Overview

Dataset statistics

Number of variables18
Number of observations29
Missing cells54
Missing cells (%)10.3%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory4.3 KiB
Average record size in memory152.6 B

Variable types

DateTime5
Numeric4
Text5
Categorical4

Dataset

Description샘플 데이터
Author한국평가데이터㈜
URLhttps://bigdata-region.kr/#/dataset/9930e436-d736-4ce3-8c09-f8082fa59eb5

Alerts

기준년월 has constant value ""Constant
금년결산기준일자 has constant value ""Constant
전년결산기준일자 has constant value ""Constant
전전년결산기준일자 has constant value ""Constant
정보기준일자 has constant value ""Constant
기업코드 is highly overall correlated with NET인증여부High correlation
금년연구개발비 is highly overall correlated with 전년연구개발비 and 1 other fieldsHigh correlation
전년연구개발비 is highly overall correlated with 금년연구개발비 and 1 other fieldsHigh correlation
전전년연구개발비 is highly overall correlated with 금년연구개발비 and 1 other fieldsHigh correlation
NET인증여부 is highly overall correlated with 기업코드 and 1 other fieldsHigh correlation
NET인증만료일자 is highly overall correlated with NET인증여부High correlation
NEP인증여부 is highly overall correlated with NEP인증만료일자High correlation
NEP인증만료일자 is highly overall correlated with NEP인증여부High correlation
NEP인증여부 is highly imbalanced (52.0%)Imbalance
NEP인증만료일자 is highly imbalanced (52.0%)Imbalance
금년연구개발비 has 10 (34.5%) missing valuesMissing
전년연구개발비 has 10 (34.5%) missing valuesMissing
전전년연구개발비 has 10 (34.5%) missing valuesMissing
주요제품2 has 11 (37.9%) missing valuesMissing
주요제품3 has 13 (44.8%) missing valuesMissing
기업코드 has unique valuesUnique
기업명 has unique valuesUnique
사업자등록번호 has unique valuesUnique
주요제품1 has unique valuesUnique

Reproduction

Analysis started2023-12-10 13:52:46.023575
Analysis finished2023-12-10 13:52:51.636460
Duration5.61 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

기준년월
Date

CONSTANT 

Distinct1
Distinct (%)3.4%
Missing0
Missing (%)0.0%
Memory size364.0 B
Minimum2023-01-01 00:00:00
Maximum2023-01-01 00:00:00
2023-12-10T22:52:51.706092image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T22:52:51.907621image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=1)

기업코드
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct29
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean192.06897
Minimum174
Maximum207
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size393.0 B
2023-12-10T22:52:52.157723image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum174
5-th percentile175.8
Q1185
median193
Q3200
95-th percentile205.6
Maximum207
Range33
Interquartile range (IQR)15

Descriptive statistics

Standard deviation9.8195542
Coefficient of variation (CV)0.051125148
Kurtosis-1.0021842
Mean192.06897
Median Absolute Deviation (MAD)8
Skewness-0.27559791
Sum5570
Variance96.423645
MonotonicityStrictly increasing
2023-12-10T22:52:52.358430image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=29)
ValueCountFrequency (%)
174 1
 
3.4%
175 1
 
3.4%
207 1
 
3.4%
206 1
 
3.4%
205 1
 
3.4%
204 1
 
3.4%
203 1
 
3.4%
202 1
 
3.4%
201 1
 
3.4%
200 1
 
3.4%
Other values (19) 19
65.5%
ValueCountFrequency (%)
174 1
3.4%
175 1
3.4%
177 1
3.4%
178 1
3.4%
181 1
3.4%
182 1
3.4%
183 1
3.4%
185 1
3.4%
186 1
3.4%
187 1
3.4%
ValueCountFrequency (%)
207 1
3.4%
206 1
3.4%
205 1
3.4%
204 1
3.4%
203 1
3.4%
202 1
3.4%
201 1
3.4%
200 1
3.4%
199 1
3.4%
198 1
3.4%

기업명
Text

UNIQUE 

Distinct29
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size364.0 B
2023-12-10T22:52:52.688894image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length6
Median length5
Mean length5.137931
Min length4

Characters and Unicode

Total characters149
Distinct characters69
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
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 row가나환경건설
2nd row가나환경개발
3rd row가나드림
4th row가나차이나
5th row가나쵸이스
ValueCountFrequency (%)
가나환경건설 1
 
3.4%
가나장작구이 1
 
3.4%
가나색연필 1
 
3.4%
가나프론티어 1
 
3.4%
가나프런티어 1
 
3.4%
가나커피숍 1
 
3.4%
가나특송 1
 
3.4%
가나클리닉 1
 
3.4%
가나식품유통 1
 
3.4%
가나민속주점 1
 
3.4%
Other values (19) 19
65.5%
2023-12-10T22:52:53.215763image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
가 30
20.1%
나 30
20.1%
이 6
 
