Overview

Dataset statistics

Number of variables10
Number of observations500
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory41.1 KiB
Average record size in memory84.3 B

Variable types

Text2
Numeric4
Boolean1
DateTime3

Dataset

Description해당 파일 데이터는 신용보증기금의 보증고객 창업기업 중단폐지에 대해 확인하실 수 있는 자료이니 데이터 활용에 참고하여 주시기 바랍니다.
Author신용보증기금
URLhttps://www.data.go.kr/data/15093235/fileData.do

Alerts

중단사유발생여부 has constant value ""Constant
프로그램중단일자 has constant value ""Constant
유효개시일자 has constant value ""Constant
유효종료일자 has constant value ""Constant

Reproduction

Analysis started2023-12-12 02:10:55.138158
Analysis finished2023-12-12 02:10:57.657237
Duration2.52 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

기업고객ID
Text

Distinct361
Distinct (%)72.2%
Missing0
Missing (%)0.0%
Memory size4.0 KiB
2023-12-12T11:10:57.900016image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length10
Median length10
Mean length10
Min length10

Characters and Unicode

Total characters5000
Distinct characters62
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique273 ?
Unique (%)54.6%

Sample

1st row9bsBkYGgH6
2nd row9bsBkYGgH6
3rd row9bv3YIys6C
4th row9bp1BBjC7z
5th row9bth6yOZSq
ValueCountFrequency (%)
9a9yuepxmy 7
 
1.4%
9bqdw0rlpg 6
 
1.2%
9bmdlhzmpk 6
 
1.2%
9bfuh3uiue 5
 
1.0%
9bujcec2mr 5
 
1.0%
9bfckrnjdb 5
 
1.0%
9bq1jyi1l7 4
 
0.8%
9btjaylayf 4
 
0.8%
9br5lowlbh 4
 
0.8%
9bv8y2kcng 4
 
0.8%
Other values (351) 450
90.0%
2023-12-12T11:10:58.381518image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
9 557
 
11.1%
b 539
 
10.8%
a 138
 
2.8%
p 123
 
2.5%
q 115
 
2.3%
u 103
 
2.1%
n 99
 
2.0%
o 95
 
1.9%
r 92
 
1.8%
s 83
 
1.7%
Other values (52) 3056
61.1%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 2510
50.2%
Uppercase Letter 1477
29.5%
Decimal Number 1013
20.3%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
b 539
21.5%
a 138
 
5.5%
p 123
 
4.9%
q 115
 
4.6%
u 103
 
4.1%
n 99
 
3.9%
o 95
 
3.8%
r 92
 
3.7%
s 83
 
3.3%
m 79
 
3.1%
Other values (16) 1044
41.6%
Uppercase Letter
ValueCountFrequency (%)
R 76
 
5.1%
H 73
 
4.9%
E 72
 
4.9%
J 71
 
4.8%
X 70
 
4.7%
K 69
 
4.7%
L 67
 
4.5%
U 61
 
4.1%
N 59
 
4.0%
W 58
 
3.9%
Other values (16) 801
54.2%
Decimal Number
ValueCountFrequency (%)
9 557
55.0%
3 64
 
6.3%
2 60
 
5.9%
6 59
 
5.8%
7 56
 
5.5%
8 51
 
5.0%
5 47
 
4.6%
1 46
 
4.5%
4 37
 
3.7%
0 36
 
3.6%

Most occurring scripts

ValueCountFrequency (%)
Latin 3987
79.7%
Common 1013
 
20.3%

Most frequent character per script

Latin
ValueCountFrequency (%)
b 539
 
13.5%
a 138
 
3.5%
p 123
 
3.1%
q 115
 
2.9%
u 103
 
2.6%
n 99
 
2.5%
o 95
 
2.4%
r 92
 
2.3%
s 83
 
2.1%
m 79
 
2.0%
Other values (42) 2521
63.2%
Common
ValueCountFrequency (%)
9 557
55.0%
3 64
 
6.3%
2 60
 
5.9%
6 59
 
5.8%
7 56
 
5.5%
8 51
 
5.0%
5 47
 
4.6%
1 46
 
4.5%
4 37
 
3.7%
0 36
 
3.6%

Most occurring blocks

ValueCountFrequency (%)
ASCII 5000
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
9 557
 
