Overview

Dataset statistics

Number of variables10
Number of observations231
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory19.5 KiB
Average record size in memory86.6 B

Variable types

Numeric5
Text2
Categorical2
DateTime1

Dataset

Description한국산업기술진흥원의 과제 지원을 통한 일반 과제현황 관련 고객만족도 조사 데이터로서 조사기관, 년도, 평점 등의 데이터를 제공합니다.
URLhttps://www.data.go.kr/data/15117024/fileData.do

Alerts

성과발생년도 is highly overall correlated with 조사년도High correlation
조사년도 is highly overall correlated with 성과발생년도High correlation
고객만족도 순번 is highly imbalanced (66.3%)Imbalance

Reproduction

Analysis started2023-12-12 22:29:52.371652
Analysis finished2023-12-12 22:29:56.008798
Duration3.64 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

성과발생년도
Real number (ℝ)

HIGH CORRELATION 

Distinct6
Distinct (%)2.6%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2020.4459
Minimum2017
Maximum2022
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size2.2 KiB
2023-12-13T07:29:56.056168image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum2017
5-th percentile2019
Q12020
median2020
Q32021
95-th percentile2022
Maximum2022
Range5
Interquartile range (IQR)1

Descriptive statistics

Standard deviation1.1441222
Coefficient of variation (CV)0.00056627213
Kurtosis-0.7052424
Mean2020.4459
Median Absolute Deviation (MAD)1
Skewness-0.14704355
Sum466723
Variance1.3090156
MonotonicityNot monotonic
2023-12-13T07:29:56.180205image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=6)
ValueCountFrequency (%)
2020 71
30.7%
2022 55
23.8%
2021 52
22.5%
2019 49
21.2%
2017 2
 
0.9%
2018 2
 
0.9%
ValueCountFrequency (%)
2017 2
 
0.9%
2018 2
 
0.9%
2019 49
21.2%
2020 71
30.7%
2021 52
22.5%
2022 55
23.8%
ValueCountFrequency (%)
2022 55
23.8%
2021 52
22.5%
2020 71
30.7%
2019 49
21.2%
2018 2
 
0.9%
2017 2
 
0.9%

접수번호
Text

Distinct112
Distinct (%)48.5%
Missing0
Missing (%)0.0%
Memory size1.9 KiB
2023-12-13T07:29:56.422180image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length10
Median length10
Mean length10
Min length10

Characters and Unicode

Total characters2310
Distinct characters14
Distinct categories2 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique38 ?
Unique (%)16.5%

Sample

1st rowN060700008
2nd rowN038100005
3rd rowN033400001
4th rowN033400001
5th rowA013700123
ValueCountFrequency (%)
n038100005 7
 
3.0%
a019100008 6
 
2.6%
p010700029 6
 
2.6%
p114000045 5
 
2.2%
p122200006 4
 
1.7%
a011800005 4
 
1.7%
p010700021 4
 
1.7%
p010700009 4
 
1.7%
a019700279 4
 
1.7%
p006801132 4
 
1.7%
Other values (102) 183
79.2%
2023-12-13T07:29:56.810365image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 991
42.9%
1 292
 
12.6%
P 155
 
6.7%
7 119
 
5.2%
5 112
 
4.8%
2 111
 
4.8%
8 104
 
4.5%
4 102
 
4.4%
9 95
 
4.1%
3 81
 
3.5%
Other values (4) 148
 
6.4%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 2079
90.0%
Uppercase Letter 231
 
10.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 991
47.7%
1 292
 
14.0%
7 119
 
5.7%
5 112
 
5.4%
2 111
 
5.3%
8 104
 
5.0%
4 102
 
4.9%
9 95
 
4.6%
3 81
 
3.9%
6 72
 
3.5%
Uppercase Letter
ValueCountFrequency (%)
P 155
67.1%
A 43
 
18.6%
N 26
 
11.3%
F 7
 
3.0%

Most occurring scripts

ValueCountFrequency (%)
Common 2079
90.0%
Latin 231
 
10.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 991
47.7%
1 292
 
14.0%
7 119
 
5.7%
5 112
 
5.4%
2 111
 
5.3%
8 104
 
5.0%
4 102
 
4.9%
9 95
 
4.6%
3 81
 
3.9%
6 72
 
3.5%
Latin
ValueCountFrequency (%)
P 155
67.1%
A 43
 
18.6%
N 26
 
11.3%
F 7
 
3.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 2310
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 991
42.9%
1 292
 