4.0%
스 3
 
2.0%
어 3
 
2.0%
유 3
 
2.0%
낸 2
 
1.3%
파 2
 
1.3%
클 2
 
1.3%
시 2
 
1.3%
Other values (59) 66
44.3%

Most occurring categories

ValueCountFrequency (%)
Other Letter 149
100.0%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
가 30
20.1%
나 30
20.1%
이 6
 
4.0%
스 3
 
2.0%
어 3
 
2.0%
유 3
 
2.0%
낸 2
 
1.3%
파 2
 
1.3%
클 2
 
1.3%
시 2
 
1.3%
Other values (59) 66
44.3%

Most occurring scripts

ValueCountFrequency (%)
Hangul 149
100.0%

Most frequent character per script

Hangul
ValueCountFrequency (%)
가 30
20.1%
나 30
20.1%
이 6
 
4.0%
스 3
 
2.0%
어 3
 
2.0%
유 3
 
2.0%
낸 2
 
1.3%
파 2
 
1.3%
클 2
 
1.3%
시 2
 
1.3%
Other values (59) 66
44.3%

Most occurring blocks

ValueCountFrequency (%)
Hangul 149
100.0%

Most frequent character per block

Hangul
ValueCountFrequency (%)
가 30
20.1%
나 30
20.1%
이 6
 
4.0%
스 3
 
2.0%
어 3
 
2.0%
유 3
 
2.0%
낸 2
 
1.3%
파 2
 
1.3%
클 2
 
1.3%
시 2
 
1.3%
Other values (59) 66
44.3%

사업자등록번호
Text

UNIQUE 

Distinct29
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size364.0 B
2023-12-10T22:52:53.531679image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length12
Median length12
Mean length12
Min length12

Characters and Unicode

Total characters348
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

Unique29 ?
Unique (%)100.0%

Sample

1st row999-86-99902
2nd row999-86-99903
3rd row999-87-99905
4th row999-87-99906
5th row999-86-99909
ValueCountFrequency (%)
999-86-99902 1
 
3.4%
999-81-99922 1
 
3.4%
999-81-99934 1
 
3.4%
999-81-99933 1
 
3.4%
999-81-99932 1
 
3.4%
999-81-99931 1
 
3.4%
999-81-99930 1
 
3.4%
999-81-99929 1
 
3.4%
999-81-99928 1
 
3.4%
999-81-99927 1
 
3.4%
Other values (19) 19
65.5%
2023-12-10T22:52:54.041856image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
9 177
50.9%
- 58
 
16.7%
8 31
 
8.9%
1 29
 
8.3%
2 13
 
3.7%
6 10
 
2.9%
3 10
 
2.9%
0 8
 
2.3%
7 5
 
1.4%
5 4
 
1.1%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 290
83.3%
Dash Punctuation 58
 
16.7%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
9 177
61.0%
8 31
 
10.7%
1 29
 
10.0%
2 13
 
4.5%
6 10
 
3.4%
3 10
 
3.4%
0 8
 
2.8%
7 5
 
1.7%
5 4
 
1.4%
4 3
 
1.0%
Dash Punctuation
ValueCountFrequency (%)
- 58
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 348
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
9 177
50.9%
- 58
 
16.7%
8 31
 
8.9%
1 29
 
8.3%
2 13
 
3.7%
6 10
 
2.9%
3 10
 
2.9%
0 8
 
2.3%
7 5
 
1.4%
5 4
 
1.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 348
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
9 177
50.9%
- 58
 
16.7%
8 31
 
8.9%
1 29
 
8.3%
2 13
 
3.7%
6 10
 
2.9%
3 10
 
2.9%
0 8
 
2.3%
7 5
 
1.4%
5 4
 
1.1%

NET인증여부
Categorical

HIGH CORRELATION 

Distinct2
Distinct (%)6.9%
Missing0
Missing (%)0.0%
Memory size364.0 B
Y
18 
11 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
Y 18
62.1%
11
37.9%

Length

2023-12-10T22:52:54.260502image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T22:52:54.417538image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
y 18
100.0%

NET인증만료일자
Categorical

HIGH CORRELATION 

Distinct8
Distinct (%)27.6%
Missing0
Missing (%)0.0%
Memory size364.0 B
11 
2023-08-31
6 
2024-08-10
3 
2023-11-11
3 
2023-07-05
2 
Other values (3)
4 

Length

Max length10
Median length10
Mean length6.5862069
Min length1

Unique

Unique2 ?
Unique (%)6.9%

Sample

1st row2024-01-31
2nd row2024-08-10
3rd row2024-08-31
4th row2023-11-11
5th row2023-08-31

Common Values

ValueCountFrequency (%)
11
37.9%
2023-08-31 6
20.7%
2024-08-10 3
 
10.3%
2023-11-11 3
 
10.3%
2023-07-05 2
 
6.9%
2024-12-31 2
 
6.9%
2024-01-31 1
 
3.4%
2024-08-31 1
 
3.4%

Length

2023-12-10T22:52:54.713852image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T22:52:54.934540image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2023-08-31 6
33.3%
2024-08-10 3
16.7%
2023-11-11 3
16.7%
2023-07-05 2
 