11.1%
b 539
 
10.8%
a 138
 
2.8%
p 123
 
2.5%
q 115
 
2.3%
u 103
 
2.1%
n 99
 
2.0%
o 95
 
1.9%
r 92
 
1.8%
s 83
 
1.7%
Other values (52) 3056
61.1%

창업기업프로그램중단사유코드
Real number (ℝ)

Distinct9
Distinct (%)1.8%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean7.11
Minimum1
Maximum10
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size4.5 KiB
2023-12-12T11:10:58.521449image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q14
median9
Q310
95-th percentile10
Maximum10
Range9
Interquartile range (IQR)6

Descriptive statistics

Standard deviation3.194732
Coefficient of variation (CV)0.4493294
Kurtosis-0.9711659
Mean7.11
Median Absolute Deviation (MAD)1
Skewness-0.71977532
Sum3555
Variance10.206313
MonotonicityNot monotonic
2023-12-12T11:10:58.657446image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=9)
ValueCountFrequency (%)
10 179
35.8%
9 91
18.2%
4 62
 
12.4%
1 51
 
10.2%
5 47
 
9.4%
8 32
 
6.4%
2 20
 
4.0%
6 10
 
2.0%
7 8
 
1.6%
ValueCountFrequency (%)
1 51
 
10.2%
2 20
 
4.0%
4 62
 
12.4%
5 47
 
9.4%
6 10
 
2.0%
7 8
 
1.6%
8 32
 
6.4%
9 91
18.2%
10 179
35.8%
ValueCountFrequency (%)
10 179
35.8%
9 91
18.2%
8 32
 
6.4%
7 8
 
1.6%
6 10
 
2.0%
5 47
 
9.4%
4 62
 
12.4%
2 20
 
4.0%
1 51
 
10.2%

이력일련번호
Real number (ℝ)

Distinct12
Distinct (%)2.4%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1.638
Minimum1
Maximum12
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size4.5 KiB
2023-12-12T11:10:58.795062image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q11
median1
Q31
95-th percentile5
Maximum12
Range11
Interquartile range (IQR)0

Descriptive statistics

Standard deviation1.5084784
Coefficient of variation (CV)0.92092697
Kurtosis12.421956
Mean1.638
Median Absolute Deviation (MAD)0
Skewness3.205083
Sum819
Variance2.275507
MonotonicityNot monotonic
2023-12-12T11:10:58.965390image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=12)
ValueCountFrequency (%)
1 388
77.6%
3 51
 
10.2%
2 22
 
4.4%
5 18
 
3.6%
7 6
 
1.2%
4 5
 
1.0%
6 4
 
0.8%
8 2
 
0.4%
11 1
 
0.2%
9 1
 
0.2%
Other values (2) 2
 
0.4%
ValueCountFrequency (%)
1 388
77.6%
2 22
 
4.4%
3 51
 
10.2%
4 5
 
1.0%
5 18
 
3.6%
6 4
 
0.8%
7 6
 
1.2%
8 2
 
0.4%
9 1
 
0.2%
10 1
 
0.2%
ValueCountFrequency (%)
12 1
 
0.2%
11 1
 
0.2%
10 1
 
0.2%
9 1
 
0.2%
8 2
 
0.4%
7 6
 
1.2%
6 4
 
0.8%
5 18
 
3.6%
4 5
 
1.0%
3 51
10.2%

중단사유발생여부
Boolean

CONSTANT 

Distinct1
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size632.0 B
True
500 
ValueCountFrequency (%)
True 500
100.0%
2023-12-12T11:10:59.083381image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

프로그램중단일자
Date

CONSTANT 

Distinct1
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size4.0 KiB
Minimum2023-12-12 00:00:00
Maximum2023-12-12 00:00:00
2023-12-12T11:10:59.182737image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T11:10:59.306930image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=1)

유효개시일자
Date

CONSTANT 

Distinct1
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size4.0 KiB
Minimum2023-12-12 00:00:00
Maximum2023-12-12 00:00:00
2023-12-12T11:10:59.412431image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T11:10:59.557124image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=1)

유효종료일자
Date

CONSTANT 

Distinct1
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size4.0 KiB
Minimum2023-12-12 00:00:00
Maximum2023-12-12 00:00:00
2023-12-12T11:10:59.678826image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T11:10:59.802989image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=1)

최종수정수
Real number (ℝ)