12.6%
P 155
 
6.7%
7 119
 
5.2%
5 112
 
4.8%
2 111
 
4.8%
8 104
 
4.5%
4 102
 
4.4%
9 95
 
4.1%
3 81
 
3.5%
Other values (4) 148
 
6.4%

고객만족도 순번
Categorical

IMBALANCE 

Distinct3
Distinct (%)1.3%
Missing0
Missing (%)0.0%
Memory size1.9 KiB
1
209 
2
 
16
3
 
6

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row1
2nd row1
3rd row1
4th row3
5th row1

Common Values

ValueCountFrequency (%)
1 209
90.5%
2 16
 
6.9%
3 6
 
2.6%

Length

2023-12-13T07:29:56.950402image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T07:29:57.033875image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
1 209
90.5%
2 16
 
6.9%
3 6
 
2.6%

시점구분
Categorical

Distinct2
Distinct (%)0.9%
Missing0
Missing (%)0.0%
Memory size1.9 KiB
R67001
160 
R67002
71 

Length

Max length6
Median length6
Mean length6
Min length6

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowR67001
2nd rowR67001
3rd rowR67001
4th rowR67001
5th rowR67001

Common Values

ValueCountFrequency (%)
R67001 160
69.3%
R67002 71
30.7%

Length

2023-12-13T07:29:57.124408image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T07:29:57.222397image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
r67001 160
69.3%
r67002 71
30.7%

조사년도
Real number (ℝ)

HIGH CORRELATION 

Distinct6
Distinct (%)2.6%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2020.4459
Minimum2017
Maximum2022
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size2.2 KiB
2023-12-13T07:29:57.303727image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum2017
5-th percentile2019
Q12020
median2020
Q32021
95-th percentile2022
Maximum2022
Range5
Interquartile range (IQR)1

Descriptive statistics

Standard deviation1.1441222
Coefficient of variation (CV)0.00056627213
Kurtosis-0.7052424
Mean2020.4459
Median Absolute Deviation (MAD)1
Skewness-0.14704355
Sum466723
Variance1.3090156
MonotonicityNot monotonic
2023-12-13T07:29:57.405335image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=6)
ValueCountFrequency (%)
2020 71
30.7%
2022 55
23.8%
2021 52
22.5%
2019 49
21.2%
2017 2
 
0.9%
2018 2
 
0.9%
ValueCountFrequency (%)
2017 2
 
0.9%
2018 2
 
0.9%
2019 49
21.2%
2020 71
30.7%
2021 52
22.5%
2022 55
23.8%
ValueCountFrequency (%)
2022 55
23.8%
2021 52
22.5%
2020 71
30.7%
2019 49
21.2%
2018 2
 
0.9%
2017 2
 
0.9%

평균 만족도 점수
Real number (ℝ)

Distinct34
Distinct (%)14.7%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean76.835498
Minimum3
Maximum100
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size2.2 KiB
2023-12-13T07:29:57.550313image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum3
5-th percentile4
Q184
median90
Q394.5
95-th percentile98
Maximum100
Range97
Interquartile range (IQR)10.5

Descriptive statistics

Standard deviation31.842257
Coefficient of variation (CV)0.41442117
Kurtosis1.0585942
Mean76.835498
Median Absolute Deviation (MAD)5
Skewness-1.6903449
Sum17749
Variance1013.9293
MonotonicityNot monotonic
2023-12-13T07:29:57.707634image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=34)
ValueCountFrequency (%)
90 26
 
11.3%
95 19
 
8.2%
93 16
 
6.9%
89 14
 
6.1%
92 13
 
5.6%
91 12
 
5.2%
98 12
 
5.2%
4 11
 
4.8%
96 11
 
4.8%
88 11
 
4.8%
Other values (24) 86
37.2%
ValueCountFrequency (%)
3 2
 
0.9%
4 11
4.8%
5 8
3.5%
6 2
 
0.9%
7 3
 
1.3%
9 7
3.0%
10 2
 
0.9%
16 1
 
0.4%
18 2
 
0.9%
52 2
 
0.9%
ValueCountFrequency (%)
100 4
 
1.7%
99 2
 
0.9%
98 12
5.2%
97 10
4.3%
96 11
4.8%
95 19
8.2%
94 9
3.9%
93 16
6.9%
92 13
5.6%
91 12
5.2%

고객수
Real number (ℝ)

