Overview

Dataset statistics

Number of variables15
Number of observations21
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory2.9 KiB
Average record size in memory140.1 B

Variable types

Text1
Numeric14

Dataset

Description중소벤처기업진흥공단이 중소기업을 대상으로 제공하는 정책자금의 자산 규모별 집행실적을 개방하여, 중소기업이 정책자금 신청 시 이를 활용할 수 있도록 개방
Author중소벤처기업진흥공단
URLhttps://www.data.go.kr/data/15107072/fileData.do

Alerts

10억미만 건수 is highly overall correlated with 10억미만 금액 and 5 other fieldsHigh correlation
10억미만 금액 is highly overall correlated with 10억미만 건수 and 8 other fieldsHigh correlation
30억미만 건수 is highly overall correlated with 10억미만 건수 and 10 other fieldsHigh correlation
30억미만 금액 is highly overall correlated with 10억미만 건수 and 10 other fieldsHigh correlation
70억미만 건수 is highly overall correlated with 10억미만 건수 and 10 other fieldsHigh correlation
70억미만 금액 is highly overall correlated with 10억미만 금액 and 9 other fieldsHigh correlation
100억미만 건수 is highly overall correlated with 10억미만 금액 and 9 other fieldsHigh correlation
100억미만 금액 is highly overall correlated with 10억미만 금액 and 9 other fieldsHigh correlation
200억미만 건수 is highly overall correlated with 30억미만 건수 and 8 other fieldsHigh correlation
200억미만 금액 is highly overall correlated with 30억미만 건수 and 8 other fieldsHigh correlation
200억이상 건수 is highly overall correlated with 70억미만 건수 and 6 other fieldsHigh correlation
200억이상 금액 is highly overall correlated with 30억미만 금액 and 7 other fieldsHigh correlation
재무제표미등록 건수 is highly overall correlated with 10억미만 건수 and 3 other fieldsHigh correlation
재무제표미등록 금액 is highly overall correlated with 10억미만 건수 and 4 other fieldsHigh correlation
구분 has unique valuesUnique
10억미만 금액 has unique valuesUnique
30억미만 건수 has unique valuesUnique
30억미만 금액 has unique valuesUnique
10억미만 건수 has 1 (4.8%) zerosZeros
10억미만 금액 has 1 (4.8%) zerosZeros
30억미만 건수 has 1 (4.8%) zerosZeros
30억미만 금액 has 1 (4.8%) zerosZeros
70억미만 건수 has 1 (4.8%) zerosZeros
70억미만 금액 has 1 (4.8%) zerosZeros
100억미만 건수 has 3 (14.3%) zerosZeros
100억미만 금액 has 3 (14.3%) zerosZeros
200억미만 건수 has 2 (9.5%) zerosZeros
200억미만 금액 has 2 (9.5%) zerosZeros
200억이상 건수 has 3 (14.3%) zerosZeros
200억이상 금액 has 3 (14.3%) zerosZeros
재무제표미등록 건수 has 4 (19.0%) zerosZeros
재무제표미등록 금액 has 4 (19.0%) zerosZeros

Reproduction

Analysis started2024-04-20 21:52:35.228037
Analysis finished2024-04-20 21:53:14.629593
Duration39.4 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

구분
Text

UNIQUE 

Distinct21
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size296.0 B
2024-04-21T06:53:15.130363image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length20
Median length11
Mean length9.047619
Min length3

Characters and Unicode

Total characters190
Distinct characters74
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

Unique21 ?
Unique (%)100.0%

Sample

1st row창업기반지원(일반)
2nd row청년전용창업(일반)
3rd row청년전용창업(창성패)
4th row일자리창출촉진
5th row개발기술사업화
ValueCountFrequency (%)
지원 3
 
10.3%
중소기업 2
 
6.9%
창업기반지원(일반 1
 
3.4%
재창업 1
 
3.4%
무역조정 1
 
3.4%
사업전환(일반 1
 
3.4%
긴급경영안정자금(원전 1
 
3.4%
재해중소기업 1
 
3.4%
일시적경영애로 1
 
3.4%
글로벌기업화 1
 
3.4%
Other values (16) 16
55.2%
2024-04-21T06:53:16.276092image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
15
 
7.9%
10
 
5.3%
8
 
4.2%
) 8
 
4.2%
8
 
4.2%
( 8
 
4.2%
8
 
4.2%
6
 
3.2%
6
 
3.2%
6
 
3.2%
Other values (64) 107
56.3%

Most occurring categories

ValueCountFrequency (%)
Other Letter 158
83.2%
Space Separator 8
 
4.2%
Close Punctuation 8
 
4.2%
Open Punctuation 8
 
4.2%
Lowercase Letter 5
 
2.6%
Uppercase Letter 2
 
1.1%
Dash Punctuation 1
 
0.5%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
15
 
9.5%
10
 
6.3%
8
 
5.1%
8
 
5.1%
6
 
3.8%
6
 
3.8%
6
 
3.8%
6
 
3.8%
5
 
3.2%
4
 
2.5%
Other values (54) 84
53.2%
Lowercase Letter
ValueCountFrequency (%)
e 2
40.0%
o 1
20.0%
t 1
20.0%
r 1
20.0%
Uppercase Letter
ValueCountFrequency (%)
N 1
50.0%
Z 1
50.0%
Space Separator
ValueCountFrequency (%)
8
100.0%
Close Punctuation
ValueCountFrequency (%)
) 8
100.0%
Open Punctuation
ValueCountFrequency (%)
( 8
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 158
83.2%
Common 25
 
