How to convert two pandas columns into a dictionary, but merge all values of same first column (key) into one key?

Question

Sorry for the confusing title, basically I have a Pandas dataframe and I want to convert two columns into a dictionary (with one being the key and the other the value). However, when I use to_dict(), the problem is that since I have many rows in the first column that have the same value, it only takes one of them and I don't get all the data. Is there a way to work around this?

I have tried solving this recursively but I haven't been able to figure it out.

EDIT: added code

data = pd.read_csv('file')
datalist = []
data2list = []


for i in range(len(data.index)):
    datalist.append(data.loc[i, 'column1'])

for i in range(len(data.index)):
        data2list.append(data.loc[i, 'column2'])

Now datalist has all the values from column1, which I want to be the keys, and column2 has all the values that I want to be the values in the dictionary.

The problem however is, the dataframe looks kind of like this:

   column1   column2
0  key1      value1
1  key1      value2
2  key2      value3
3  key2      value4

I want the dictionary to look like this:

dict = {"key1": [value1, value2], "key2": [value3, value4]}

Answer 1

Python dictionaries do not support repeated keys. You could solve this by adjusting the values in your first column so that the keys are not repeated. Alternatively, you could create a dictionary of lists for each unique key in the first column. Since your data is in a Pandas DataFrame, you could do:

import pandas as pd

# Your data
data = pd.DataFrame({'column1':['key1','key1','key2','key2'],
       'column2':['value1','value2','value3','value3']})

# Grouped dict
data_dict = data.groupby('column1').column2.apply(list).to_dict()