Distinct75
Distinct (%)32.5%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean48.277056
Minimum2
Maximum400
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size2.2 KiB
2023-12-13T07:29:57.856321image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum2
5-th percentile5
Q111
median29
Q353.5
95-th percentile178
Maximum400
Range398
Interquartile range (IQR)42.5

Descriptive statistics

Standard deviation64.45687
Coefficient of variation (CV)1.335145
Kurtosis11.9751
Mean48.277056
Median Absolute Deviation (MAD)19
Skewness3.1774424
Sum11152
Variance4154.6881
MonotonicityNot monotonic
2023-12-13T07:29:58.003848image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
10 18
 
7.8%
30 14
 
6.1%
8 8
 
3.5%
7 8
 
3.5%
19 8
 
3.5%
15 7
 
3.0%
50 7
 
3.0%
26 6
 
2.6%
5 6
 
2.6%
100 6
 
2.6%
Other values (65) 143
61.9%
ValueCountFrequency (%)
2 5
 
2.2%
3 4
 
1.7%
4 1
 
0.4%
5 6
 
2.6%
6 2
 
0.9%
7 8
3.5%
8 8
3.5%
9 5
 
2.2%
10 18
7.8%
11 3
 
1.3%
ValueCountFrequency (%)
400 2
0.9%
370 1
 
0.4%
315 1
 
0.4%
311 1
 
0.4%
251 2
0.9%
200 3
1.3%
198 2
0.9%
158 2
0.9%
151 2
0.9%
128 1
 
0.4%

조사기관명
Text

Distinct114
Distinct (%)49.4%
Missing0
Missing (%)0.0%
Memory size1.9 KiB
2023-12-13T07:29:58.249079image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length41
Median length24
Mean length9.9220779
Min length2

Characters and Unicode

Total characters2292
Distinct characters221
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

Unique49 ?
Unique (%)21.2%

Sample

1st row사단법인 한국비아이기술사업화협회
2nd row창원대학교 산학협력단
3rd row글로벌리서치
4th row울산대학교산학협력단WISET울산지역사업단
5th row다원텍 주식회사
ValueCountFrequency (%)
자체조사 19
 
6.2%
산학협력단 18
 
5.9%
한국생산기술연구원 10
 
3.3%
재)자동차융합기술원 8
 
2.6%
자체 7
 
2.3%
한국산업기술시험원 6
 
2.0%
창원대학교 6
 
2.0%
주식회사 6
 
2.0%
한국안광학산업진흥원 5
 
1.6%
경상국립대학교 4
 
1.3%
Other values (124) 217
70.9%
2023-12-13T07:29:58.678267image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
원 84
 
3.7%
79
 
3.4%
( 68
 
3.0%
) 68
 
3.0%
학 66
 
2.9%
산 63
 
2.7%
기 63
 
2.7%
크 59
 
2.6%
국 56
 
2.4%
한 54
 
2.4%
Other values (211) 1632
71.2%

Most occurring categories

ValueCountFrequency (%)
Other Letter 2015
87.9%
Space Separator 79
 
3.4%
Open Punctuation 68
 
3.0%
Close Punctuation 68
 
3.0%
Uppercase Letter 27
 
1.2%
Other Punctuation 19
 
0.8%
Lowercase Letter 12
 
0.5%
Other Symbol 2
 
0.1%
Decimal Number 2
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
원 84
 
4.2%
학 66
 
3.3%
산 63
 
3.1%
기 63
 
3.1%
크 59
 
2.9%
국 56
 
2.8%
한 54
 
2.7%
술 53
 
2.6%
자 51
 
2.5%
사 50
 
2.5%
Other values (184) 1416
70.3%
Uppercase Letter
ValueCountFrequency (%)
K 4
14.8%
I 4
14.8%
A 4
14.8%
T 3
11.1%
S 3
11.1%
E 2
7.4%
D 2
7.4%
Q 1
 
3.7%
X 1
 
3.7%
W 1
 
3.7%
Other values (2) 2
7.4%
Lowercase Letter
ValueCountFrequency (%)
a 2
16.7%
r 2
16.7%
d 2
16.7%
u 1
8.3%
e 1
8.3%
l 1
8.3%
i 1
8.3%
o 1
8.3%
n 1
8.3%
Space Separator
ValueCountFrequency (%)
79
100.0%
Open Punctuation
ValueCountFrequency (%)
( 68
100.0%
Close Punctuation
ValueCountFrequency (%)
) 68
100.0%
Other Punctuation
ValueCountFrequency (%)
, 19
100.0%
Other Symbol
ValueCountFrequency (%)
㈜ 2
100.0%
Decimal Number
ValueCountFrequency (%)
3 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 2017
88.0%
Common 236
 