13.2%
Latin 7
 
3.7%

Most frequent character per script

Hangul
ValueCountFrequency (%)
15
 
9.5%
10
 
6.3%
8
 
5.1%
8
 
5.1%
6
 
3.8%
6
 
3.8%
6
 
3.8%
6
 
3.8%
5
 
3.2%
4
 
2.5%
Other values (54) 84
53.2%
Latin
ValueCountFrequency (%)
e 2
28.6%
o 1
14.3%
N 1
14.3%
t 1
14.3%
Z 1
14.3%
r 1
14.3%
Common
ValueCountFrequency (%)
8
32.0%
) 8
32.0%
( 8
32.0%
- 1
 
4.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 158
83.2%
ASCII 32
 
16.8%

Most frequent character per block

Hangul
ValueCountFrequency (%)
15
 
9.5%
10
 
6.3%
8
 
5.1%
8
 
5.1%
6
 
3.8%
6
 
3.8%
6
 
3.8%
6
 
3.8%
5
 
3.2%
4
 
2.5%
Other values (54) 84
53.2%
ASCII
ValueCountFrequency (%)
8
25.0%
) 8
25.0%
( 8
25.0%
e 2
 
6.2%
o 1
 
3.1%
N 1
 
3.1%
t 1
 
3.1%
- 1
 
3.1%
Z 1
 
3.1%
r 1
 
3.1%

10억미만 건수
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct20
Distinct (%)95.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean310.42857
Minimum0
Maximum2370
Zeros1
Zeros (%)4.8%
Negative0
Negative (%)0.0%
Memory size317.0 B
2024-04-21T06:53:16.639701image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile3
Q129
median70
Q3340
95-th percentile1191
Maximum2370
Range2370
Interquartile range (IQR)311

Descriptive statistics

Standard deviation551.28501
Coefficient of variation (CV)1.7758836
Kurtosis10.154167
Mean310.42857
Median Absolute Deviation (MAD)67
Skewness3.0314881
Sum6519
Variance303915.16
MonotonicityNot monotonic
2024-04-21T06:53:17.002667image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=20)
ValueCountFrequency (%)
29 2
 
9.5%
2370 1
 
4.8%
347 1
 
4.8%
70 1
 
4.8%
340 1
 
4.8%
10 1
 
4.8%
44 1
 
4.8%
3 1
 
4.8%
38 1
 
4.8%
648 1
 
4.8%
Other values (10) 10
47.6%
ValueCountFrequency (%)
0 1
4.8%
3 1
4.8%
4 1
4.8%
10 1
4.8%
24 1
4.8%
29 2
9.5%
36 1
4.8%
38 1
4.8%
44 1
4.8%
70 1
4.8%
ValueCountFrequency (%)
2370 1
4.8%
1191 1
4.8%
648 1
4.8%
356 1
4.8%
347 1
4.8%
340 1
4.8%
314 1
4.8%
297 1
4.8%
277 1
4.8%
92 1
4.8%

10억미만 금액
Real number (ℝ)

HIGH CORRELATION  UNIQUE  ZEROS 

Distinct21
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean52126.944
Minimum0
Maximum400994
Zeros1
Zeros (%)4.8%
Negative0
Negative (%)0.0%
Memory size317.0 B
2024-04-21T06:53:17.355666image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile450
Q16590
median18128
Q341554
95-th percentile229451
Maximum400994
Range400994
Interquartile range (IQR)34964

Descriptive statistics

Standard deviation95074.479
Coefficient of variation (CV)1.8239028
Kurtosis9.6031094
Mean52126.944
Median Absolute Deviation (MAD)16678
Skewness3.0247071
Sum1094665.8
Variance9.0391565 × 109
MonotonicityNot monotonic
2024-04-21T06:53:17.754306image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=21)
ValueCountFrequency (%)
400994.0 1
 
4.8%
34640.0 1
 
4.8%
6590.0 1
 
4.8%
53660.0 1
 
4.8%
1450.0 1
 
4.8%
8053.0 1
 
4.8%
450.0 1
 
4.8%
4291.0 1
 
4.8%
62786.0 1
 
4.8%
34561.0 1
 
4.8%
Other values (11) 11
52.4%
ValueCountFrequency (%)
0.0 1
4.8%
450.0 1
4.8%
750.0 1
4.8%
1450.0 1
4.8%
4291.0 1
4.8%
6590.0 1
4.8%
8053.0 1
4.8%
8929.0 1
4.8%
9150.0 1
4.8%
11248.81698 1
4.8%
ValueCountFrequency (%)
400994.0 1
4.8%
229451.0 1
4.8%
102823.0 1
4.8%
62786.0 1
4.8%
53660.0 1
4.8%
41554.0 1
4.8%
35290.0 1
4.8%
34640.0 1
4.8%
34561.0 1
4.8%
29867.0 1
4.8%

30억미만 건수
Real number (ℝ)

HIGH CORRELATION  UNIQUE  ZEROS 

Distinct21
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean184.52381
Minimum0
Maximum788
Zeros1
Zeros (%)4.8%
Negative0
Negative (%)0.0%
Memory size317.0 B
2024-04-21T06:53:18.133865image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile4
Q121
median53
Q3339
95-th percentile651
Maximum788
Range788
Interquartile range (IQR)318