11.1%
2024-12-31 2
 
11.1%
2024-01-31 1
 
5.6%
2024-08-31 1
 
5.6%

NEP인증여부
Categorical

HIGH CORRELATION  IMBALANCE 

Distinct2
Distinct (%)6.9%
Missing0
Missing (%)0.0%
Memory size364.0 B
26 
Y
3 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row
2nd row
3rd row
4th row
5th rowY

Common Values

ValueCountFrequency (%)
26
89.7%
Y 3
 
10.3%

Length

2023-12-10T22:52:55.216666image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T22:52:55.396099image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
y 3
100.0%

NEP인증만료일자
Categorical

HIGH CORRELATION  IMBALANCE 

Distinct2
Distinct (%)6.9%
Missing0
Missing (%)0.0%
Memory size364.0 B
26 
2024-08-10
3 

Length

Max length10
Median length1
Mean length1.9310345
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row
2nd row
3rd row
4th row
5th row2024-08-10

Common Values

ValueCountFrequency (%)
26
89.7%
2024-08-10 3
 
10.3%

Length

2023-12-10T22:52:55.626712image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T22:52:55.771612image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2024-08-10 3
100.0%

금년결산기준일자
Date

CONSTANT 

Distinct1
Distinct (%)3.4%
Missing0
Missing (%)0.0%
Memory size364.0 B
Minimum2022-12-31 00:00:00
Maximum2022-12-31 00:00:00
2023-12-10T22:52:55.896074image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T22:52:56.040655image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=1)

전년결산기준일자
Date

CONSTANT 

Distinct1
Distinct (%)3.4%
Missing0
Missing (%)0.0%
Memory size364.0 B
Minimum2021-12-31 00:00:00
Maximum2021-12-31 00:00:00
2023-12-10T22:52:56.213105image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T22:52:56.400966image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=1)

전전년결산기준일자
Date

CONSTANT 

Distinct1
Distinct (%)3.4%
Missing0
Missing (%)0.0%
Memory size364.0 B
Minimum2020-12-31 00:00:00
Maximum2020-12-31 00:00:00
2023-12-10T22:52:56.544353image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T22:52:56.709202image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=1)

금년연구개발비
Real number (ℝ)

HIGH CORRELATION  MISSING 

Distinct19
Distinct (%)100.0%
Missing10
Missing (%)34.5%
Infinite0
Infinite (%)0.0%
Mean10214765
Minimum110742
Maximum1.1776572 × 108
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size393.0 B
2023-12-10T22:52:56.926066image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum110742
5-th percentile140590.5
Q11767458
median3506887
Q35573743.5
95-th percentile26792172
Maximum1.1776572 × 108
Range1.1765498 × 108
Interquartile range (IQR)3806285.5

Descriptive statistics

Standard deviation26389453
Coefficient of variation (CV)2.5834616
Kurtosis17.850311
Mean10214765
Median Absolute Deviation (MAD)1959218
Skewness4.1785076
Sum1.9408053 × 108
Variance6.9640323 × 1014
MonotonicityNot monotonic
2023-12-10T22:52:57.181972image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=19)
ValueCountFrequency (%)
6256000 1
 
3.4%
2182784 1
 
3.4%
602236 1
 
3.4%
1547669 1
 
3.4%
3051600 1
 
3.4%
4307500 1
 
3.4%
510000 1
 
3.4%
16684000 1
 
3.4%
1987247 1
 
3.4%
3506887 1
 
3.4%
Other values (9) 9
31.0%
(Missing) 10
34.5%
ValueCountFrequency (%)
110742 1
3.4%
143907 1
3.4%
510000 1
3.4%
602236 1
3.4%
1547669 1
3.4%
1987247 1
3.4%
2182784 1
3.4%
2280498 1
3.4%
3051600 1
3.4%
3506887 1
3.4%
ValueCountFrequency (%)
117765718 1
3.4%
16684000 1
3.4%
13122580 1
3.4%
6256000 1
3.4%
5930581 1
3.4%
5216906 1
3.4%
4881675 1
3.4%
4307500 1
3.4%
3992000 1
3.4%
3506887 1
3.4%

전년연구개발비
Real number (ℝ)

HIGH CORRELATION  MISSING 

Distinct19
Distinct (%)100.0%
Missing10
Missing (%)34.5%
Infinite0
Infinite (%)0.0%
Mean9473342.2
Minimum52144
Maximum1.12664 × 108
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size393.0 B
2023-12-10T22:52:57.497252image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum52144
5-th percentile80610.1
Q11395373.5
median2681221
Q34396761
95-th percentile26214500
Maximum1.12664 × 108
Range1.1261186 × 108
Interquartile range (IQR)3001387.5

