Overview

Dataset statistics

Number of variables11
Number of observations101
Missing cells1
Missing cells (%)0.1%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory8.8 KiB
Average record size in memory89.3 B

Variable types

DateTime1
Categorical4
Numeric1
Boolean5

Alerts

Did you seek any specialist for a treatment? is highly imbalanced (67.5%)Imbalance

Reproduction

Analysis started2024-01-08 08:40:01.203516
Analysis finished2024-01-08 08:40:02.932379
Duration1.73 second
Software versionydata-profiling vv4.6.3
Download configurationconfig.json

Variables

Timestamp
Date

Distinct92
Distinct (%)91.1%
Missing0
Missing (%)0.0%
Memory size936.0 B
Minimum2020-07-13 10:07:32
Maximum2020-09-07 18:24:00
2024-01-08T14:10:03.055642image/svg+xmlMatplotlib v3.8.2, https://matplotlib.org/
2024-01-08T14:10:03.233273image/svg+xmlMatplotlib v3.8.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

Choose your gender
Categorical

Distinct2
Distinct (%)2.0%
Missing0
Missing (%)0.0%
Memory size936.0 B
Female
75 
Male
26 

Length

Max length6
Median length6
Mean length5.4851485
Min length4

Characters and Unicode

Total characters554
Distinct characters6
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

Unique0 ?
Unique (%)0.0%

Sample

1st rowFemale
2nd rowMale
3rd rowMale
4th rowFemale
5th rowMale

Common Values

ValueCountFrequency (%)
Female 75
74.3%
Male 26
 
25.7%

Length

2024-01-08T14:10:03.400821image/svg+xmlMatplotlib v3.8.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-01-08T14:10:03.534574image/svg+xmlMatplotlib v3.8.2, https://matplotlib.org/
ValueCountFrequency (%)
female 75
74.3%
male 26
 
25.7%

Most occurring characters

ValueCountFrequency (%)
e 176
31.8%
a 101
18.2%
l 101
18.2%
F 75
13.5%
m 75
13.5%
M 26
 
4.7%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 453
81.8%
Uppercase Letter 101
 
18.2%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
e 176
38.9%
a 101
22.3%
l 101
22.3%
m 75
16.6%
Uppercase Letter
ValueCountFrequency (%)
F 75
74.3%
M 26
 
25.7%

Most occurring scripts

ValueCountFrequency (%)
Latin 554
100.0%

Most frequent character per script

Latin
ValueCountFrequency (%)
e 176
31.8%
a 101
18.2%
l 101
18.2%
F 75
13.5%
m 75
13.5%
M 26
 
4.7%

Most occurring blocks

ValueCountFrequency (%)
ASCII 554
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
e 176
31.8%
a 101
18.2%
l 101
18.2%
F 75
13.5%
m 75
13.5%
M 26
 
4.7%

Age
Real number (ℝ)

Distinct7
Distinct (%)7.0%
Missing1
Missing (%)1.0%
Infinite0
Infinite (%)0.0%
Mean20.53
Minimum18
Maximum24
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size936.0 B
2024-01-08T14:10:03.646062image/svg+xmlMatplotlib v3.8.2, https://matplotlib.org/

Quantile statistics

Minimum18
5-th percentile18
Q118
median19
Q323
95-th percentile24
Maximum24
Range6
Interquartile range (IQR)5

Descriptive statistics

Standard deviation2.4962801
Coefficient of variation (CV)0.12159182
Kurtosis-1.640801
Mean20.53
Median Absolute Deviation (MAD)1
Skewness0.37717515
Sum2053
Variance6.2314141
MonotonicityNot monotonic
2024-01-08T14:10:03.762941image/svg+xmlMatplotlib v3.8.2, https://matplotlib.org/
Histogram with fixed size bins (bins=7)
ValueCountFrequency (%)
18 32
31.7%
24 23
22.8%
19 21
20.8%
23 13
12.9%
20 6
 
5.9%
21 3
 
3.0%
22 2
 
2.0%
(Missing) 1
 
1.0%
ValueCountFrequency (%)
18 32
31.7%
19 21
20.8%
20 6
 
5.9%
21 3
 
3.0%
22 2
 
2.0%
23 13
12.9%
24 23
22.8%
ValueCountFrequency (%)
24 23
22.8%
23 13
12.9%
22 2
 
2.0%
21 3
 
3.0%
20 6
 
5.9%
19 21
20.8%
18 32
31.7%

What is your course?
Categorical

Distinct49
Distinct (%)48.5%
Missing0
Missing (%)0.0%
Memory size936.0 B
BCS
18 
Engineering
17 
BIT
10 
Biomedical science
 