10.3%
Latin 39
 
1.7%

Most frequent character per script

Hangul
ValueCountFrequency (%)
원 84
 
4.2%
학 66
 
3.3%
산 63
 
3.1%
기 63
 
3.1%
크 59
 
2.9%
국 56
 
2.8%
한 54
 
2.7%
술 53
 
2.6%
자 51
 
2.5%
사 50
 
2.5%
Other values (185) 1418
70.3%
Latin
ValueCountFrequency (%)
K 4
 
10.3%
I 4
 
10.3%
A 4
 
10.3%
T 3
 
7.7%
S 3
 
7.7%
a 2
 
5.1%
r 2
 
5.1%
E 2
 
5.1%
d 2
 
5.1%
D 2
 
5.1%
Other values (11) 11
28.2%
Common
ValueCountFrequency (%)
79
33.5%
( 68
28.8%
) 68
28.8%
, 19
 
8.1%
3 2
 
0.8%

Most occurring blocks

ValueCountFrequency (%)
Hangul 2015
87.9%
ASCII 275
 
12.0%
None 2
 
0.1%

Most frequent character per block

Hangul
ValueCountFrequency (%)
원 84
 
4.2%
학 66
 
3.3%
산 63
 
3.1%
기 63
 
3.1%
크 59
 
2.9%
국 56
 
2.8%
한 54
 
2.7%
술 53
 
2.6%
자 51
 
2.5%
사 50
 
2.5%
Other values (184) 1416
70.3%
ASCII
ValueCountFrequency (%)
79
28.7%
( 68
24.7%
) 68
24.7%
, 19
 
6.9%
K 4
 
1.5%
I 4
 
1.5%
A 4
 
1.5%
T 3
 
1.1%
S 3
 
1.1%
a 2
 
0.7%
Other values (16) 21
 
7.6%
None
ValueCountFrequency (%)
㈜ 2
100.0%

국가과학기술정보서비스(NTIS) 순번
Real number (ℝ)

Distinct15
Distinct (%)6.5%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2.1364203 × 109
Minimum1.9041811 × 109
Maximum2.1390611 × 109
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size2.2 KiB
2023-12-13T07:29:58.854002image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1.9041811 × 109
5-th percentile2.1382726 × 109
Q12.1382726 × 109
median2.1382737 × 109
Q32.1382747 × 109
95-th percentile2.1390601 × 109
Maximum2.1390611 × 109
Range2.3487999 × 108
Interquartile range (IQR)2048

Descriptive statistics

Standard deviation21753227
Coefficient of variation (CV)0.010182092
Kurtosis112.91272
Mean2.1364203 × 109
Median Absolute Deviation (MAD)1024
Skewness-10.672792
Sum4.9351308 × 1011
Variance4.7320287 × 1014
MonotonicityNot monotonic
2023-12-13T07:29:58.977804image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=15)
ValueCountFrequency (%)
2138273663 80
34.6%
2138272639 68
29.4%
2138274687 30
 
13.0%
2139060081 11
 
4.8%
2139060085 8
 
3.5%
2139060083 6
 
2.6%
2139059065 5
 
2.2%
2139059057 4
 
1.7%
2139059059 4
 
1.7%
2139059061 4
 
1.7%
Other values (5) 11
 
4.8%
ValueCountFrequency (%)
1904181115 2
 
0.9%
2138272639 68
29.4%
2138273663 80
34.6%
2138274687 30
 
13.0%
2139059057 4
 
1.7%
2139059059 4
 
1.7%
2139059061 4
 
1.7%
2139059063 1
 
0.4%
2139059065 5
 
2.2%
2139060081 11
 
4.8%
ValueCountFrequency (%)
2139061105 2
 
0.9%
2139060089 4
 
1.7%
2139060087 2
 
0.9%
2139060085 8
3.5%
2139060083 6
2.6%
2139060081 11
4.8%
2139059065 5
2.2%
2139059063 1
 
0.4%
2139059061 4
 
1.7%
2139059059 4
 
1.7%

등록 및 수정일시
Date

Distinct75
Distinct (%)32.5%
Missing0
Missing (%)0.0%
Memory size1.9 KiB
Minimum2018-01-09 00:00:00
Maximum2023-01-31 00:00:00
2023-12-13T07:29:59.134186image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T07:29:59.298363image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

