Merge pull request jma127#4 from stiebels/master

LETOR txt to pandas data frame converter

pyltr/data/pandas_converter.py

@@ -0,0 +1,72 @@
+import pandas as pd
+
+
+class Pandas_Converter(object):    
+    '''
+    Class Converter implements parsing from original letor txt files to
+    pandas data frame representation.
+    '''
+
+    def __init__(self, path):
+        '''
+        Arguments:
+            path: path to letor txt file
+        '''
+        self._path = path
+
+    @property
+    def path(self):
+        return self._path
+
+    @path.setter
+    def path(self, p):
+        self._path = p
+
+    def _load_file(self):
+        '''        
+        Loads and parses raw letor txt file.
+        
+        Return:
+            letor txt file parsed to csv in raw format
+        '''
+        return pd.read_csv(str(self._path), sep=" ", header=None)
+
+    def _drop_col(self, df):
+        '''
+        Drops last column, which was added in the parsing procedure due to a
+        trailing white space for each sample in the text file
+        
+        Arguments:
+            df: pandas dataframe
+        Return:
+            df: original df with last column dropped
+        '''
+        return df.drop(df.columns[-1], axis=1)
+
+    def _split_colon(self, df):
+        '''
+        Splits the data on the colon and transforms it into a tabular format
+        where columns are features and rows samples. Cells represent feature
+        values per sample.
+        
+        Arguments:
+            df: pandas dataframe object
+        Return:
+            df: original df with string pattern ':' removed; columns named appropriately
+        '''
+        for col in range(1,len(df.columns)):
+            df.loc[:,col] = df.loc[:,col].apply(lambda x: str(x).split(':')[1])
+        df.columns = ['rel', 'qid'] + [str(x) for x in range(1,len(df.columns)-1)] # renaming cols
+        return df
+
+    def convert(self):
+        '''
+        Performs final conversion.
+        
+        Return:
+            fully converted pandas dataframe
+        '''
+        df_raw = self._load_file(self._path)
+        df_drop = self._drop_col(df_raw)
+        return self._split_colon(df_drop)
+