Descriptive statistics

Standard deviation243.72497
Coefficient of variation (CV)1.3208321
Kurtosis0.72705488
Mean184.52381
Median Absolute Deviation (MAD)45
Skewness1.3676404
Sum3875
Variance59401.862
MonotonicityNot monotonic
2024-04-21T06:53:18.523457image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=21)
ValueCountFrequency (%)
788 1
 
4.8%
23 1
 
4.8%
65 1
 
4.8%
74 1
 
4.8%
8 1
 
4.8%
92 1
 
4.8%
21 1
 
4.8%
41 1
 
4.8%
651 1
 
4.8%
339 1
 
4.8%
Other values (11) 11
52.4%
ValueCountFrequency (%)
0 1
4.8%
4 1
4.8%
7 1
4.8%
8 1
4.8%
18 1
4.8%
21 1
4.8%
22 1
4.8%
23 1
4.8%
41 1
4.8%
44 1
4.8%
ValueCountFrequency (%)
788 1
4.8%
651 1
4.8%
598 1
4.8%
393 1
4.8%
361 1
4.8%
339 1
4.8%
273 1
4.8%
92 1
4.8%
74 1
4.8%
65 1
4.8%

30억미만 금액
Real number (ℝ)

HIGH CORRELATION  UNIQUE  ZEROS 

Distinct21
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean52576.66
Minimum0
Maximum225871
Zeros1
Zeros (%)4.8%
Negative0
Negative (%)0.0%
Memory size317.0 B
2024-04-21T06:53:18.946192image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile400
Q13650
median18807
Q364221
95-th percentile224854
Maximum225871
Range225871
Interquartile range (IQR)60571

Descriptive statistics

Standard deviation72619.275
Coefficient of variation (CV)1.3812075
Kurtosis1.8836399
Mean52576.66
Median Absolute Deviation (MAD)18407
Skewness1.7222501
Sum1104109.9
Variance5.2735591 × 109
MonotonicityNot monotonic
2024-04-21T06:53:19.301625image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=21)
ValueCountFrequency (%)
224854.0 1
 
4.8%
2420.0 1
 
4.8%
9790.0 1
 
4.8%
20914.0 1
 
4.8%
1800.0 1
 
4.8%
47052.0 1
 
4.8%
3650.0 1
 
4.8%
8304.0 1
 
4.8%
83308.0 1
 
4.8%
57892.0 1
 
4.8%
Other values (11) 11
52.4%
ValueCountFrequency (%)
0.0 1
4.8%
400.0 1
4.8%
1400.0 1
4.8%
1800.0 1
4.8%
2420.0 1
4.8%
3650.0 1
4.8%
8304.0 1
4.8%
9790.0 1
4.8%
9997.86483 1
4.8%
17968.0 1
4.8%
ValueCountFrequency (%)
225871.0 1
4.8%
224854.0 1
4.8%
192343.0 1
4.8%
83308.0 1
4.8%
72648.0 1
4.8%
64221.0 1
4.8%
57892.0 1
4.8%
47052.0 1
4.8%
40470.0 1
4.8%
20914.0 1
4.8%

70억미만 건수
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct20
Distinct (%)95.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean128.52381
Minimum0
Maximum478
Zeros1
Zeros (%)4.8%
Negative0
Negative (%)0.0%
Memory size317.0 B
2024-04-21T06:53:19.646199image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile1
Q118
median46
Q3254
95-th percentile353
Maximum478
Range478
Interquartile range (IQR)236

Descriptive statistics

Standard deviation146.62081
Coefficient of variation (CV)1.1408066
Kurtosis-0.1473211
Mean128.52381
Median Absolute Deviation (MAD)45
Skewness1.0181005
Sum2699
Variance21497.662
MonotonicityNot monotonic
2024-04-21T06:53:20.016998image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=20)
ValueCountFrequency (%)
1 2
 
9.5%
254 1
 
4.8%
200 1
 
4.8%
91 1
 
4.8%
23 1
 
4.8%
11 1
 
4.8%
121 1
 
4.8%
19 1
 
4.8%
34 1
 
4.8%
478 1
 
4.8%
Other values (10) 10
47.6%
ValueCountFrequency (%)
0 1
4.8%
1 2
9.5%
9 1
4.8%
11 1
4.8%
18 1
4.8%
19 1
4.8%
23 1
4.8%
24 1
4.8%
34 1
4.8%
46 1
4.8%
ValueCountFrequency (%)
478 1
4.8%
353 1
4.8%
344 1
4.8%
301 1
4.8%
267 1
4.8%
254 1
4.8%
200 1
4.8%
121 1
4.8%
104 1
4.8%
91 1
4.8%

70억미만 금액
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct20
Distinct (%)95.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean49074.437
Minimum0
Maximum268032
Zeros1
Zeros (%)4.8%
Negative0
Negative (%)0.0%
Memory size317.0 B
2024-04-21T06:53:20.364732image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile100
Q14450
median16857
Q377052
95-th percentile127692
Maximum268032
Range268032
Interquartile range (IQR)72602

Descriptive statistics

Standard deviation64055.521
Coefficient of variation (CV)1.3052727
Kurtosis6.0761534
Mean49074.437
Median Absolute Deviation (MAD)16757
Skewness2.1807134
Sum1030563.2
Variance4.1031098 × 109
MonotonicityNot monotonic
2024-04-21T06:53:20.734881image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=20)
ValueCountFrequency (%)
100.0 2
 
