I saved the dictionary dict dict_keys(['df1', 'df2']) into a csv file. cat data.csv outputs something like this?
,,df1,df2
quantile_10,h0,0.03636844456195831,0.105098
quantile_10,h5,0.0654495671391487,0.108322
quantile_10,h10,0.10933497846126557,0.113496
quantile_10,h15,0.1400846481323242,0.119098
quantile_10,h20,0.1513956755399704,0.068324
quantile_10,h25,0.11640003025531769,0.017974
quantile_10,h30,0.026758757233619694,9.4e-05
quantile_10,h35,0.0020915842149406673,0.0
quantile_20,h0,0.05211468040943147,0.130436
quantile_20,h5,0.08270514607429505,0.125416
quantile_20,h10,0.12569279968738556,0.125436
quantile_20,h15,0.14520362317562102,0.149596
How to open this dictionary in python so I have a dict['df1'], dict['df2'] and quantiles being row indexes?
>Solution :
You can use the pandas library to read this CSV file and reconstruct the original dictionary.
- Read the csv with the first two columns set as the index
- Convert the DataFrame to a dictionary where keys are column names (
df1,df2, etc.) and values are DataFrames with the multi-index intact.
import pandas as pd
# Read the CSV with the first two columns as index
df = pd.read_csv('data.csv', index_col=[0, 1])
# Extract each 'df' as a transposed DataFrame and store in a dictionary
data_dict = {col: df[[col]].unstack().T for col in df.columns}
# Access the data
print(data_dict['df1'].columns)