This package include SPSS related calculations done using python.
pip install psython
import psython as psy
This package is for calculating Cronbach's alpha of an entire dataset with a "if deleted" table for finding items that should be removed.
The package is using the pingouin package for the actuall calculation of Coronbach's alpha.
Here is an example of the SAQ DataFrame (q3r = q3 reversed):
q1 | q2 | q4 | q5 | q6 | q7 | q8 | q9 | q10 | q11 | ... | q15 | q16 | q17 | q18 | q19 | q20 | q21 | q22 | q23 | q3r | |
---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
0 | 2 | 1 | 2 | 2 | 2 | 3 | 1 | 1 | 2 | 1 | ... | 2 | 3 | 1 | 2 | 3 | 2 | 2 | 2 | 5 | 2 |
1 | 1 | 1 | 3 | 2 | 2 | 2 | 2 | 5 | 2 | 2 | ... | 4 | 3 | 2 | 2 | 3 | 4 | 4 | 4 | 2 | 2 |
2 | 2 | 3 | 2 | 4 | 1 | 2 | 2 | 2 | 2 | 3 | ... | 2 | 3 | 2 | 3 | 1 | 4 | 3 | 2 | 2 | 4 |
3 | 3 | 1 | 4 | 3 | 3 | 4 | 2 | 2 | 4 | 2 | ... | 3 | 3 | 2 | 4 | 2 | 4 | 4 | 4 | 3 | 5 |
4 | 2 | 1 | 2 | 2 | 3 | 3 | 2 | 4 | 2 | 2 | ... | 2 | 2 | 2 | 3 | 3 | 4 | 2 | 4 | 4 | 3 |
5 rows × 23 columns
psy.cronbach_alpha_scale_if_deleted(df)
Where df is the items dataframe (each item as a column) and the function will return two objects - the Cronbach's alpha of the entire DataFrame at position 0 and the table of the "if delete" items in position 1.
Item | Scale Mean if Item Deleted | Scale Variance if Item Deleted | Corrected Item-Total Correlation | Cronbach's Alpha if Item Deleted | |
---|---|---|---|---|---|
0 | q1 | 59.892260 | 90.121072 | 0.520928 | 0.791887 |
1 | q2 | 60.642940 | 101.063899 | -0.163158 | 0.819978 |
2 | q4 | 59.480358 | 87.967999 | 0.569241 | 0.788177 |
3 | q5 | 59.544146 | 89.303401 | 0.480579 | 0.792419 |
4 | q6 | 60.039284 | 87.605071 | 0.482416 | 0.791397 |
5 | q7 | 59.342668 | 85.655685 | 0.594245 | 0.785032 |
6 | q8 | 60.029560 | 89.900293 | 0.503704 | 0.792141 |
7 | q9 | 59.420070 | 100.881838 | -0.137191 | 0.828613 |
8 | q10 | 59.985609 | 92.232867 | 0.355784 | 0.798693 |
9 | q11 | 60.011280 | 88.790145 | 0.568318 | 0.789112 |
10 | q12 | 59.106962 | 88.451979 | 0.562942 | 0.788889 |
11 | q13 | 59.817192 | 87.839720 | 0.576902 | 0.787798 |
12 | q14 | 59.390121 | 87.491716 | 0.562476 | 0.787931 |
13 | q15 | 59.500194 | 88.766051 | 0.484296 | 0.791916 |
14 | q16 | 59.387009 | 88.329154 | 0.570772 | 0.788520 |
15 | q17 | 59.799689 | 88.441961 | 0.587849 | 0.788165 |
16 | q18 | 59.697783 | 85.993065 | 0.608925 | 0.784771 |
17 | q19 | 59.974329 | 104.442142 | -0.295795 | 0.832243 |
18 | q20 | 58.642163 | 91.699140 | 0.313782 | 0.800711 |
19 | q21 | 59.095683 | 87.678779 | 0.561128 | 0.788157 |
20 | q22 | 59.378452 | 101.109248 | -0.152704 | 0.823798 |
21 | q23 | 58.831972 | 98.820783 | -0.044039 | 0.818680 |
22 | q3r | 58.851809 | 89.021221 | 0.434762 | 0.794258 |