9.5%
88331.0 1
 
4.8%
36160.0 1
 
4.8%
16857.0 1
 
4.8%
5989.0 1
 
4.8%
1850.0 1
 
4.8%
74545.0 1
 
4.8%
4010.0 1
 
4.8%
8140.0 1
 
4.8%
79463.0 1
 
4.8%
Other values (10) 10
47.6%
ValueCountFrequency (%)
0.0 1
4.8%
100.0 2
9.5%
1850.0 1
4.8%
4010.0 1
4.8%
4450.0 1
4.8%
5989.0 1
4.8%
8140.0 1
4.8%
16498.17801 1
4.8%
16598.0 1
4.8%
16857.0 1
4.8%
ValueCountFrequency (%)
268032.0 1
4.8%
127692.0 1
4.8%
101724.0 1
4.8%
88331.0 1
4.8%
79463.0 1
4.8%
77052.0 1
4.8%
74545.0 1
4.8%
73271.0 1
4.8%
36160.0 1
4.8%
29701.0 1
4.8%

100억미만 건수
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct18
Distinct (%)85.7%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean47.190476
Minimum0
Maximum194
Zeros3
Zeros (%)14.3%
Negative0
Negative (%)0.0%
Memory size317.0 B
2024-04-21T06:53:21.082697image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q15
median23
Q372
95-th percentile141
Maximum194
Range194
Interquartile range (IQR)67

Descriptive statistics

Standard deviation56.000553
Coefficient of variation (CV)1.1866918
Kurtosis0.94703726
Mean47.190476
Median Absolute Deviation (MAD)23
Skewness1.3159286
Sum991
Variance3136.0619
MonotonicityNot monotonic
2024-04-21T06:53:21.469400image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=18)
ValueCountFrequency (%)
0 3
 
14.3%
3 2
 
9.5%
30 1
 
4.8%
65 1
 
4.8%
38 1
 
4.8%
50 1
 
4.8%
11 1
 
4.8%
10 1
 
4.8%
141 1
 
4.8%
194 1
 
4.8%
Other values (8) 8
38.1%
ValueCountFrequency (%)
0 3
14.3%
3 2
9.5%
5 1
 
4.8%
7 1
 
4.8%
10 1
 
4.8%
11 1
 
4.8%
15 1
 
4.8%
23 1
 
4.8%
30 1
 
4.8%
38 1
 
4.8%
ValueCountFrequency (%)
194 1
4.8%
141 1
4.8%
128 1
4.8%
121 1
4.8%
75 1
4.8%
72 1
4.8%
65 1
4.8%
50 1
4.8%
38 1
4.8%
30 1
4.8%

100억미만 금액
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct19
Distinct (%)90.5%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean22056.297
Minimum0
Maximum98968
Zeros3
Zeros (%)14.3%
Negative0
Negative (%)0.0%
Memory size317.0 B
2024-04-21T06:53:21.850878image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q12600
median11895
Q333003
95-th percentile94744
Maximum98968
Range98968
Interquartile range (IQR)30403

Descriptive statistics

Standard deviation28807.846
Coefficient of variation (CV)1.3061052
Kurtosis2.8797176
Mean22056.297
Median Absolute Deviation (MAD)11095
Skewness1.830179
Sum463182.25
Variance8.2989196 × 108
MonotonicityNot monotonic
2024-04-21T06:53:22.221494image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=19)
ValueCountFrequency (%)
0.0 3
 
14.3%
15019.0 1
 
4.8%
10985.0 1
 
4.8%
800.0 1
 
4.8%
2600.0 1
 
4.8%
40840.0 1
 
4.8%
3060.0 1
 
4.8%
5100.0 1
 
4.8%
26316.0 1
 
4.8%
48972.0 1
 
4.8%
Other values (9) 9
42.9%
ValueCountFrequency (%)
0.0 3
14.3%
800.0 1
 
4.8%
1720.0 1
 
4.8%
2600.0 1
 
4.8%
3060.0 1
 
4.8%
5100.0 1
 
4.8%
6355.245886 1
 
4.8%
10985.0 1
 
4.8%
11895.0 1
 
4.8%
13751.0 1
 
4.8%
ValueCountFrequency (%)
98968.0 1
4.8%
94744.0 1
4.8%
48972.0 1
4.8%
40840.0 1
4.8%
35224.0 1
4.8%
33003.0 1
4.8%
26316.0 1
4.8%
15019.0 1
4.8%
13830.0 1
4.8%
13751.0 1
4.8%

200억미만 건수
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct17
Distinct (%)81.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean46.714286
Minimum0
Maximum242
Zeros2
Zeros (%)9.5%
Negative0
Negative (%)0.0%
Memory size317.0 B
2024-04-21T06:53:22.569896image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q18
median24
Q357
95-th percentile117
Maximum242
Range242
Interquartile range (IQR)49

Descriptive statistics

Standard deviation58.912768
Coefficient of variation (CV)1.2611296
Kurtosis5.1217904
Mean46.714286
Median Absolute Deviation (MAD)21
Skewness2.0745232
Sum981
Variance3470.7143
MonotonicityNot monotonic
2024-04-21T06:53:22.934521image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=17)
ValueCountFrequency (%)
24 2
 
