Update gen_readme.yml

.github/workflows/gen_readme.yml

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 on:
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     branches:
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+      - run_readme
     # - cron: "40 15 * * 1,3,5"
 
 jobs:
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           git config --local user.email "actions@github.com"
           git add -A
           git commit -m "Update Readme"
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         env:
           REPO_KEY: ${{ secrets.GITHUB_TOKEN }}
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README.md

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+# Difference in Difference in Python
+
+
+The **csdid** package contains tools for computing average treatment
+effect parameters in a Difference-in-Differences setup allowing for
+
+- More than two time periods
+
+- Variation in treatment timing (i.e., units can become treated at
+  different points in time)
+
+- Treatment effect heterogeneity (i.e, the effect of participating in
+  the treatment can vary across units and exhibit potentially complex
+  dynamics, selection into treatment, or time effects)
+
+- The parallel trends assumption holds only after conditioning on
+  covariates
+
+The main parameters are **group-time average treatment effects**. These
+are the average treatment effect for a particular group (group is
+defined by treatment timing) in a particular time period. These
+parameters are a natural generalization of the average treatment effect
+on the treated (ATT) which is identified in the textbook case with two
+periods and two groups to the case with multiple periods.
+
+Group-time average treatment effects are also natural building blocks
+for more aggregated treatment effect parameters such as overall
+treatment effects or event-study-type estimands.
+
+## Getting Started
+
+There has been some recent work on DiD with multiple time periods. The
+**did** package implements the framework put forward in
+
+- [Callaway, Brantly and Pedro H.C. Sant’Anna.
+  “Difference-in-Differences with Multiple Time Periods.” Journal of
+  Econometrics, Vol. 225, No. 2, pp. 200-230,
+  2021.](https://doi.org/10.1016/j.jeconom.2020.12.001) or
+  \[arXiv\](https://arxiv.org/abs/1803.09015
+
+This project is based on the original [did R
+package](https://github.com/bcallaway11/did).
+
+## Instalation
+
+You can install **csdid** from `pypi` with:
+
+    pip install csdid
+
+or via github:
+
+    pip install git+https://github.com/d2cml-ai/csdid/
+
+### Dependencies
+
+Additionally, I have created an additional library called `drdid`, which
+can be installed via GitHub.
+
+    pip install git+https://github.com/d2cml-ai/DRDID
+
+## Basic Example
+
+The following is a simplified example of the effect of states increasing
+their minimum wages on county-level teen employment rates which comes
+from [Callaway and Sant’Anna
+(2021)](https://authors.elsevier.com/a/1cFzc15Dji4pnC).
+
+- [More detailed examples are also
+  available](https://bcallaway11.github.io/did/articles/did-basics.html)
+
+A subset of the data is available in the package and can be loaded by
+
+``` python
+from csdid.att_gt import ATTgt
+import pandas as pd
+data = pd.read_csv("https://raw.githubusercontent.com/d2cml-ai/csdid/function-aggte/data/mpdta.csv")
+```
+
+The dataset contains 500 observations of county-level teen employment
+rates from 2003-2007. Some states are first treated in 2004, some in
+2006, and some in 2007 (see the paper for more details). The important
+variables in the dataset are
+
+- **lemp** This is the log of county-level teen employment. It is the
+  outcome variable
+
+- **first.treat** This is the period when a state first increases its
+  minimum wage. It can be 2004, 2006, or 2007. It is the variable that
+  defines *group* in this application
+
+- **year** This is the year and is the *time* variable
+
+- **countyreal** This is an id number for each county and provides the
+  individual identifier in this panel data context
+
+To estimate group-time average treatment effects, use the
+**ATTgt().fit()** method
+
+``` python
+out = ATTgt(yname = "lemp",
+              gname = "first.treat",
+              idname = "countyreal",
+              tname = "year",
