Create a list with your dictionaries, if they are needed, and then create a new dataframe with df = pd.DataFrame.from_records(your_list). List’s “append” method are very efficient and won’t be ever deprecated. Dataframes on the other hand, frequently have to be recreated and all data copied over on appends, due to their design – that is … Read more
There’s also the embedded formatting parameter: skipinitialspace (the default is false) http://docs.python.org/2/library/csv.html#csv-fmt-params aList=[] with open(self.filename, ‘r’) as f: reader = csv.reader(f, skipinitialspace=False,delimiter=”,”, quoting=csv.QUOTE_NONE) for row in reader: aList.append(row) return(aList)
I think in this case concat is what you want: In [12]: pd.concat([df,df1], axis=0, ignore_index=True) Out[12]: attr_1 attr_2 attr_3 id quantity 0 0 1 NaN 1 20 1 1 1 NaN 2 23 2 1 1 NaN 3 19 3 0 0 NaN 4 19 4 1 NaN 0 5 8 5 0 NaN 1 … Read more
It appears that the Excel “serial date” format is actually the number of days since 1900-01-00, with a fractional component that’s a fraction of a day, based on http://www.cpearson.com/excel/datetime.htm. (I guess that date should actually be considered 1899-12-31, since there’s no such thing as a 0th day of a month) So, it seems like it … Read more