9.5%
57 2
 
9.5%
8 2
 
9.5%
0 2
 
9.5%
46 1
 
4.8%
3 1
 
4.8%
4 1
 
4.8%
9 1
 
4.8%
115 1
 
4.8%
242 1
 
4.8%
Other values (7) 7
33.3%
ValueCountFrequency (%)
0 2
9.5%
3 1
4.8%
4 1
4.8%
6 1
4.8%
8 2
9.5%
9 1
4.8%
17 1
4.8%
24 2
9.5%
26 1
4.8%
29 1
4.8%
ValueCountFrequency (%)
242 1
4.8%
117 1
4.8%
115 1
4.8%
100 1
4.8%
89 1
4.8%
57 2
9.5%
46 1
4.8%
29 1
4.8%
26 1
4.8%
24 2
9.5%

200억미만 금액
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct20
Distinct (%)95.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean25855.413
Minimum0
Maximum152559
Zeros2
Zeros (%)9.5%
Negative0
Negative (%)0.0%
Memory size317.0 B
2024-04-21T06:53:23.280153image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q14834.5347
median12597
Q326100
95-th percentile74209
Maximum152559
Range152559
Interquartile range (IQR)21265.465

Descriptive statistics

Standard deviation36481.011
Coefficient of variation (CV)1.4109622
Kurtosis6.8181546
Mean25855.413
Median Absolute Deviation (MAD)8497
Skewness2.4586702
Sum542963.68
Variance1.3308641 × 109
MonotonicityNot monotonic
2024-04-21T06:53:23.668921image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=20)
ValueCountFrequency (%)
0.0 2
 
9.5%
10025.0 1
 
4.8%
13410.0 1
 
4.8%
17158.0 1
 
4.8%
800.0 1
 
4.8%
1300.0 1
 
4.8%
53641.0 1
 
4.8%
4100.0 1
 
4.8%
12597.0 1
 
4.8%
26100.0 1
 
4.8%
Other values (10) 10
47.6%
ValueCountFrequency (%)
0.0 2
9.5%
800.0 1
4.8%
1300.0 1
4.8%
4100.0 1
4.8%
4834.534661 1
4.8%
8600.146908 1
4.8%
8740.0 1
4.8%
10025.0 1
4.8%
11481.0 1
4.8%
12597.0 1
4.8%
ValueCountFrequency (%)
152559.0 1
4.8%
74209.0 1
4.8%
72022.0 1
4.8%
53641.0 1
4.8%
39027.0 1
4.8%
26100.0 1
4.8%
19651.0 1
4.8%
17158.0 1
4.8%
13410.0 1
4.8%
12709.0 1
4.8%

200억이상 건수
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct15
Distinct (%)71.4%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean28.380952
Minimum0
Maximum166
Zeros3
Zeros (%)14.3%
Negative0
Negative (%)0.0%
Memory size317.0 B
2024-04-21T06:53:24.025197image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q13
median15
Q342
95-th percentile83
Maximum166
Range166
Interquartile range (IQR)39

Descriptive statistics

Standard deviation39.441699
Coefficient of variation (CV)1.3897243
Kurtosis6.9282582
Mean28.380952
Median Absolute Deviation (MAD)12
Skewness2.4216933
Sum596
Variance1555.6476
MonotonicityNot monotonic
2024-04-21T06:53:24.376336image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=15)
ValueCountFrequency (%)
0 3
14.3%
3 3
14.3%
15 2
 
9.5%
17 2
 
9.5%
9 1
 
4.8%
7 1
 
4.8%
50 1
 
4.8%
4 1
 
4.8%
83 1
 
4.8%
57 1
 
4.8%
Other values (5) 5
23.8%
ValueCountFrequency (%)
0 3
14.3%
3 3
14.3%
4 1
 
4.8%
7 1
 
4.8%
9 1
 
4.8%
15 2
9.5%
17 2
9.5%
18 1
 
4.8%
24 1
 
4.8%
42 1
 
4.8%
ValueCountFrequency (%)
166 1
4.8%
83 1
4.8%
63 1
4.8%
57 1
4.8%
50 1
4.8%
42 1
4.8%
24 1
4.8%
18 1
4.8%
17 2
9.5%
15 2
9.5%

200억이상 금액
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct19
Distinct (%)90.5%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean22447.165
Minimum0
Maximum116167
Zeros3
Zeros (%)14.3%
Negative0
Negative (%)0.0%
Memory size317.0 B
2024-04-21T06:53:24.722365image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q12300
median9990
Q323359
95-th percentile77344
Maximum116167
Range116167
Interquartile range (IQR)21059

Descriptive statistics

Standard deviation31345.551
Coefficient of variation (CV)1.3964147
Kurtosis3.1408923
Mean22447.165
Median Absolute Deviation (MAD)8990
Skewness1.9034355
Sum471390.47
Variance9.8254359 × 108
MonotonicityNot monotonic
2024-04-21T06:53:25.088920image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=19)
ValueCountFrequency (%)
0.0 3
 
14.3%
9990.0 1
 
4.8%
7720.0 1
 
4.8%
1000.0 1
 
4.8%
13869.0 1
 
4.8%
6480.0 1
 
4.8%
1050.0 1
 
4.8%
13450.0 1
 
4.8%
77344.0 1
 
4.8%
4640.0 1
 
4.8%
Other values (9) 9
42.9%
ValueCountFrequency (%)
0.0 3
14.3%
1000.0 1
 
4.8%
1050.0 1
 
4.8%
2300.0 1
 
4.8%
4640.0 1
 
4.8%
5000.0 1
 
4.8%
6480.0 1
 
4.8%
7720.0 1
 
4.8%
9990.0 1
 
4.8%
13450.0 1
 
4.8%
ValueCountFrequency (%)
116167.0 1
4.8%
77344.0 1
4.8%
71882.0 1
4.8%
55165.46534 1
4.8%
27820.0 1
4.8%
23359.0 1
4.8%
19697.0 1
4.8%
14457.0 1
4.8%
13869.0 1
4.8%
13450.0 1
4.8%