Distinct12
Distinct (%)2.4%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1.876
Minimum1
Maximum13
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size4.5 KiB
2023-12-12T11:10:59.969536image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q11
median1
Q32
95-th percentile5
Maximum13
Range12
Interquartile range (IQR)1

Descriptive statistics

Standard deviation1.6253947
Coefficient of variation (CV)0.86641507
Kurtosis10.915276
Mean1.876
Median Absolute Deviation (MAD)0
Skewness2.9169466
Sum938
Variance2.6419078
MonotonicityNot monotonic
2023-12-12T11:11:00.126599image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=12)
ValueCountFrequency (%)
1 306
61.2%
2 102
 
20.4%
3 32
 
6.4%
4 26
 
5.2%
6 11
 
2.2%
5 10
 
2.0%
7 6
 
1.2%
11 2
 
0.4%
8 2
 
0.4%
10 1
 
0.2%
Other values (2) 2
 
0.4%
ValueCountFrequency (%)
1 306
61.2%
2 102
 
20.4%
3 32
 
6.4%
4 26
 
5.2%
5 10
 
2.0%
6 11
 
2.2%
7 6
 
1.2%
8 2
 
0.4%
9 1
 
0.2%
10 1
 
0.2%
ValueCountFrequency (%)
13 1
 
0.2%
11 2
 
0.4%
10 1
 
0.2%
9 1
 
0.2%
8 2
 
0.4%
7 6
 
1.2%
6 11
 
2.2%
5 10
 
2.0%
4 26
5.2%
3 32
6.4%

처리시각
Text

Distinct473
Distinct (%)94.6%
Missing0
Missing (%)0.0%
Memory size4.0 KiB
2023-12-12T11:11:00.596301image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length7
Median length7
Mean length7
Min length7

Characters and Unicode

Total characters3500
Distinct characters12
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

Unique447 ?
Unique (%)89.4%

Sample

1st row03:10.8
2nd row06:34.1
3rd row04:00.0
4th row34:08.3
5th row19:51.1
ValueCountFrequency (%)
27:57.1 3
 
0.6%
31:36.9 2
 
0.4%
52:16.3 2
 
0.4%
21:20.5 2
 
0.4%
22:36.8 2
 
0.4%
39:51.1 2
 
0.4%
03:51.6 2
 
0.4%
15:20.8 2
 
0.4%
51:46.2 2
 
0.4%
56:23.1 2
 
0.4%
Other values (463) 479
95.8%
2023-12-12T11:11:01.196772image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
: 500
14.3%
. 500
14.3%
2 342
9.8%
1 327
9.3%
3 323
9.2%
5 322
9.2%
0 320
9.1%
4 287
8.2%
9 156
 
4.5%
6 149
 
4.3%
Other values (2) 274
7.8%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 2500
71.4%
Other Punctuation 1000
 
28.6%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
2 342
13.7%
1 327
13.1%
3 323
12.9%
5 322
12.9%
0 320
12.8%
4 287
11.5%
9 156
6.2%
6 149
6.0%
7 142
5.7%
8 132
 
5.3%
Other Punctuation
ValueCountFrequency (%)
: 500
50.0%
. 500
50.0%

Most occurring scripts

ValueCountFrequency (%)
Common 3500
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
: 500
14.3%
. 500
14.3%
2 342
9.8%
1 327
9.3%
3 323
9.2%
5 322
9.2%
0 320
9.1%
4 287
8.2%
9 156
 
4.5%
6 149
 
4.3%
Other values (2) 274
7.8%

Most occurring blocks

ValueCountFrequency (%)
ASCII 3500
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
: 500
14.3%
. 500
14.3%
2 342
9.8%
1 327
9.3%
3 323
9.2%
5 322
9.2%
0 320
9.1%
4 287
8.2%
9 156
 
4.5%
6 149
 
4.3%
Other values (2) 274
7.8%

처리직원번호
Real number (ℝ)

Distinct256
Distinct (%)51.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean3775.502
Minimum1782
Maximum4795
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size4.5 KiB
2023-12-12T11:11:01.391071image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1782
5-th percentile2637.45
Q13360
median3864
Q34333.75
95-th percentile4691
Maximum4795
Range3013
Interquartile range (IQR)973.75

Descriptive statistics

Standard deviation661.56406
Coefficient of variation (CV)0.17522546
Kurtosis-0.15303472
Mean3775.502
Median Absolute Deviation (MAD)482
Skewness-0.55042573
Sum1887751
Variance437667
MonotonicityNot monotonic
2023-12-12T11:11:01.609498image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
3465 9
 
