Metadata-Version: 2.1
Name: psython
Version: 0.0.6
Summary: A package for SPSS methods
Home-page: https://github.com/cxt9/psython
Author: Doron Goldberg
Author-email: doron.goldberg@gmail.com
License: UNKNOWN
Platform: UNKNOWN
Classifier: Programming Language :: Python :: 3
Classifier: License :: OSI Approved :: MIT License
Classifier: Operating System :: OS Independent
Requires-Python: >=3.6
Description-Content-Type: text/markdown

# Psython

This package include SPSS related calculations done using python.

## Installation

```
pip install psython
```

## Importing

```
import psython as psy
```

## Cronbach's alpha - with "if deleted"

This package is for calculating Cronbach's alpha of an entire dataset with an "if deleted" table for finding items that should be removed.

The package is using the pingouin package for the actuall calculation of Cronbach's alpha.

### Usage

Here an example of the SAQ DataFrame (q3r = q3 reversed):

<div>

<table border="1" class="dataframe">
  <thead>
    <tr style="text-align: right;">
      <th></th>
      <th>q1</th>
      <th>q2</th>
      <th>q4</th>
      <th>q5</th>
      <th>q6</th>
      <th>q7</th>
      <th>q8</th>
      <th>q9</th>
      <th>q10</th>
      <th>q11</th>
      <th>...</th>
      <th>q15</th>
      <th>q16</th>
      <th>q17</th>
      <th>q18</th>
      <th>q19</th>
      <th>q20</th>
      <th>q21</th>
      <th>q22</th>
      <th>q23</th>
      <th>q3r</th>
    </tr>
  </thead>
  <tbody>
    <tr>
      <th>0</th>
      <td>2</td>
      <td>1</td>
      <td>2</td>
      <td>2</td>
      <td>2</td>
      <td>3</td>
      <td>1</td>
      <td>1</td>
      <td>2</td>
      <td>1</td>
      <td>...</td>
      <td>2</td>
      <td>3</td>
      <td>1</td>
      <td>2</td>
      <td>3</td>
      <td>2</td>
      <td>2</td>
      <td>2</td>
      <td>5</td>
      <td>2</td>
    </tr>
    <tr>
      <th>1</th>
      <td>1</td>
      <td>1</td>
      <td>3</td>
      <td>2</td>
      <td>2</td>
      <td>2</td>
      <td>2</td>
      <td>5</td>
      <td>2</td>
      <td>2</td>
      <td>...</td>
      <td>4</td>
      <td>3</td>
      <td>2</td>
      <td>2</td>
      <td>3</td>
      <td>4</td>
      <td>4</td>
      <td>4</td>
      <td>2</td>
      <td>2</td>
    </tr>
    <tr>
      <th>2</th>
      <td>2</td>
      <td>3</td>
      <td>2</td>
      <td>4</td>
      <td>1</td>
      <td>2</td>
      <td>2</td>
      <td>2</td>
      <td>2</td>
      <td>3</td>
      <td>...</td>
      <td>2</td>
      <td>3</td>
      <td>2</td>
      <td>3</td>
      <td>1</td>
      <td>4</td>
      <td>3</td>
      <td>2</td>
      <td>2</td>
      <td>4</td>
    </tr>
    <tr>
      <th>3</th>
      <td>3</td>
      <td>1</td>
      <td>4</td>
      <td>3</td>
      <td>3</td>
      <td>4</td>
      <td>2</td>
      <td>2</td>
      <td>4</td>
      <td>2</td>
      <td>...</td>
      <td>3</td>
      <td>3</td>
      <td>2</td>
      <td>4</td>
      <td>2</td>
      <td>4</td>
      <td>4</td>
      <td>4</td>
      <td>3</td>
      <td>5</td>
    </tr>
    <tr>
      <th>4</th>
      <td>2</td>
      <td>1</td>
      <td>2</td>
      <td>2</td>
      <td>3</td>
      <td>3</td>
      <td>2</td>
      <td>4</td>
      <td>2</td>
      <td>2</td>
      <td>...</td>
      <td>2</td>
      <td>2</td>
      <td>2</td>
      <td>3</td>
      <td>3</td>
      <td>4</td>
      <td>2</td>
      <td>4</td>
      <td>4</td>
      <td>3</td>
    </tr>
  </tbody>
</table>
<p>5 rows × 23 columns</p>
</div>

```
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.

<div>

<table border="1" class="dataframe">
  <thead>
    <tr style="text-align: right;">
      <th></th>
      <th>Item</th>
      <th>Scale Mean if Item Deleted</th>
