25:33.043536image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
단지명종업원수
단지명1.0000.404
종업원수0.4041.000
2024-01-10T06:25:33.126409image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
종업원수단지명
종업원수1.0000.209
단지명0.2091.000

Missing values

2024-01-10T06:25:31.243069image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-01-10T06:25:31.320869image/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

단지명회사명공장대표주소(도로명)등록일종업원수데이터기준일
0공주검상농공단지(주) 피엔제이 생활건강충청남도 공주시 검상동 729-12013-01-24422022-09-19
1공주검상농공단지(주)고려헬스팜충청남도 공주시 공단길 33-7 (검상동, (주)고려양행)2008-10-07182022-09-19
2공주검상농공단지(주)고려화학엔지니어링충청남도 공주시 공단길 57 (검상동, (주)고려화학엔지니어)1999-10-02172022-09-19
3공주검상농공단지(주)대덕바이오충청남도 공주시 공단길 33-42 (검상동, (주)대덕바이오)2010-05-24112022-09-19
4공주검상농공단지(주)신일팜글라스충청남도 공주시 공단길 75 (검상동, (주)신일유리)2006-03-08572022-09-19
5공주검상농공단지(주)에니켐텍충청남도 공주시 공단길 33-8 (검상동)2020-11-17142022-09-19
6공주검상농공단지(주)에스피충청남도 공주시 공단길 33-42 (검상동, (주)대덕바이오)2022-09-1692022-09-19
7공주검상농공단지(주)에이치케이피충청남도 공주시 공단길 75 (검상동)2019-02-12142022-09-19
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