Taking a list of data frames and grouping by a variable and using that variable as the key to a dictionary

问题

I am relatively new to python programming. I have a list of pandas dataframes that all have the column 'Year'. I am trying to group by that column and convert to a dictionary where the dictionary key is the variable 'Year' and values is a list of dataframes of that year. Is this possible in python?

I tried this:

grouped_dict = list_of_csv_files.groupby(by = 'Year').to_dict()

I believe I will have to loop through each dataframe? I did not provide any data because I am hoping it is a somewhat simple solution.

I also tried this:

grouped_dict = list_of_csv_files.groupby(by = 'Year').apply(lambda dfg: dfg.to_dict(orient='list')).to_dict()

Any guidance would be greatly appreciated!

回答1:

Other answers have missed the mark so far, so I'll give you an alternative. Assuming you have CSV files (since your variable is named that way):

from collections import defaultdict

yearly_dfs = defaultdict(list)
for csv in list_of_csv_files:
    df = pd.read_csv(csv)
    for yr, yr_df in df.groupby("Year"):
        yearly_dfs[yr].append(yr_df)

Assuming you have DataFrames already:

from collections import defaultdict

yearly_dfs = defaultdict(list)
for df in list_of_csv_files:
    for yr, yr_df in df.groupby("Year"):
        yearly_dfs[yr].append(yr_df)

回答2:

Firstly you should read the files into a single dataframe: list_of_dfs = [pd.read_csv(filename, index_col=False) for filename in list_of_csv_files] df = pd.concat(list_of_dfs, sort=True)

Then apply the groupby transformation on the dataframe and convert it into a dictionary: grouped_dict = df.groupby('Year').apply(list).to_dict()

This question is a duplicate of GroupBy results to dictionary of lists

来源：https://stackoverflow.com/questions/55692550/taking-a-list-of-data-frames-and-grouping-by-a-variable-and-using-that-variable