Remove mention to RDataFrame functions removed in v6.30

See also root-project/root#11994.

Author: jalopezg-git

manual/data_frame/index.md

@@ -20,7 +20,7 @@ RDataFrame provides the necessary methods to perform all operations required by
 
 Every RDataFrame program follows this workflow:
 
-1. Construct a dataframe object by specifying a dataset. RDataFrame supports single TTrees as well as multiple TTrees (i.e., {% include ref class="TChain" %}), [CSV files](https://root.cern/doc/master/df014__CSVDataSource_8C.html), [SQLite files](https://root.cern/doc/master/df027__SQliteDependencyOverVersion_8C.html), [RNTuples](https://root.cern/doc/master/structROOT_1_1Experimental_1_1RNTuple.html), and it can be extended to custom data formats. From Python, [NumPy arrays can be imported into RDataFrame](https://root.cern/doc/master/df032__MakeNumpyDataFrame_8py.html) as well.
+1. Construct a dataframe object by specifying a dataset. RDataFrame supports single TTrees as well as multiple TTrees (i.e., {% include ref class="TChain" %}), [CSV files](https://root.cern/doc/master/df014__CSVDataSource_8C.html), [SQLite files](https://root.cern/doc/master/df027__SQliteDependencyOverVersion_8C.html), [RNTuples](https://root.cern/doc/master/structROOT_1_1Experimental_1_1RNTuple.html), and it can be extended to custom data formats. From Python, [NumPy arrays can be imported into RDataFrame](https://root.cern/doc/master/df032__RDFFromNumpy_8py.html) as well.
 
 2. Transform the dataframe by:
 

manual/root_files/index.md

@@ -214,7 +214,7 @@ h.Draw()
 Besides ROOT files, RDataFrame can also read from other data sources, for example CSV files:
 
 {% highlight C++ %}
-auto rdf = ROOT::RDF::MakeCsvDataFrame("myfile.csv");
+auto rdf = ROOT::RDF::FromCSV("myfile.csv");
 auto h = rdf.Histo1D("x");
 h->Draw();
 {% endhighlight %}

primer/index.md

@@ -2071,7 +2071,7 @@ cited:
 
 Every RDataFrame program follows this workflow:
 
-1. Construct a dataframe object by specifying a dataset. RDataFrame supports single TTrees as well as multiple TTrees (i.e., {% include ref class="TChain" %}), [CSV files](https://root.cern/doc/master/df014__CSVDataSource_8C.html), [SQLite files](https://root.cern/doc/master/df027__SQliteDependencyOverVersion_8C.html), [RNTuples](https://root.cern/doc/master/structROOT_1_1Experimental_1_1RNTuple.html), and it can be extended to custom data formats. From Python, [NumPy arrays can be imported into RDataFrame](https://root.cern/doc/master/df032__MakeNumpyDataFrame_8py.html) as well.
+1. Construct a dataframe object by specifying a dataset. RDataFrame supports single TTrees as well as multiple TTrees (i.e., {% include ref class="TChain" %}), [CSV files](https://root.cern/doc/master/df014__CSVDataSource_8C.html), [SQLite files](https://root.cern/doc/master/df027__SQliteDependencyOverVersion_8C.html), [RNTuples](https://root.cern/doc/master/structROOT_1_1Experimental_1_1RNTuple.html), and it can be extended to custom data formats. From Python, [NumPy arrays can be imported into RDataFrame](https://root.cern/doc/master/df032__RDFFromNumpy_8py.html) as well.
 
 2. Transform the dataframe by: