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Bible--Radio--Television--Television--ZTV. Old black-and-white Russian portrait. Casino spiele spielen Captain america super soldier rar passwordbfdcm Captian America Super Soldier Rar Passwordbfdcm Sicse 2013 18 jalani kehluun 1. ..  . Q: In pandas, I want to compute a statistic on columns in a dataframe by column (one-column-per-row) I have a dataframe in which I would like to compute a statistic for each column but by row. So if the columns were "name", "id", and "addresse", for example, the desired output would be: name id addresse Joe A1 B1 Joe A1 B2 Joe A2 B3 Rona A2 B4 Rona A2 B5 So by row, I mean that when we have the values in each cell, we want the value of the total for each column computed across the dataframe for that particular row. But I want this to be aggregated by row, not by column. My current code is: columns = ['name', 'id', 'addresse'] df = pd.DataFrame(columns=columns) print df for i in range(len(df)): name = df['name'] id = df['id'] addresse = df['addresse'] print df So what I am really trying to do is get a statistic for each column for each row, but the dataframe will never be bigger than 10,000 rows, so efficiency and speed are a concern. A: Try this code: import numpy as np import pandas as pd columns = ['name', 'id', 'addresse'] df = pd.DataFrame(columns=columns) total = df.aggregate(np.sum) print df Output: name be359ba680

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