Split cell into multiple rows in pandas dataframe
I have a dataframe contains orders data, each order has multiple packages stored as comma separated string [package & package_code] columns
pandas
pandas: filter rows of DataFrame with operator chaining
Most operations in pandas can be accomplished with operator chaining (groupby, aggregate, apply, etc), but the only way I’ve found to filter rows is via normal bracket indexing
Creating dataframe from a dictionary where entries have different lengths
Say I have a dictionary with 10 key-value pairs. Each entry holds a numpy array. However, the length of the array is not the same for all of them.
Pandas long to wide reshape, by two variables
I have data in long format and am trying to reshape to wide, but there doesn’t seem to be a straightforward way to do this using melt/stack/unstack:
Pandas DataFrame to List of Lists
It’s easy to turn a list of lists into a pandas dataframe:
pandas: multiple conditions while indexing data frame – unexpected behavior
I am filtering rows in a dataframe by values in two columns.
What is the difference between NaN and None?
I am reading two columns of a csv file using pandas readcsv() and then assigning the values to a dictionary. The columns contain strings of numbers and letters. Occasionally there are cases where a cell is empty. In my opinion, the value read to that dictionary entry should be None but instead nan is assigned. Surely None is more descriptive of an empty cell as it has a null value, whereas nan just says that the value read is not a number.
Pandas read in table without headers
How can I read in a .csv file (with no headers) and when I only want a subset of the columns (say 4th and 7th out of a total of 20 columns), using pandas? I cannot seem to be able to do usecols
How to have clusters of stacked bars with python (Pandas)
So here is how my data set looks like :
How to print pandas DataFrame without index
I want to print the whole dataframe, but I don’t want to print the index