+              xformla = f"lemp~1",
+              data = data,
+              ).fit(est_method = 'dr')
+```
+
+Summary table
+
+``` python
+out.summ_attgt().summary2
+```
+
+<div>
+<style scoped>
+    .dataframe tbody tr th:only-of-type {
+        vertical-align: middle;
+    }
+&#10;    .dataframe tbody tr th {
+        vertical-align: top;
+    }
+&#10;    .dataframe thead th {
+        text-align: right;
+    }
+</style>
+
+|     | Group | Time | ATT(g, t) | Post | Std. Error | \[95% Pointwise | Conf. Band\] |     |
+|-----|-------|------|-----------|------|------------|-----------------|--------------|-----|
+| 0   | 2004  | 2004 | -0.0105   | 0    | 0.0244     | -0.0758         | 0.0548       |     |
+| 1   | 2004  | 2005 | -0.0704   | 0    | 0.0327     | -0.1581         | 0.0173       |     |
+| 2   | 2004  | 2006 | -0.1373   | 0    | 0.0368     | -0.2359         | -0.0386      | \*  |
+| 3   | 2004  | 2007 | -0.1008   | 0    | 0.0361     | -0.1975         | -0.0041      | \*  |
+| 4   | 2006  | 2004 | 0.0065    | 0    | 0.0235     | -0.0565         | 0.0696       |     |
+| 5   | 2006  | 2005 | -0.0028   | 0    | 0.0200     | -0.0565         | 0.0510       |     |
+| 6   | 2006  | 2006 | -0.0046   | 0    | 0.0180     | -0.0528         | 0.0436       |     |
+| 7   | 2006  | 2007 | -0.0412   | 0    | 0.0198     | -0.0943         | 0.0118       |     |
+| 8   | 2007  | 2004 | 0.0305    | 0    | 0.0153     | -0.0105         | 0.0715       |     |
+| 9   | 2007  | 2005 | -0.0027   | 0    | 0.0164     | -0.0467         | 0.0413       |     |
+| 10  | 2007  | 2006 | -0.0311   | 0    | 0.0174     | -0.0777         | 0.0155       |     |
+| 11  | 2007  | 2007 | -0.0261   | 0    | 0.0182     | -0.0747         | 0.0226       |     |
+
+</div>
+
+In the graphs, a semicolon `;` should be added to prevent printing the
+class and the graph information.
+
+``` python
+out.plot_attgt();
+```
+
+    /home/runner/work/csdid/csdid/csdid/plots/gplot.py:19: FutureWarning: Setting an item of incompatible dtype is deprecated and will raise in a future error of pandas. Value '['2004' '2005' '2006' '2007']' has dtype incompatible with int64, please explicitly cast to a compatible dtype first.
+      ssresults.loc[:, 'year'] = ssresults['year'].astype(int).astype(str)
+    /home/runner/work/csdid/csdid/csdid/plots/gplot.py:19: FutureWarning: Setting an item of incompatible dtype is deprecated and will raise in a future error of pandas. Value '['2004' '2005' '2006' '2007']' has dtype incompatible with int64, please explicitly cast to a compatible dtype first.
+      ssresults.loc[:, 'year'] = ssresults['year'].astype(int).astype(str)
+    /home/runner/work/csdid/csdid/csdid/plots/gplot.py:19: FutureWarning: Setting an item of incompatible dtype is deprecated and will raise in a future error of pandas. Value '['2004' '2005' '2006' '2007']' has dtype incompatible with int64, please explicitly cast to a compatible dtype first.
+      ssresults.loc[:, 'year'] = ssresults['year'].astype(int).astype(str)
+
+![](README_files/figure-commonmark/cell-5-output-2.png)
+
+``` python
+out.aggte(typec='calendar');
+```
+
+
+
+    Overall summary of ATT's based on calendar time aggregation:
+        ATT Std. Error  [95.0%  Conf. Int.]  
+    -0.0417      0.017 -0.0751      -0.0083 *
+
+
+    Time Effects (calendar):
+       Time  Estimate  Std. Error  [95.0% Simult.   Conf. Band   
+    0  2004   -0.0105      0.0250          -0.0596      0.0386   
+    1  2005   -0.0704      0.0332          -0.1354     -0.0054  *
+    2  2006   -0.0488      0.0211          -0.0902     -0.0074  *
+    3  2007   -0.0371      0.0147          -0.0659     -0.0082  *
+    ---
+    Signif. codes: `*' confidence band does not cover 0
+    Control Group:  Never Treated , 
+    Anticipation Periods:  0
+    Estimation Method:  Doubly Robust
+
+``` python
+out.plot_aggte();
+```
+
+    /home/runner/work/csdid/csdid/csdid/plots/gplot.py:19: FutureWarning: Setting an item of incompatible dtype is deprecated and will raise in a future error of pandas. Value '['2004' '2005' '2006' '2007']' has dtype incompatible with int64, please explicitly cast to a compatible dtype first.
+      ssresults.loc[:, 'year'] = ssresults['year'].astype(int).astype(str)
+
+![](README_files/figure-commonmark/cell-7-output-2.png)