4
KOE
 
4
Other values (44)
48 

Length

Max length23
Median length18
Mean length7.6534653
Min length2

Characters and Unicode

Total characters773
Distinct characters40
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

Unique40 ?
Unique (%)39.6%

Sample

1st rowEngineering
2nd rowIslamic education
3rd rowBIT
4th rowLaws
5th rowMathemathics

Common Values

ValueCountFrequency (%)
BCS 18
17.8%
Engineering 17
16.8%
BIT 10
 
9.9%
Biomedical science 4
 
4.0%
KOE 4
 
4.0%
psychology 2
 
2.0%
Engine 2
 
2.0%
Laws 2
 
2.0%
BENL 2
 
2.0%
ENM 1
 
1.0%
Other values (39) 39
38.6%

Length

2024-01-08T14:10:03.895576image/svg+xmlMatplotlib v3.8.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
bcs 18
 
15.3%
engineering 17
 
14.4%
bit 10
 
8.5%
koe 6
 
5.1%
science 5
 
4.2%
biomedical 4
 
3.4%
psychology 3
 
2.5%
benl 3
 
2.5%
pendidikan 3
 
2.5%
islam 3
 
2.5%
Other values (37) 46
39.0%

Most occurring characters

ValueCountFrequency (%)
n 89
 
11.5%
i 82
 
10.6%
e 67
 
8.7%
g 46
 
6.0%
B 38
 
4.9%
a 31
 
4.0%
c 31
 
4.0%
E 30
 
3.9%
s 30
 
3.9%
o 27
 
3.5%
Other values (30) 302
39.1%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 541
70.0%
Uppercase Letter 208
 
26.9%
Space Separator 24
 
3.1%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
n 89
16.5%
i 82
15.2%
e 67
12.4%
g 46
8.5%
a 31
 
5.7%
c 31
 
5.7%
s 30
 
5.5%
o 27
 
5.0%
r 25
 
4.6%
m 17
 
3.1%
Other values (11) 96
17.7%
Uppercase Letter
ValueCountFrequency (%)
B 38
18.3%
E 30
14.4%
S 26
12.5%
C 21
10.1%
I 18
8.7%
T 14
 
6.7%
K 10
 
4.8%
L 9
 
4.3%
A 7
 
3.4%
M 7
 
3.4%
Other values (8) 28
13.5%
Space Separator
ValueCountFrequency (%)
24
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 749
96.9%
Common 24
 
3.1%

Most frequent character per script

Latin
ValueCountFrequency (%)
n 89
 
11.9%
i 82
 
10.9%
e 67
 
8.9%
g 46
 
6.1%
B 38
 
5.1%
a 31
 
4.1%
c 31
 
4.1%
E 30
 
4.0%
s 30
 
4.0%
o 27
 
3.6%
Other values (29) 278
37.1%
Common
ValueCountFrequency (%)
24
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 773
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
n 89
 
11.5%
i 82
 
10.6%
e 67
 
8.7%
g 46
 
6.0%
B 38
 
4.9%
a 31
 
4.0%
c 31
 
4.0%
E 30
 
3.9%
s 30
 
3.9%
o 27
 
3.5%
Other values (30) 302
39.1%

Your current year of Study
Categorical

Distinct7
Distinct (%)6.9%
Missing0
Missing (%)0.0%
Memory size936.0 B
year 1
41 
Year 3
19 
Year 2
16 
year 2
10 
year 4
8 
Other values (2)
7 

Length

Max length6
Median length6
Mean length6
Min length6

Characters and Unicode

Total characters606
Distinct characters10
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowyear 1
2nd rowyear 2
3rd rowYear 1
4th rowyear 3
5th rowyear 4

Common Values

ValueCountFrequency (%)
year 1 41
40.6%
Year 3 19
18.8%
Year 2 16
 
15.8%
year 2 10
 
9.9%
year 4 8
 
7.9%
year 3 5
 
5.0%
Year 1 2
 
2.0%

Length

2024-01-08T14:10:04.021424image/svg+xmlMatplotlib v3.8.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-01-08T14:10:04.157137image/svg+xmlMatplotlib v3.8.2, https://matplotlib.org/
ValueCountFrequency (%)
year 101
50.0%
1 43
21.3%
2 26
 
12.9%
3 24
 
11.9%
4 8
 
4.0%

Most occurring characters

ValueCountFrequency (%)
e 101
16.7%
a 101
16.7%
r 101
16.7%
101
16.7%
y 64
10.6%
1 43
7.1%
Y 37
 