재무제표미등록 건수
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct18
Distinct (%)85.7%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean196.04762
Minimum0
Maximum1570
Zeros4
Zeros (%)19.0%
Negative0
Negative (%)0.0%
Memory size317.0 B
2024-04-21T06:53:25.649469image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q12
median16
Q362
95-th percentile1440
Maximum1570
Range1570
Interquartile range (IQR)60

Descriptive statistics

Standard deviation447.86008
Coefficient of variation (CV)2.2844454
Kurtosis6.5297416
Mean196.04762
Median Absolute Deviation (MAD)16
Skewness2.7316889
Sum4117
Variance200578.65
MonotonicityNot monotonic
2024-04-21T06:53:26.034824image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=18)
ValueCountFrequency (%)
0 4
19.0%
1570 1
 
4.8%
7 1
 
4.8%
2 1
 
4.8%
158 1
 
4.8%
1 1
 
4.8%
16 1
 
4.8%
42 1
 
4.8%
58 1
 
4.8%
62 1
 
4.8%
Other values (8) 8
38.1%
ValueCountFrequency (%)
0 4
19.0%
1 1
 
4.8%
2 1
 
4.8%
3 1
 
4.8%
5 1
 
4.8%
7 1
 
4.8%
8 1
 
4.8%
16 1
 
4.8%
37 1
 
4.8%
42 1
 
4.8%
ValueCountFrequency (%)
1570 1
4.8%
1440 1
4.8%
446 1
4.8%
206 1
4.8%
158 1
4.8%
62 1
4.8%
58 1
4.8%
56 1
4.8%
42 1
4.8%
37 1
4.8%

재무제표미등록 금액
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct18
Distinct (%)85.7%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean34910.702
Minimum0
Maximum340787
Zeros4
Zeros (%)19.0%
Negative0
Negative (%)0.0%
Memory size317.0 B
2024-04-21T06:53:26.398305image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q11600
median6200
Q317837
95-th percentile142840
Maximum340787
Range340787
Interquartile range (IQR)16237

Descriptive statistics

Standard deviation79606.93
Coefficient of variation (CV)2.2803016
Kurtosis11.540358
Mean34910.702
Median Absolute Deviation (MAD)6200
Skewness3.2805877
Sum733124.75
Variance6.3372633 × 109
MonotonicityNot monotonic
2024-04-21T06:53:26.781660image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=18)
ValueCountFrequency (%)
0.0 4
19.0%
340787.0 1
 
4.8%
8435.0 1
 
4.8%
900.0 1
 
4.8%
17837.0 1
 
4.8%
2000.0 1
 
4.8%
3615.0 1
 
4.8%
3730.0 1
 
4.8%
9970.0 1
 
4.8%
6200.0 1
 
4.8%
Other values (8) 8
38.1%
ValueCountFrequency (%)
0.0 4
19.0%
900.0 1
 
4.8%
1600.0 1
 
4.8%
2000.0 1
 
4.8%
2299.747768 1
 
4.8%
3615.0 1
 
4.8%
3730.0 1
 
4.8%
6200.0 1
 
4.8%
8435.0 1
 
4.8%
9970.0 1
 
4.8%
ValueCountFrequency (%)
340787.0 1
4.8%
142840.0 1
4.8%
116313.0 1
4.8%
31042.0 1
4.8%
20350.0 1
4.8%
17837.0 1
4.8%
14750.0 1
4.8%
10456.0 1
4.8%
9970.0 1
4.8%
8435.0 1
4.8%