Descriptive statistics

Standard deviation25316724
Coefficient of variation (CV)2.6724174
Kurtosis17.859569
Mean9473342.2
Median Absolute Deviation (MAD)1828486
Skewness4.1812138
Sum1.799935 × 108
Variance6.4093651 × 1014
MonotonicityNot monotonic
2023-12-10T22:52:57.722209image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=19)
ValueCountFrequency (%)
4144214 1
 
3.4%
852735 1
 
3.4%
443345 1
 
3.4%
2056045 1
 
3.4%
2529703 1
 
3.4%
4211074 1
 
3.4%
404000 1
 
3.4%
16609000 1
 
3.4%
1938012 1
 
3.4%
2681221 1
 
3.4%
Other values (9) 9
31.0%
(Missing) 10
34.5%
ValueCountFrequency (%)
52144 1
3.4%
83773 1
3.4%
404000 1
3.4%
443345 1
3.4%
852735 1
3.4%
1938012 1
3.4%
2056045 1
3.4%
2227333 1
3.4%
2529703 1
3.4%
2681221 1
3.4%
ValueCountFrequency (%)
112664000 1
3.4%
16609000 1
3.4%
11390297 1
3.4%
5517755 1
3.4%
4553000 1
3.4%
4240522 1
3.4%
4211074 1
3.4%
4144214 1
3.4%
3395328 1
3.4%
2681221 1
3.4%

전전년연구개발비
Real number (ℝ)

HIGH CORRELATION  MISSING 

Distinct19
Distinct (%)100.0%
Missing10
Missing (%)34.5%
Infinite0
Infinite (%)0.0%
Mean10159345
Minimum5397
Maximum1.28773 × 108
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size393.0 B
2023-12-10T22:52:58.103618image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum5397
5-th percentile62907
Q1760508.5
median2369487
Q33536659
95-th percentile29289700
Maximum1.28773 × 108
Range1.287676 × 108
Interquartile range (IQR)2776150.5

Descriptive statistics

Standard deviation29117089
Coefficient of variation (CV)2.8660399
Kurtosis17.810406
Mean10159345
Median Absolute Deviation (MAD)1419164
Skewness4.174784
Sum1.9302756 × 108
Variance8.4780487 × 1014
MonotonicityNot monotonic
2023-12-10T22:52:58.372270image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=19)
ValueCountFrequency (%)
2249921 1
 
3.4%
950323 1
 
3.4%
307786 1
 
3.4%
2151495 1
 
3.4%
14416518 1
 
3.4%
2922223 1
 
3.4%
570694 1
 
3.4%
18236000 1
 
3.4%
1308250 1
 
3.4%
2369487 1
 
3.4%
Other values (9) 9
31.0%
(Missing) 10
34.5%
ValueCountFrequency (%)
5397 1
3.4%
69297 1
3.4%
227872 1
3.4%
307786 1
3.4%
570694 1
3.4%
950323 1
3.4%
1308250 1
3.4%
2151495 1
3.4%
2249921 1
3.4%
2369487 1
3.4%
ValueCountFrequency (%)
128773000 1
3.4%
18236000 1
3.4%
14416518 1
3.4%
5282853 1
3.4%
3700000 1
3.4%
3373318 1
3.4%
3211995 1
3.4%
2922223 1
3.4%
2901130 1
3.4%
2369487 1
3.4%

주요제품1
Text

UNIQUE 

Distinct29
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size364.0 B
2023-12-10T22:52:58.806111image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length48
Median length35
Mean length16.655172
Min length2

Characters and Unicode

Total characters483
Distinct characters169
Distinct categories7 ?
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 row차량용 배터리
2nd rowCOWL CROSS MEMBER
3rd row여성내의류
4th row자기관리부동산투자(공동주택 신축 및 분양; 임대; 부동산펀드 지분투자 등)
5th row가공직물
ValueCountFrequency (%)
등 8
 
8.6%
외 4
 
4.3%
및 3
 
3.2%
엔진 2
 
2.2%
임대 2
 
2.2%
차량용 1
 
1.1%
항공운송 1
 
1.1%
발전기 1
 
1.1%
산업용 1
 
1.1%
등(선박용 1
 
1.1%
Other values (69) 69
74.2%
2023-12-10T22:52:59.448726image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
65
 
13.5%
; 32
 
6.6%
기 14
 
2.9%
등 11
 
2.3%
류 7
 
1.4%
) 7
 
1.4%
( 7
 
1.4%
E 6
 
1.2%
공 6
 
1.2%
산 6
 
1.2%
Other values (159) 322
66.7%

Most occurring categories

ValueCountFrequency (%)
Other Letter 295
61.1%
Space Separator 65
 
13.5%
Uppercase Letter 59
 
12.2%
Other Punctuation 39
 
8.1%
Close Punctuation 9
 
1.9%
Open Punctuation 9
 
1.9%
Lowercase Letter 7
 
1.4%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
기 14
 
4.7%
등 11
 
3.7%
류 7
 
2.4%
공 6
 
2.0%
산 6
 
2.0%
자 6
 
2.0%
물 5
 
1.7%
동 5
 
1.7%
화 5
 
1.7%
외 5
 
1.7%
Other values (126) 225
76.3%
Uppercase Letter
ValueCountFrequency (%)
E 6
 
10.2%
S 5
 
8.5%
C 5
 
8.5%
A 5
 
8.5%
R 5
 
8.5%
P 4
 
6.8%
M 4
 
6.8%
O 4
 
6.8%
T 3
 
5.1%
H 3
 
5.1%
Other values (9) 15
25.4%
Lowercase Letter
ValueCountFrequency (%)
o 2
28.6%
n 1
14.3%
i 1
14.3%
t 1
14.3%
l 1
14.3%
u 1
14.3%
Other Punctuation
ValueCountFrequency (%)
; 32
82.1%
/ 6
 