6.1%
2 26
 
4.3%
3 24
 
4.0%
4 8
 
1.3%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 367
60.6%
Space Separator 101
 
16.7%
Decimal Number 101
 
16.7%
Uppercase Letter 37
 
6.1%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
e 101
27.5%
a 101
27.5%
r 101
27.5%
y 64
17.4%
Decimal Number
ValueCountFrequency (%)
1 43
42.6%
2 26
25.7%
3 24
23.8%
4 8
 
7.9%
Space Separator
ValueCountFrequency (%)
101
100.0%
Uppercase Letter
ValueCountFrequency (%)
Y 37
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 404
66.7%
Common 202
33.3%

Most frequent character per script

Latin
ValueCountFrequency (%)
e 101
25.0%
a 101
25.0%
r 101
25.0%
y 64
15.8%
Y 37
 
9.2%
Common
ValueCountFrequency (%)
101
50.0%
1 43
21.3%
2 26
 
12.9%
3 24
 
11.9%
4 8
 
4.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 606
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
e 101
16.7%
a 101
16.7%
r 101
16.7%
101
16.7%
y 64
10.6%
1 43
7.1%
Y 37
 
6.1%
2 26
 
4.3%
3 24
 
4.0%
4 8
 
1.3%

What is your CGPA?
Categorical

Distinct6
Distinct (%)5.9%
Missing0
Missing (%)0.0%
Memory size936.0 B
3.50 - 4.00
47 
3.00 - 3.49
43 
2.50 - 2.99
 
4
0 - 1.99
 
4
2.00 - 2.49
 
2

Length

Max length12
Median length11
Mean length10.891089
Min length8

Characters and Unicode

Total characters1100
Distinct characters10
Distinct categories4 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1 ?
Unique (%)1.0%

Sample

1st row3.00 - 3.49
2nd row3.00 - 3.49
3rd row3.00 - 3.49
4th row3.00 - 3.49
5th row3.00 - 3.49

Common Values

ValueCountFrequency (%)
3.50 - 4.00 47
46.5%
3.00 - 3.49 43
42.6%
2.50 - 2.99 4
 
4.0%
0 - 1.99 4
 
4.0%
2.00 - 2.49 2
 
2.0%
3.50 - 4.00 1
 
1.0%

Length

2024-01-08T14:10:04.328094image/svg+xmlMatplotlib v3.8.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-01-08T14:10:04.479514image/svg+xmlMatplotlib v3.8.2, https://matplotlib.org/
ValueCountFrequency (%)
101
33.3%
3.50 48
15.8%
4.00 48
15.8%
3.00 43
14.2%
3.49 43
14.2%
2.50 4
 
1.3%
2.99 4
 
1.3%
0 4
 
1.3%
1.99 4
 
1.3%
2.00 2
 
0.7%

Most occurring characters

ValueCountFrequency (%)
0 242
22.0%
203
18.5%
. 198
18.0%
3 134
12.2%
- 101
9.2%
4 93
 
8.5%
9 61
 
5.5%
5 52
 
4.7%
2 12
 
1.1%
1 4
 
0.4%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 598
54.4%
Space Separator 203
 
18.5%
Other Punctuation 198
 
18.0%
Dash Punctuation 101
 
9.2%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 242
40.5%
3 134
22.4%
4 93
 
15.6%
9 61
 
10.2%
5 52
 
8.7%
2 12
 
2.0%
1 4
 
0.7%
Space Separator
ValueCountFrequency (%)
203
100.0%
Other Punctuation
ValueCountFrequency (%)
. 198
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 101
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 1100
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 242
22.0%
203
18.5%
. 198
18.0%
3 134
12.2%
- 101
9.2%
4 93
 
8.5%
9 61
 
5.5%
5 52
 
4.7%
2 12
 
1.1%
1 4
 
0.4%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1100
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 242
22.0%
203
18.5%
. 198
18.0%
3 134
12.2%
- 101
9.2%
4 93
 
8.5%
9 61
 
5.5%
5 52
 
4.7%
2 12
 
1.1%
1 4
 
0.4%

Marital status
Boolean

Distinct2
Distinct (%)2.0%
Missing0
Missing (%)0.0%
Memory size229.0 B
False
85 
True
16 
ValueCountFrequency (%)
False 85
84.2%
True 16
 
15.8%
2024-01-08T14:10:04.709908image/svg+xmlMatplotlib v3.8.2, https://matplotlib.org/