Interactions

2024-04-21T06:53:10.071672image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T06:52:35.914043image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T06:52:39.275345image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T06:52:42.578498image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T06:52:44.889014image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T06:52:47.105268image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T06:52:49.729980image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T06:52:53.245280image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T06:52:56.733133image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T06:52:58.763815image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T06:53:00.814472image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T06:53:03.225369image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T06:53:05.341018image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T06:53:07.526772image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T06:53:10.314418image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T06:52:36.134933image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T06:52:39.515619image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T06:52:42.723014image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T06:52:45.015339image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T06:52:47.233879image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T06:52:49.959563image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T06:52:53.494119image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T06:52:56.862336image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T06:52:58.895199image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T06:53:00.957638image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T06:53:03.367506image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T06:53:05.476958image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T06:53:07.669515image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T06:53:10.782421image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T06:52:36.387726image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T06:52:39.781929image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T06:52:42.896185image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T06:52:45.165904image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T06:52:47.393085image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T06:52:50.218550image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T06:52:53.765602image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T06:52:57.021250image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T06:52:59.051462image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T06:53:01.124246image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T06:53:03.529978image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T06:53:05.641499image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T06:53:07.837796image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T06:53:11.050086image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T06:52:36.640179image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T06:52:40.049284image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T06:52:43.072195image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T06:52:45.521544image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T06:52:47.546023image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T06:52:50.475021image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T06:52:54.030630image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T06:52:57.178428image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T06:52:59.206669image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T06:53:01.296149image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T06:53:03.693504image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T06:53:05.806640image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T06:53:08.003653image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T06:53:11.288199image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T06:52:36.868514image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T06:52:40.288304image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T06:52:43.218394image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T06:52:45.645153image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T06:52:47.679069image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T06:52:50.708109image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T06:52:54.270270image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T06:52:57.309340image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T06:52:59.334695image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T06:53:01.436697image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T06:53:03.826877image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T06:53:05.951458image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T06:53:08.144240image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T06:53:11.452433image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T06:52:37.100478image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T06:52:40.539266image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T06:52:43.374949image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T06:52:45.780929image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T06:52:47.813764image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T06:52:50.946412image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T06:52:54.516561image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T06:52:57.448198image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T06:52:59.472619image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T06:53:01.589379image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T06:53:03.970736image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T06:53:06.092875image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T06:53:08.294892image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T06:53:11.599805image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T06:52:37.333408image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T06:52:40.785547image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T06:52:43.530287image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T06:52:45.912434image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T06:52:47.951585image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T06:52:51.187783image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T06:52:54.763279image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T06:52:57.583993image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T06:52:59.609365image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T06:53:01.740863image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T06:53:04.108833image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T06:53:06.243916image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T06:53:08.444798image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T06:53:11.849539image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T06:52:37.583068image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T06:52:41.055267image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T06:52:43.704081image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T06:52:46.067485image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T06:52:48.104686image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T06:52:51.444460image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T06:52:55.027192image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T06:52:57.742401image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T06:52:59.763409image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T06:53:01.908890image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T06:53:04.270125image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T06:53:06.408313image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T06:53:08.610886image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T06:53:12.100439image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T06:52:37.817548image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T06:52:41.304237image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T06:52:43.857181image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T06:52:46.203040image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T06:52:48.244861image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T06:52:51.685367image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T06:52:55.272006image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T06:52:57.876688image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T06:52:59.898977image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T06:53:02.058220image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T06:53:04.417391image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T06:53:06.547121image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T06:53:08.759837image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T06:53:12.347862image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T06:52:38.047921image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T06:52:41.554752image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T06:52:44.013274image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T06:52:46.337256image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T06:52:48.438532image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T06:52:51.925720image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T06:52:55.726193image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T06:52:58.015841image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T06:53:00.036999image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T06:53:02.206966image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T06:53:04.558943image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T06:53:06.720323image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T06:53:08.906847image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T06:53:12.617018image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T06:52:38.301430image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T06:52:41.826265image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T06:52:44.187591image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T06:52:46.493199image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T06:52:48.706083image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T06:52:52.202042image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T06:52:55.996683image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T06:52:58.170493image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T06:53:00.196741image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T06:53:02.371430image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T06:53:04.724217image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T06:53:06.917429image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T06:53:09.079068image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T06:53:12.869661image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T06:52:38.537736image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T06:52:42.082526image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T06:52:44.349458image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T06:52:46.648037image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T06:52:48.960809image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T06:52:52.456067image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T06:52:56.216418image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T06:52:58.314614image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T06:53:00.351313image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T06:53:02.524672image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T06:53:04.869547image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T06:53:07.066674image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T06:53:09.282635image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T06:53:13.125772image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T06:52:38.777712image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T06:52:42.242171image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T06:52:44.520784image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T06:52:46.791760image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T06:52:49.215271image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T06:52:52.712664image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T06:52:56.405812image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T06:52:58.455446image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T06:53:00.499027image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T06:53:02.679945image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T06:53:05.019266image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T06:53:07.211807image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T06:53:09.543280image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T06:53:13.391112image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T06:52:39.027629image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T06:52:42.411274image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T06:52:44.725127image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T06:52:46.944973image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T06:52:49.476932image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T06:52:52.983666image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T06:52:56.571216image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T06:52:58.613118image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T06:53:00.662525image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T06:53:02.851486image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T06:53:05.182039image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T06:53:07.373664image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T06:53:09.806963image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-04-21T06:53:27.065086image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
구분10억미만 건수10억미만 금액30억미만 건수30억미만 금액70억미만 건수70억미만 금액100억미만 건수100억미만 금액200억미만 건수200억미만 금액200억이상 건수200억이상 금액재무제표미등록 건수재무제표미등록 금액
구분1.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.000
10억미만 건수1.0001.0000.9710.9420.7730.8190.5570.7110.6490.0500.0000.4890.0000.7040.829
10억미만 금액1.0000.9711.0000.8370.8380.7080.7700.5320.5980.6360.0000.0000.0000.7080.809
30억미만 건수1.0000.9420.8371.0000.9030.9120.7580.9660.7830.7000.6930.6570.2930.7010.827
30억미만 금액1.0000.7730.8380.9031.0000.9160.9480.7430.9200.9190.7540.6700.5140.6710.750
70억미만 건수1.0000.8190.7080.9120.9161.0000.8470.8580.8370.8130.8950.7720.6890.0000.309
70억미만 금액1.0000.5570.7700.7580.9480.8471.0000.6290.9180.8980.8790.5400.8700.3550.540
100억미만 건수1.0000.7110.5320.9660.7430.8580.6291.0000.8730.8560.8540.8640.5630.0000.000
100억미만 금액1.0000.6490.5980.7830.9200.8370.9180.8731.0000.8980.9130.9410.7980.0000.000
200억미만 건수1.0000.0500.6360.7000.9190.8130.8980.8560.8981.0000.9290.9490.7970.0000.000
200억미만 금액1.0000.0000.0000.6930.7540.8950.8790.8540.9130.9291.0000.8780.9480.0000.000
200억이상 건수1.0000.4890.0000.6570.6700.7720.5400.8640.9410.9490.8781.0000.9120.0000.000
200억이상 금액1.0000.0000.0000.2930.5140.6890.8700.5630.7980.7970.9480.9121.0000.0000.000
재무제표미등록 건수1.0000.7040.7080.7010.6710.0000.3550.0000.0000.0000.0000.0000.0001.0000.974
재무제표미등록 금액1.0000.8290.8090.8270.7500.3090.5400.0000.0000.0000.0000.0000.0000.9741.000
2024-04-21T06:53:27.446379image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
10억미만 건수10억미만 금액30억미만 건수30억미만 금액70억미만 건수70억미만 금액100억미만 건수100억미만 금액200억미만 건수200억미만 금액200억이상 건수200억이상 금액재무제표미등록 건수재무제표미등록 금액
10억미만 건수1.0000.8800.8000.6480.5890.4890.4250.3280.2930.166-0.081-0.0830.8840.777
10억미만 금액0.8801.0000.8180.8290.6630.6800.5330.5210.3770.2890.0740.1760.8310.852
30억미만 건수0.8000.8181.0000.9310.9240.8430.8160.7560.7200.6200.3600.3730.5620.549
30억미만 금액0.6480.8290.9311.0000.9110.9450.8430.8750.7430.6940.4350.5380.4790.573
70억미만 건수0.5890.6630.9240.9111.0000.9040.9620.8950.9010.8180.5690.5620.3550.358
70억미만 금액0.4890.6800.8430.9450.9041.0000.8920.9500.8200.8260.5300.6390.3230.450
100억미만 건수0.4250.5330.8160.8430.9620.8921.0000.9300.9590.8920.6820.6730.2040.233
100억미만 금액0.3280.5210.7560.8750.8950.9500.9301.0000.9040.9140.6590.7380.1620.301
200억미만 건수0.2930.3770.7200.7430.9010.8200.9590.9041.0000.9500.8060.7470.0800.109
200억미만 금액0.1660.2890.6200.6940.8180.8260.8920.9140.9501.0000.7870.786-0.0270.073
200억이상 건수-0.0810.0740.3600.4350.5690.5300.6820.6590.8060.7871.0000.909-0.215-0.132
200억이상 금액-0.0830.1760.3730.5380.5620.6390.6730.7380.7470.7860.9091.000-0.1390.042
재무제표미등록 건수0.8840.8310.5620.4790.3550.3230.2040.1620.080-0.027-0.215-0.1391.0000.922
재무제표미등록 금액0.7770.8520.5490.5730.3580.4500.2330.3010.1090.073-0.1320.0420.9221.000