15.4%
& 1
 
2.6%
Close Punctuation
ValueCountFrequency (%)
) 7
77.8%
] 2
 
22.2%
Open Punctuation
ValueCountFrequency (%)
( 7
77.8%
[ 2
 
22.2%
Space Separator
ValueCountFrequency (%)
65
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 295
61.1%
Common 122
25.3%
Latin 66
 
13.7%

Most frequent character per script

Hangul
ValueCountFrequency (%)
기 14
 
4.7%
등 11
 
3.7%
류 7
 
2.4%
공 6
 
2.0%
산 6
 
2.0%
자 6
 
2.0%
물 5
 
1.7%
동 5
 
1.7%
화 5
 
1.7%
외 5
 
1.7%
Other values (126) 225
76.3%
Latin
ValueCountFrequency (%)
E 6
 
9.1%
S 5
 
7.6%
C 5
 
7.6%
A 5
 
7.6%
R 5
 
7.6%
P 4
 
6.1%
M 4
 
6.1%
O 4
 
6.1%
T 3
 
4.5%
H 3
 
4.5%
Other values (15) 22
33.3%
Common
ValueCountFrequency (%)
65
53.3%
; 32
26.2%
) 7
 
5.7%
( 7
 
5.7%
/ 6
 
4.9%
] 2
 
1.6%
[ 2
 
1.6%
& 1
 
0.8%

Most occurring blocks

ValueCountFrequency (%)
Hangul 295
61.1%
ASCII 188
38.9%

Most frequent character per block

ASCII
ValueCountFrequency (%)
65
34.6%
; 32
17.0%
) 7
 
3.7%
( 7
 
3.7%
E 6
 
3.2%
/ 6
 
3.2%
S 5
 
2.7%
C 5
 
2.7%
A 5
 
2.7%
R 5
 
2.7%
Other values (23) 45
23.9%
Hangul
ValueCountFrequency (%)
기 14
 
4.7%
등 11
 
3.7%
류 7
 
2.4%
공 6
 
2.0%
산 6
 
2.0%
자 6
 
2.0%
물 5
 
1.7%
동 5
 
1.7%
화 5
 
1.7%
외 5
 
1.7%
Other values (126) 225
76.3%

주요제품2
Text

MISSING 

Distinct17
Distinct (%)94.4%
Missing11
Missing (%)37.9%
Memory size364.0 B
2023-12-10T22:52:59.773337image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length37
Median length11
Mean length8.2222222
Min length2

Characters and Unicode

Total characters148
Distinct characters78
Distinct categories6 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique16 ?
Unique (%)88.9%

Sample

1st row산업용 축전지
2nd rowDASH PANE
3rd row스타킹
4th row투자중개
5th row기타
ValueCountFrequency (%)
기타 4
 
10.8%
등 2
 
5.4%
판매 1
 
2.7%
lpm 1
 
2.7%
가공보드 1
 
2.7%
pb 1
 
2.7%
합판 1
 
2.7%
원목 1
 
2.7%
수입 1
 
2.7%
원재료 1
 
2.7%
Other values (23) 23
62.2%
2023-12-10T22:53:00.455995image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
19
 
12.8%
기 6
 
4.1%
타 6
 
4.1%
; 5
 
3.4%
A 4
 
2.7%
스 4
 
2.7%
품 4
 
2.7%
전 4
 
2.7%
P 3
 
2.0%
E 3
 
2.0%
Other values (68) 90
60.8%

Most occurring categories

ValueCountFrequency (%)
Other Letter 92
62.2%
Uppercase Letter 24
 
16.2%
Space Separator 19
 
12.8%
Other Punctuation 5
 
3.4%
Open Punctuation 4
 
2.7%
Close Punctuation 4
 
2.7%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
기 6
 
6.5%
타 6
 
6.5%
스 4
 
4.3%
품 4
 
4.3%
전 4
 
4.3%
판 3
 
3.3%
등 3
 
3.3%
용 2
 
2.2%
상 2
 
2.2%
료 2
 
2.2%
Other values (50) 56
60.9%
Uppercase Letter
ValueCountFrequency (%)
A 4
16.7%
P 3
12.5%
E 3
12.5%
M 3
12.5%
B 2
8.3%
L 2
8.3%
D 2
8.3%
F 1
 
