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POPython Pandas - returning results of groupby function back to parent table
 

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  1. POPython Pandas - returning results of groupby function back to parent table
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    <p>[Using Python3] I'm using pandas to read a csv file, group the dataframe, apply a function to the grouped data and add these results back to the original dataframe.</p> <p>My input looks like this:</p> <pre><code>email cc timebucket total_value john@john.com us 1 110.50 example@example.com uk 3 208.84 ... ... ... ... </code></pre> <p>Basically I'm trying to group by <code>cc</code> and calculate the percentile rank for each value in <code>total_value</code> within that group. Secondly I want to apply a flow statement to these results. I need these results to be added back to the original/parent DataFrame. Such that it would look something like this:</p> <pre><code>email cc timebucket total_value percentrank rankbucket john@john.com us 1 110.50 48.59 mid50 example@example.com uk 3 208.84 99.24 top25 ... ... ... ... ... ... </code></pre> <p>The code below gives me an <code>AssertionError</code> and I cannot figure out why. I'm very new to Python and pandas, so that might explain one and another.</p> <p>Code:</p> <pre><code>import pandas as pd import numpy as np from scipy.stats import rankdata def percentilerank(frame, groupkey='cc', rankkey='total_value'): from pandas.compat.scipy import percentileofscore # Technically the below percentileofscore function should do the trick but I cannot # get that to work, hence the alternative below. It would be great if the answer would # include both so that I can understand why one works and the other doesnt. # func = lambda x, score: percentileofscore(x[rankkey], score, kind='mean') func = lambda x: (rankdata(x.total_value)-1)/(len(x.total_value)-1)*100 frame['percentrank'] = frame.groupby(groupkey).transform(func) def calc_and_write(filename): """ Function reads the file (must be tab-separated) and stores in a pandas DataFrame. Next, the percentile rank score based is calculated based on total_value and is done so within a country. Secondly, based on the percentile rank score (prs) a row is assigned to one of three buckets: rankbucket = 'top25' if prs &gt; 75 rankbucket = 'mid50' if 25 &gt; prs &lt; 75 rankbucket = 'bottom25' if prs &lt; 25 """ # Define headers for pandas to read in DataFrame, stored in a list headers = [ 'email', # 0 'cc', # 1 'last_trans_date', # 3 'timebucket', # 4 'total_value', # 5 ] # Reading csv file in chunks and creating an iterator (is supposed to be much faster than reading at once) tp = pd.read_csv(filename, delimiter='\t', names=headers, iterator=True, chunksize=50000) # Concatenating the chunks and sorting total DataFrame by booker_cc and total_nett_spend df = pd.concat(tp, ignore_index=True).sort(['cc', 'total_value'], ascending=False) percentilerank(df) </code></pre> <p>Edit: As requested, this is the traceback log:</p> <pre><code>Traceback (most recent call last): File "C:\Users\m\Documents\Python\filter_n_split_3.py", line 85, in &lt;module&gt; print(calc_and_write('tsv/test.tsv')) File "C:\Users\m\Documents\Python\filter_n_split_3.py", line 74, in calc_and_write percentilerank(df) File "C:\Users\m\Documents\Python\filter_n_split_3.py", line 33, in percentilerank frame['percentrank'] = frame.groupby(groupkey).transform(func) File "C:\Python33\lib\site-packages\pandas\core\groupby.py", line 1844, in transform axis=self.axis, verify_integrity=False) File "C:\Python33\lib\site-packages\pandas\tools\merge.py", line 894, in concat verify_integrity=verify_integrity) File "C:\Python33\lib\site-packages\pandas\tools\merge.py", line 964, in __init__ self.new_axes = self._get_new_axes() File "C:\Python33\lib\site-packages\pandas\tools\merge.py", line 1124, in _get_new_axes assert(len(self.join_axes) == ndim - 1) AssertionError </code></pre>
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    1. USMatthijs
    1. USMatthijs
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    1. COWhat AssertionError? Can you include the entire stacktrace (including the line number, and which line this corresponds to in your code)?
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      1. POPython Pandas - returning results of groupby function back to parent table
      1. USAndy Hayden
    2. COHi Andy, I've added the Traceback log, hope this makes more sense.
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      1. POPython Pandas - returning results of groupby function back to parent table
      1. USMatthijs
    3. COSo it stems from `frame.groupby(groupkey).transform(func)`...
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      1. POPython Pandas - returning results of groupby function back to parent table
      1. USAndy Hayden
 

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