python – Using pandas structures with large csv(iterate and chunksize)
I have a large csv file, about 600mb with 11 million rows and I want to create statistical data like pivots, histograms, graphs etc. Obviously trying to just to read it normally:
dataframe
Add column to dataframe with constant value
I have an existing dataframe which I need to add an additional column to which will contain the same value for every row.
Rename specific column(s) in pandas
I’ve got a dataframe called data. How would I rename the only one column header? For example gdp to log(gdp)?
Concatenate a list of pandas dataframes together
I have a list of Pandas dataframes that I would like to combine into one Pandas dataframe. I am using Python 2.7.10 and Pandas 0.16.2
Drop rows containing empty cells from a pandas DataFrame
I have a pd.DataFrame that was created by parsing some excel spreadsheets. A column of which has empty cells. For example, below is the output for the frequency of that column, 32320 records have missing values for Tenant.
Python pandas: how to specify data types when reading an Excel file?
I am importing an excel file into a pandas dataframe with the pandas.read_excel() function.
Convert row to column header for Pandas DataFrame,
The data I have to work with is a bit messy.. It has header names inside of its data. How can I choose a row from an existing pandas dataframe and make it (rename it to) a column header?
Nested dictionary to multiindex dataframe where dictionary keys are column labels
Say I have a dictionary that looks like this:
Selection with .loc in python
I saw this code in someone’s iPython notebook, and I’m very confused as to how this code works. As far as I understood, pd.loc[] is used as a location based indexer where the format is:
Running get_dummies on several DataFrame columns?
How can one idiomatically run a function like get_dummies, which expects a single column and returns several, on multiple DataFrame columns?