Interactions

2023-12-13T07:29:55.184076image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T07:29:52.777320image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T07:29:53.297177image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T07:29:53.812916image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T07:29:54.307715image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T07:29:55.275331image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T07:29:52.860232image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T07:29:53.394814image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T07:29:53.893716image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T07:29:54.421978image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T07:29:55.394548image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T07:29:53.031884image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T07:29:53.485733image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T07:29:54.004912image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T07:29:54.542926image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T07:29:55.506190image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T07:29:53.115784image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T07:29:53.582671image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T07:29:54.099538image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T07:29:54.660318image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T07:29:55.638186image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T07:29:53.211585image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T07:29:53.698188image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T07:29:54.209833image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T07:29:55.070382image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-13T07:29:59.421407image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
성과발생년도고객만족도 순번시점구분조사년도평균 만족도 점수고객수국가과학기술정보서비스(NTIS) 순번등록 및 수정일시
성과발생년도1.0000.2390.3241.0000.2660.197NaN0.999
고객만족도 순번0.2391.0000.0000.2390.0000.000NaN0.000
시점구분0.3240.0001.0000.3240.0000.000NaN0.000
조사년도1.0000.2390.3241.0000.2660.197NaN0.999
평균 만족도 점수0.2660.0000.0000.2661.0000.245NaN0.809
고객수0.1970.0000.0000.1970.2451.000NaN0.834
국가과학기술정보서비스(NTIS) 순번NaNNaNNaNNaNNaNNaN1.000NaN
등록 및 수정일시0.9990.0000.0000.9990.8090.834NaN1.000
2023-12-13T07:29:59.577023image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
시점구분고객만족도 순번
시점구분1.0000.000
고객만족도 순번0.0001.000
2023-12-13T07:29:59.675400image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
성과발생년도조사년도평균 만족도 점수고객수국가과학기술정보서비스(NTIS) 순번고객만족도 순번시점구분
성과발생년도1.0001.0000.080-0.119-0.4440.1730.392
조사년도1.0001.0000.080-0.119-0.4440.1730.392
평균 만족도 점수0.0800.0801.000-0.246-0.0720.0000.000
고객수-0.119-0.119-0.2461.0000.0760.0000.000
국가과학기술정보서비스(NTIS) 순번-0.444-0.444-0.0720.0761.0000.0000.000
고객만족도 순번0.1730.1730.0000.0000.0001.0000.000
시점구분0.3920.3920.0000.0000.0000.0001.000

Missing values

2023-12-13T07:29:55.778261image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-13T07:29:55.953709image/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

성과발생년도접수번호고객만족도 순번시점구분조사년도평균 만족도 점수고객수조사기관명국가과학기술정보서비스(NTIS) 순번등록 및 수정일시
02017N0607000081R6700120179064사단법인 한국비아이기술사업화협회19041811152018-01-09
12017N0381000051R6700120179237창원대학교 산학협력단19041811152018-01-10
22018N0334000011R6700120187954글로벌리서치21390590632018-12-19
32018N0334000013R6700120189126울산대학교산학협력단WISET울산지역사업단21390590652018-12-19
42019A0137001231R6700120198012다원텍 주식회사21390590572019-12-30
52019A0153006001R670012019958다원텍 주식회사21390590572019-12-30
62019P0068001201R67001201990100자체 조사21390590592020-01-03
72019P0494000521R6700120199037(주)드림경영컨설팅21390590592020-01-06
82019P0267002691R6700120198060이암허브21390590612020-01-07
92019A0131000011R67001201910087한국생산기술연구원21390590612020-01-07
성과발생년도접수번호고객만족도 순번시점구분조사년도평균 만족도 점수고객수조사기관명국가과학기술정보서비스(NTIS) 순번등록 및 수정일시
2212021F0712145141R6700220219610(재)세종테크노파크21382746872021-12-30
2222021P0861000971R6700220214400사나래(주)농업회사법인21382746872022-01-03
2232021P1569000141R670022021433세계김치연구소21382726392022-01-05
2242021N0555000011R67002202191151리서치코리아21382726392022-01-17
2252021P1140000451R6700220219553(주)지아이피21382726392022-01-19
2262022P1569000181R670022022519라스고21382736632023-01-16
2272022P1841000471R670022022897한국산업기술시험원21382746872023-01-17
2282022P1401000041R67002202290100라마당21382746872023-01-17
2292022P1222000061R670022022477경상국립대학교 기술경영학과21382726392023-01-18
2302022P1222000062R670022022470경상국립대학교 기술경영학과21382726392023-01-18