How to convert duplicate keys containing multiple list to a dataframe in Python?

user_3971643 0
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My dictionary looks like below. From below dictionary one can see that the key "Column A" contains Multiple values 1,2,3. I would to convert below dictionary to pandas dataframe such that there is duplicate values for Column A. Below is my expected output. I tried using pandas function pd.Dataframe. However, receieved and error that says "ValueError: arrays must all be same length". Please advice how to proceed with dataframe creation.

Thanks in advance for your time!

My Dictionary

my_dict={"Column A":[1,2,3],"ABC":456,"CDE":[12,11]}

Expected Output:

Column A       1
Column A       2
Column A       3
ABC            456
CDE            12
CDE            11
pandas dataframe dictionary python
3 Answers

Try:

my_dict = {"Column A": [1, 2, 3], "ABC": 456, "CDE": [12, 11]}

df = pd.DataFrame({"col1": my_dict.keys(), "col2": my_dict.values()})
df = df.explode("col2")
print(df)

Prints:

       col1 col2
0  Column A    1
0  Column A    2
0  Column A    3
1       ABC  456
2       CDE   12
2       CDE   11
user_100359850

Following the question in the comments: In DataFrames and Series, index is always there.

if you want, you can set one of your columns as index, or you can reset it, but it is impossible to remove it. if you want to set col1 as your index, try:

df.set_index('col1')
user_169321720

Try:

code

df = pd.DataFrame(dict([(k,pd.Series(v)) for k,v in my_dict.items()])
                  ).T.stack().reset_index().drop(columns = ['level_1'])

result

    level_0      0
0  Column A    1.0
1  Column A    2.0
2  Column A    3.0
3       ABC  456.0
4       CDE   12.0
5       CDE   11.0
user_117025910
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