4.2%
S 1
 
4.2%
H 1
 
4.2%
Other values (2) 2
8.3%
Open Punctuation
ValueCountFrequency (%)
( 2
50.0%
[ 2
50.0%
Close Punctuation
ValueCountFrequency (%)
) 2
50.0%
] 2
50.0%
Space Separator
ValueCountFrequency (%)
19
100.0%
Other Punctuation
ValueCountFrequency (%)
; 5
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 92
62.2%
Common 32
 
21.6%
Latin 24
 
16.2%

Most frequent character per script

Hangul
ValueCountFrequency (%)
기 6
 
6.5%
타 6
 
6.5%
스 4
 
4.3%
품 4
 
4.3%
전 4
 
4.3%
판 3
 
3.3%
등 3
 
3.3%
용 2
 
2.2%
상 2
 
2.2%
료 2
 
2.2%
Other values (50) 56
60.9%
Latin
ValueCountFrequency (%)
A 4
16.7%
P 3
12.5%
E 3
12.5%
M 3
12.5%
B 2
8.3%
L 2
8.3%
D 2
8.3%
F 1
 
4.2%
S 1
 
4.2%
H 1
 
4.2%
Other values (2) 2
8.3%
Common
ValueCountFrequency (%)
19
59.4%
; 5
 
15.6%
( 2
 
6.2%
) 2
 
6.2%
] 2
 
6.2%
[ 2
 
6.2%

Most occurring blocks

ValueCountFrequency (%)
Hangul 92
62.2%
ASCII 56
37.8%

Most frequent character per block

ASCII
ValueCountFrequency (%)
19
33.9%
; 5
 
8.9%
A 4
 
7.1%
P 3
 
5.4%
E 3
 
5.4%
M 3
 
5.4%
B 2
 
3.6%
( 2
 
3.6%
) 2
 
3.6%
L 2
 
3.6%
Other values (8) 11
19.6%
Hangul
ValueCountFrequency (%)
기 6
 
6.5%
타 6
 
6.5%
스 4
 
4.3%
품 4
 
4.3%
전 4
 
4.3%
판 3
 
3.3%
등 3
 
3.3%
용 2
 
2.2%
상 2
 
2.2%
료 2
 
2.2%
Other values (50) 56
60.9%

주요제품3
Text

MISSING 

Distinct16
Distinct (%)100.0%
Missing13
Missing (%)44.8%
Memory size364.0 B
2023-12-10T22:53:00.777130image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length21
Median length12
Mean length7.75
Min length3

Characters and Unicode

Total characters124
Distinct characters80
Distinct categories6 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique16 ?
Unique (%)100.0%

Sample

1st row지분법이익
2nd rowHEAT PROTECTOR PANEL
3rd row투자일임
4th row메시지
5th row란제리
ValueCountFrequency (%)
외 3
 
11.5%
제품 2
 
7.7%
판프랜지 1
 
3.8%
부품 1
 
3.8%
스테인레스 1
 
3.8%
유기질 1
 
3.8%
연결조정 1
 
3.8%
항공운송지원서비스 1
 
3.8%
한국지역난방공사]업무용 1
 
3.8%
증명발급기 1
 
3.8%
Other values (13) 13
50.0%
2023-12-10T22:53:01.336035image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
12
 
9.7%
지 5
 
4.0%
품 5
 
4.0%
O 3
 
2.4%
스 3
 
2.4%
외 3
 
2.4%
T 3
 
2.4%
R 3
 
2.4%
E 3
 
2.4%
제 3
 
2.4%
Other values (70) 81
65.3%

Most occurring categories

ValueCountFrequency (%)
Other Letter 80
64.5%
Uppercase Letter 23
 
18.5%
Space Separator 12
 
9.7%
Close Punctuation 4
 
3.2%
Open Punctuation 4
 
3.2%
Dash Punctuation 1
 
0.8%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
지 5
 
6.2%
품 5
 
6.2%
스 3
 
3.8%
외 3
 
3.8%
제 3
 
3.8%
판 2
 
2.5%
공 2
 
2.5%
부 2
 
2.5%
기 2
 
2.5%
송 1
 
1.2%
Other values (52) 52
65.0%
Uppercase Letter
ValueCountFrequency (%)
O 3
13.0%
T 3
13.0%
R 3
13.0%
E 3
13.0%
P 2
8.7%
A 2
8.7%
C 2
8.7%
D 1
 
4.3%
U 1
 
4.3%
H 1
 
4.3%
Other values (2) 2
8.7%
Close Punctuation
ValueCountFrequency (%)
) 2
50.0%
] 2
50.0%
Open Punctuation
ValueCountFrequency (%)
[ 2
50.0%
( 2
50.0%
Space Separator
ValueCountFrequency (%)
12
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 80
64.5%
Latin 23
 