Do you have Depression?
Boolean

Distinct2
Distinct (%)2.0%
Missing0
Missing (%)0.0%
Memory size229.0 B
False
66 
True
35 
ValueCountFrequency (%)
False 66
65.3%
True 35
34.7%
2024-01-08T14:10:04.815664image/svg+xmlMatplotlib v3.8.2, https://matplotlib.org/

Do you have Anxiety?
Boolean

Distinct2
Distinct (%)2.0%
Missing0
Missing (%)0.0%
Memory size229.0 B
False
67 
True
34 
ValueCountFrequency (%)
False 67
66.3%
True 34
33.7%
2024-01-08T14:10:04.918502image/svg+xmlMatplotlib v3.8.2, https://matplotlib.org/

Do you have Panic attack?
Boolean

Distinct2
Distinct (%)2.0%
Missing0
Missing (%)0.0%
Memory size229.0 B
False
68 
True
33 
ValueCountFrequency (%)
False 68
67.3%
True 33
32.7%
2024-01-08T14:10:05.021997image/svg+xmlMatplotlib v3.8.2, https://matplotlib.org/

Did you seek any specialist for a treatment?
Boolean

IMBALANCE 

Distinct2
Distinct (%)2.0%
Missing0
Missing (%)0.0%
Memory size229.0 B
False
95 
True
 
6
ValueCountFrequency (%)
False 95
94.1%
True 6
 
5.9%
2024-01-08T14:10:05.122324image/svg+xmlMatplotlib v3.8.2, https://matplotlib.org/

Interactions

2024-01-08T14:10:02.076056image/svg+xmlMatplotlib v3.8.2, https://matplotlib.org/

Missing values

2024-01-08T14:10:02.485285image/svg+xmlMatplotlib v3.8.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-01-08T14:10:02.805651image/svg+xmlMatplotlib v3.8.2, https://matplotlib.org/
Nullity matrix is a data-dense display which lets you quickly visually pick out patterns in data completion.

Sample

TimestampChoose your genderAgeWhat is your course?Your current year of StudyWhat is your CGPA?Marital statusDo you have Depression?Do you have Anxiety?Do you have Panic attack?Did you seek any specialist for a treatment?
08/7/2020 12:02Female18.0Engineeringyear 13.00 - 3.49NoYesNoYesNo
18/7/2020 12:04Male21.0Islamic educationyear 23.00 - 3.49NoNoYesNoNo
28/7/2020 12:05Male19.0BITYear 13.00 - 3.49NoYesYesYesNo
38/7/2020 12:06Female22.0Lawsyear 33.00 - 3.49YesYesNoNoNo
48/7/2020 12:13Male23.0Mathemathicsyear 43.00 - 3.49NoNoNoNoNo
58/7/2020 12:31Male19.0EngineeringYear 23.50 - 4.00NoNoNoYesNo
68/7/2020 12:32Female23.0Pendidikan islamyear 23.50 - 4.00YesYesNoYesNo
78/7/2020 12:33Female18.0BCSyear 13.50 - 4.00NoNoYesNoNo
88/7/2020 12:35Female19.0Human ResourcesYear 22.50 - 2.99NoNoNoNoNo
98/7/2020 12:39Male18.0Irkhsyear 13.50 - 4.00NoNoYesYesNo
TimestampChoose your genderAgeWhat is your course?Your current year of StudyWhat is your CGPA?Marital statusDo you have Depression?Do you have Anxiety?Do you have Panic attack?Did you seek any specialist for a treatment?
9113/07/2020 14:38:12Male18.0KoeYear 23.00 - 3.49NoNoYesNoNo
9213/07/2020 14:48:05Female19.0KOEyear 23.00 - 3.49YesYesNoNoNo
9313/07/2020 16:15:13Female18.0BENLyear 13.00 - 3.49NoYesNoNoNo
9413/07/2020 17:30:44Female24.0FiqhYear 30 - 1.99NoNoNoYesNo
9513/07/2020 19:08:32Female18.0Islamic Educationyear 13.50 - 4.00NoNoNoNoNo
9613/07/2020 19:56:49Female21.0BCSyear 13.50 - 4.00NoNoYesNoNo
9713/07/2020 21:21:42Male18.0EngineeringYear 23.00 - 3.49NoYesYesNoNo
9813/07/2020 21:22:56Female19.0NursingYear 33.50 - 4.00YesYesNoYesNo
9913/07/2020 21:23:57Female23.0Pendidikan Islamyear 43.50 - 4.00NoNoNoNoNo
10018/07/2020 20:16:21Male20.0Biomedical scienceYear 23.00 - 3.49NoNoNoNoNo