1.8%
4212 9
 
1.8%
3555 9
 
1.8%
3871 7
 
1.4%
4285 7
 
1.4%
2905 6
 
1.2%
4040 6
 
1.2%
3244 6
 
1.2%
3514 6
 
1.2%
4691 6
 
1.2%
Other values (246) 429
85.8%
ValueCountFrequency (%)
1782 1
 
0.2%
1865 4
0.8%
1875 1
 
0.2%
1916 2
0.4%
2074 1
 
0.2%
2082 1
 
0.2%
2111 1
 
0.2%
2253 1
 
0.2%
2345 1
 
0.2%
2394 3
0.6%
ValueCountFrequency (%)
4795 1
 
0.2%
4784 3
0.6%
4780 1
 
0.2%
4759 3
0.6%
4755 2
0.4%
4749 1
 
0.2%
4748 4
0.8%
4730 1
 
0.2%
4726 1
 
0.2%
4720 1
 
0.2%

Interactions

2023-12-12T11:10:56.839759image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T11:10:55.423619image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T11:10:55.848236image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T11:10:56.380185image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T11:10:56.950438image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T11:10:55.523488image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T11:10:55.982842image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T11:10:56.492347image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T11:10:57.082186image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T11:10:55.628659image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T11:10:56.125977image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T11:10:56.597295image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T11:10:57.203596image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T11:10:55.734159image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T11:10:56.269017image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T11:10:56.716400image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-12T11:11:01.744359image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
창업기업프로그램중단사유코드이력일련번호최종수정수처리직원번호
창업기업프로그램중단사유코드1.0000.0970.1740.325
이력일련번호0.0971.0000.9580.000
최종수정수0.1740.9581.0000.000
처리직원번호0.3250.0000.0001.000
2023-12-12T11:11:01.875316image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
창업기업프로그램중단사유코드이력일련번호최종수정수처리직원번호
창업기업프로그램중단사유코드1.0000.0320.042-0.008
이력일련번호0.0321.0000.4910.069
최종수정수0.0420.4911.0000.086
처리직원번호-0.0080.0690.0861.000

Missing values

2023-12-12T11:10:57.348356image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-12T11:10:57.571515image/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

기업고객ID창업기업프로그램중단사유코드이력일련번호중단사유발생여부프로그램중단일자유효개시일자유효종료일자최종수정수처리시각처리직원번호
09bsBkYGgH691Y00:00.000:00.000:00.0303:10.84153
19bsBkYGgH693Y00:00.000:00.000:00.0206:34.14153
29bv3YIys6C101Y00:00.000:00.000:00.0104:00.03543
39bp1BBjC7z91Y00:00.000:00.000:00.0134:08.34269
49bth6yOZSq101Y00:00.000:00.000:00.0119:51.14160
59bpJjjl7JK91Y00:00.000:00.000:00.0332:24.52111
69bvWwFOUFK101Y00:00.000:00.000:00.0137:56.13163
79bxVESED4M91Y00:00.000:00.000:00.0126:28.33082
89bt2QVEPha101Y00:00.000:00.000:00.0101:36.84587
99bq59XqL25101Y00:00.000:00.000:00.0105:32.23973
기업고객ID창업기업프로그램중단사유코드이력일련번호중단사유발생여부프로그램중단일자유효개시일자유효종료일자최종수정수처리시각처리직원번호
4909bijIrzoiB41Y00:00.000:00.000:00.0150:37.13676
4919brLiEGuSn101Y00:00.000:00.000:00.0110:19.82782
4929bfFS0cO3a41Y00:00.000:00.000:00.0156:24.42443
4939bm9J8GzB581Y00:00.000:00.000:00.0154:06.43661
4949bqmHpjoJN91Y00:00.000:00.000:00.0142:05.93231
4959biaBFNVXY41Y00:00.000:00.000:00.0122:00.53355
4969biN7HVrD541Y00:00.000:00.000:00.0125:19.43574
4979bkjcKxMZR51Y00:00.000:00.000:00.0104:28.31782
4989bjkAppHlY41Y00:00.000:00.000:00.0148:33.74433
4999bkYkK1bJT51Y00:00.000:00.000:00.0113:06.44601