update readme

README.md

@@ -19,12 +19,14 @@ A best-practice setup includes initialising git and creating a virtual environme
 - install kedro `pip install kedro`
 - Install the packages and libraries `pip install -r src/requirements.txt`
 
-Then open a terminal in the `actes-princiers` folder 
+Then open a terminal in the `actes-princiers`'s folder 
 and launch jupyter : `kedro jupyter notebook` 
 or start the ipython prompt : `kedro ipython`
 
 ## Launching the pipeline
 
+Open a terminal in the `actes-princiers`'s folder and launch kedro
+
 `kedro run`
 
 ## Visualizing the pipelines

actes-princiers/src/actes_princiers/pipelines/data_processing/nodes.py

@@ -1,16 +1,17 @@
 import pandas as pd
 import numpy as np
 
-def _is_true(x: pd.Series) -> pd.Series:
-    return x == "t"
+#def _is_true(x: pd.Series) -> pd.Series:
+#    return x == "t"
 
-def _parse_percentage(x: pd.Series) -> pd.Series:
-    x = x.str.replace("%", "")
-    x = x.astype(float) / 100
-    return x
+#def _parse_percentage(x: pd.Series) -> pd.Series:
+#    x = x.str.replace("%", "")
+#    x = x.astype(float) / 100
+#    return x
 
 def preprocess_actors(actors: pd.DataFrame) -> pd.DataFrame:
     actors.replace("XXXX", np.NaN)
     return actors
 
+#def parse_xsl(
 

actes-princiers/src/actes_princiers/pipelines/data_processing/pipeline.py

@@ -12,5 +12,11 @@ def create_pipeline(**kwargs) -> Pipeline:
                 outputs="preprocessed_actors",
                 name="preprocess_actors_node",
             ),
+#            node(
+#                func=parse_xsl,
+#                inputs="actors",
+#                outputs="preprocessed_actors",
+#                name="preprocess_actors_node",
+#            ),
         ]
     )