18.5%
Common 21
 
16.9%

Most frequent character per script

Hangul
ValueCountFrequency (%)
지 5
 
6.2%
품 5
 
6.2%
스 3
 
3.8%
외 3
 
3.8%
제 3
 
3.8%
판 2
 
2.5%
공 2
 
2.5%
부 2
 
2.5%
기 2
 
2.5%
송 1
 
1.2%
Other values (52) 52
65.0%
Latin
ValueCountFrequency (%)
O 3
13.0%
T 3
13.0%
R 3
13.0%
E 3
13.0%
P 2
8.7%
A 2
8.7%
C 2
8.7%
D 1
 
4.3%
U 1
 
4.3%
H 1
 
4.3%
Other values (2) 2
8.7%
Common
ValueCountFrequency (%)
12
57.1%
) 2
 
9.5%
] 2
 
9.5%
[ 2
 
9.5%
( 2
 
9.5%
- 1
 
4.8%

Most occurring blocks

ValueCountFrequency (%)
Hangul 80
64.5%
ASCII 44
35.5%

Most frequent character per block

ASCII
ValueCountFrequency (%)
12
27.3%
O 3
 
6.8%
T 3
 
6.8%
R 3
 
6.8%
E 3
 
6.8%
) 2
 
4.5%
] 2
 
4.5%
P 2
 
4.5%
A 2
 
4.5%
[ 2
 
4.5%
Other values (8) 10
22.7%
Hangul
ValueCountFrequency (%)
지 5
 
6.2%
품 5
 
6.2%
스 3
 
3.8%
외 3
 
3.8%
제 3
 
3.8%
판 2
 
2.5%
공 2
 
2.5%
부 2
 
2.5%
기 2
 
2.5%
송 1
 
1.2%
Other values (52) 52
65.0%

정보기준일자
Date

CONSTANT 

Distinct1
Distinct (%)3.4%
Missing0
Missing (%)0.0%
Memory size364.0 B
Minimum2023-06-25 00:00:00
Maximum2023-06-25 00:00:00
2023-12-10T22:53:01.600227image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T22:53:01.835492image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=1)

Interactions

2023-12-10T22:52:49.558458image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T22:52:47.435246image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T22:52:47.971345image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T22:52:48.536761image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T22:52:49.694225image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T22:52:47.577338image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T22:52:48.102933image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T22:52:48.678942image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T22:52:49.894311image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T22:52:47.708655image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T22:52:48.232776image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T22:52:49.168231image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T22:52:50.201071image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T22:52:47.834409image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T22:52:48.386143image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T22:52:49.383761image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-10T22:53:02.040957image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
기업코드기업명사업자등록번호NET인증여부NET인증만료일자NEP인증여부NEP인증만료일자금년연구개발비전년연구개발비전전년연구개발비주요제품1주요제품2주요제품3
기업코드1.0001.0001.0000.8230.5540.6070.6070.0000.0000.2651.0000.9311.000
기업명1.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.000
사업자등록번호1.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.000
NET인증여부0.8231.0001.0001.0001.0000.0000.0000.0000.0000.0001.0000.0001.000
NET인증만료일자0.5541.0001.0001.0001.0000.1880.1880.0000.0000.0001.0000.9551.000
NEP인증여부0.6071.0001.0000.0000.1881.0000.9540.0000.0000.0001.000NaNNaN
NEP인증만료일자0.6071.0001.0000.0000.1880.9541.0000.0000.0000.0001.000NaNNaN
금년연구개발비0.0001.0001.0000.0000.0000.0000.0001.0001.0000.9511.0001.0001.000
전년연구개발비0.0001.0001.0000.0000.0000.0000.0001.0001.0000.9511.0001.0001.000
전전년연구개발비0.2651.0001.0000.0000.0000.0000.0000.9510.9511.0001.0001.0001.000
주요제품11.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.000
주요제품20.9311.0001.0000.0000.955NaNNaN1.0001.0001.0001.0001.0001.000
주요제품31.0001.0001.0001.0001.000NaNNaN1.0001.0001.0001.0001.0001.000
2023-12-10T22:53:02.289195image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
NEP인증만료일자NET인증여부NET인증만료일자NEP인증여부
NEP인증만료일자1.0000.0000.0820.806
NET인증여부0.0001.0000.8820.000
NET인증만료일자0.0820.8821.0000.082
NEP인증여부0.8060.0000.0821.000
2023-12-10T22:53:02.903173image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
기업코드금년연구개발비전년연구개발비전전년연구개발비NET인증여부NET인증만료일자NEP인증여부NEP인증만료일자
기업코드1.000-0.389-0.321-0.1120.5580.2000.3970.397
금년연구개발비-0.3891.0000.9600.8840.0000.0000.0000.000
전년연구개발비-0.3210.9601.0000.9010.0000.0000.0000.000
전전년연구개발비-0.1120.8840.9011.0000.0000.0000.0000.000
NET인증여부0.5580.0000.0000.0001.0000.8820.0000.000
NET인증만료일자0.2000.0000.0000.0000.8821.0000.0820.082
NEP인증여부0.3970.0000.0000.0000.0000.0821.0000.806
NEP인증만료일자0.3970.0000.0000.0000.0000.0820.8061.000