      <th>Scale Variance if Item Deleted</th>
      <th>Corrected Item-Total Correlation</th>
      <th>Cronbach's Alpha if Item Deleted</th>
    </tr>
  </thead>
  <tbody>
    <tr>
      <th>0</th>
      <td>q1</td>
      <td>59.892260</td>
      <td>90.121072</td>
      <td>0.520928</td>
      <td>0.791887</td>
    </tr>
    <tr>
      <th>1</th>
      <td>q2</td>
      <td>60.642940</td>
      <td>101.063899</td>
      <td>-0.163158</td>
      <td>0.819978</td>
    </tr>
    <tr>
      <th>2</th>
      <td>q4</td>
      <td>59.480358</td>
      <td>87.967999</td>
      <td>0.569241</td>
      <td>0.788177</td>
    </tr>
    <tr>
      <th>3</th>
      <td>q5</td>
      <td>59.544146</td>
      <td>89.303401</td>
      <td>0.480579</td>
      <td>0.792419</td>
    </tr>
    <tr>
      <th>4</th>
      <td>q6</td>
      <td>60.039284</td>
      <td>87.605071</td>
      <td>0.482416</td>
      <td>0.791397</td>
    </tr>
    <tr>
      <th>5</th>
      <td>q7</td>
      <td>59.342668</td>
      <td>85.655685</td>
      <td>0.594245</td>
      <td>0.785032</td>
    </tr>
    <tr>
      <th>6</th>
      <td>q8</td>
      <td>60.029560</td>
      <td>89.900293</td>
      <td>0.503704</td>
      <td>0.792141</td>
    </tr>
    <tr>
      <th>7</th>
      <td>q9</td>
      <td>59.420070</td>
      <td>100.881838</td>
      <td>-0.137191</td>
      <td>0.828613</td>
    </tr>
    <tr>
      <th>8</th>
      <td>q10</td>
      <td>59.985609</td>
      <td>92.232867</td>
      <td>0.355784</td>
      <td>0.798693</td>
    </tr>
    <tr>
      <th>9</th>
      <td>q11</td>
      <td>60.011280</td>
      <td>88.790145</td>
      <td>0.568318</td>
      <td>0.789112</td>
    </tr>
    <tr>
      <th>10</th>
      <td>q12</td>
      <td>59.106962</td>
      <td>88.451979</td>
      <td>0.562942</td>
      <td>0.788889</td>
    </tr>
    <tr>
      <th>11</th>
      <td>q13</td>
      <td>59.817192</td>
      <td>87.839720</td>
      <td>0.576902</td>
      <td>0.787798</td>
    </tr>
    <tr>
      <th>12</th>
      <td>q14</td>
      <td>59.390121</td>
      <td>87.491716</td>
      <td>0.562476</td>
      <td>0.787931</td>
    </tr>
    <tr>
      <th>13</th>
      <td>q15</td>
      <td>59.500194</td>
      <td>88.766051</td>
      <td>0.484296</td>
      <td>0.791916</td>
    </tr>
    <tr>
      <th>14</th>
      <td>q16</td>
      <td>59.387009</td>
      <td>88.329154</td>
      <td>0.570772</td>
      <td>0.788520</td>
    </tr>
    <tr>
      <th>15</th>
      <td>q17</td>
      <td>59.799689</td>
      <td>88.441961</td>
      <td>0.587849</td>
      <td>0.788165</td>
    </tr>
    <tr>
      <th>16</th>
      <td>q18</td>
      <td>59.697783</td>
      <td>85.993065</td>
      <td>0.608925</td>
      <td>0.784771</td>
    </tr>
    <tr>
      <th>17</th>
      <td>q19</td>
      <td>59.974329</td>
      <td>104.442142</td>
      <td>-0.295795</td>
      <td>0.832243</td>
    </tr>
    <tr>
      <th>18</th>
      <td>q20</td>
      <td>58.642163</td>
      <td>91.699140</td>
      <td>0.313782</td>
      <td>0.800711</td>
    </tr>
    <tr>
      <th>19</th>
      <td>q21</td>
      <td>59.095683</td>
      <td>87.678779</td>
      <td>0.561128</td>
      <td>0.788157</td>
    </tr>
    <tr>
      <th>20</th>
      <td>q22</td>
      <td>59.378452</td>
      <td>101.109248</td>
      <td>-0.152704</td>
      <td>0.823798</td>
    </tr>
    <tr>
      <th>21</th>
      <td>q23</td>
      <td>58.831972</td>
      <td>98.820783</td>
      <td>-0.044039</td>
      <td>0.818680</td>
    </tr>
    <tr>
      <th>22</th>
      <td>q3r</td>
      <td>58.851809</td>
      <td>89.021221</td>
      <td>0.434762</td>
      <td>0.794258</td>
    </tr>
  </tbody>
</table>
</div>