Missing values

2024-04-21T06:53:13.775416image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-04-21T06:53:14.380537image/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

구분10억미만 건수10억미만 금액30억미만 건수30억미만 금액70억미만 건수70억미만 금액100억미만 건수100억미만 금액200억미만 건수200억미만 금액200억이상 건수200억이상 금액재무제표미등록 건수재무제표미등록 금액
0창업기반지원(일반)2370400994.0788224854.025488331.03015019.02410025.099990.01570340787.0
1청년전용창업(일반)35634640.0232420.01100.000.000.000.01440142840.0
2청년전용창업(창성패)929150.04400.01100.000.000.000.020620350.0
3일자리창출촉진1191229451.0598192343.0267101724.07533003.02912709.0714457.0446116313.0
4개발기술사업화31441554.036172648.030173271.012835224.011739027.05027820.05610456.0
5성장공유형(일반)2911248.81698189997.864831816498.1780176355.24588688600.14690845000.052299.747768
6스케일업금융00.000.000.000.084834.5346618355165.4653400.0
7혁신성장지원(일반)297102823.0393225871.0344268032.012198968.08972022.05771882.03731042.0
8협동화368929.04417968.04616598.02311895.02619651.02423359.031600.0
9제조현장스마트화2929867.05364221.0104127692.07294744.0100152559.063116167.0814750.0
구분10억미만 건수10억미만 금액30억미만 건수30억미만 금액70억미만 건수70억미만 금액100억미만 건수100억미만 금액200억미만 건수200억미만 금액200억이상 건수200억이상 금액재무제표미등록 건수재무제표미등록 금액
11혁신성장지원(원전 중소기업 지원)4750.071400.094450.051720.068740.032300.000.0
12내수기업 수출기업화34735290.027340470.020036160.06513830.05713410.0174640.0626200.0
13수출기업 글로벌기업화27734561.033957892.035377052.019448972.024274209.016677344.0589970.0
14일시적경영애로64862786.065183308.047879463.014126316.011526100.04213450.0423730.0
15재해중소기업384291.0418304.0348140.0105100.02412597.031050.0163615.0
16긴급경영안정자금(원전 중소기업 지원)3450.0213650.0194010.0113060.094100.0156480.000.0
17사업전환(일반)448053.09247052.012174545.05040840.05753641.01713869.012000.0
18무역조정101450.081800.0111850.032600.041300.031000.000.0
19재창업34053660.07420914.0235989.03800.03800.000.015817837.0
20구조개선전용706590.0659790.09116857.03810985.04617158.0187720.02900.0