Missing values

2023-12-10T22:52:50.471810image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-10T22:52:51.082652image/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.
2023-12-10T22:52:51.521952image/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

기준년월기업코드기업명사업자등록번호NET인증여부NET인증만료일자NEP인증여부NEP인증만료일자금년결산기준일자전년결산기준일자전전년결산기준일자금년연구개발비전년연구개발비전전년연구개발비주요제품1주요제품2주요제품3정보기준일자
02023-01174가나환경건설999-86-99902Y2024-01-312022-12-312021-12-312020-12-31350688726812212369487차량용 배터리산업용 축전지지분법이익2023-06-25
12023-01175가나환경개발999-86-99903Y2024-08-102022-12-312021-12-312020-12-3162560004144214<NA>COWL CROSS MEMBERDASH PANEHEAT PROTECTOR PANEL2023-06-25
22023-01177가나드림999-87-99905Y2024-08-312022-12-312021-12-312020-12-31<NA><NA><NA>여성내의류스타킹<NA>2023-06-25
32023-01178가나차이나999-87-99906Y2023-11-112022-12-312021-12-312020-12-31<NA><NA><NA>자기관리부동산투자(공동주택 신축 및 분양; 임대; 부동산펀드 지분투자 등)<NA><NA>2023-06-25
42023-01181가나쵸이스999-86-99909Y2023-08-31Y2024-08-102022-12-312021-12-312020-12-31<NA><NA><NA>가공직물<NA><NA>2023-06-25
52023-01182가나이화999-86-99910Y2023-11-11Y2024-08-102022-12-312021-12-312020-12-31<NA><NA><NA>손해보험(자동차;화재;해상;특종);장기(질병;상해등);연금(개인;퇴직)일반보험 외<NA><NA>2023-06-25
62023-01183가나최가네999-81-99911Y2023-08-312022-12-312021-12-312020-12-31<NA><NA><NA>투자매매투자중개투자일임2023-06-25
72023-01185가나유라시아999-86-99913Y2023-08-312022-12-312021-12-312020-12-31<NA><NA><NA>광고기타메시지2023-06-25
82023-01186가나기독교999-86-99914Y2023-07-052022-12-312021-12-312020-12-31<NA><NA><NA>임대화운데이션란제리2023-06-25
92023-01187가나정공999-81-99915Y2024-08-102022-12-312021-12-312020-12-31228049822273332249921절연선전력선소재(CU-ROD)2023-06-25
기준년월기업코드기업명사업자등록번호NET인증여부NET인증만료일자NEP인증여부NEP인증만료일자금년결산기준일자전년결산기준일자전전년결산기준일자금년연구개발비전년연구개발비전전년연구개발비주요제품1주요제품2주요제품3정보기준일자
192023-01198가나깨끗한999-81-999262022-12-312021-12-312020-12-31<NA><NA><NA>ROSE임대증명발급기 외2023-06-25
202023-01199가나민속주점999-81-999272022-12-312021-12-312020-12-31198724719380121308250[한국지역난방공사]구역전기사업[한국지역난방공사]발전사업[한국지역난방공사]업무용2023-06-25
212023-01200가나식품유통999-81-999282022-12-312021-12-312020-12-31166840001660900018236000물류센터; 지식산업센터; 오피스텔 등의 건축공사; 건축물 주요구조부 PC 제조 및 설치<NA><NA>2023-06-25
222023-01201가나클리닉999-81-999292022-12-312021-12-312020-12-31510000404000570694항공운송정보통신항공운송지원서비스2023-06-25
232023-01202가나특송999-81-999302022-12-312021-12-312020-12-31<NA><NA><NA>건강기능식품기타연결조정2023-06-25
242023-01203가나커피숍999-81-99931Y2024-08-102022-12-312021-12-312020-12-31430750042110742922223디젤엔진 등(선박용 엔진; 산업용 발전기 엔진); 특수엔진; 예인음탐기 외<NA><NA>2023-06-25
252023-01204가나프런티어999-81-99932Y2024-12-312022-12-312021-12-312020-12-313051600252970314416518가성칼륨; 탄산칼륨; 액체염소 등MDF; LPM; 기타 가공보드; PB; 합판; 원목 수입 판매 등<NA>2023-06-25
262023-01205가나프론티어999-81-999332022-12-312021-12-312020-12-31154766920560452151495공사수익스테인레스 판 외 (상품)스테인레스 판 외 (제품)2023-06-25
272023-01206가나색연필999-81-999342022-12-312021-12-312020-12-31602236443345307786W/PUMP; AUTO PART; AL CYLINDER HEAD<NA><NA>2023-06-25
282023-01207가나사료999-81-999352022-12-312021-12-312020-12-312182784852735950323우유류; 분유류; 음료류(차; 커피; 생수 등); 치즈류; 발효유류; 외식산업 외<NA><NA>2023-06-25