Append dictionary to pandas dataframe in a loop

user_6664990 0
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I have a requirement to create a dictionary within a loop and append them to a pandas data frame with matching key name of dict and column name of data frame. The key value pairs of dictionary in each iteration could be different. An empty pandas data frame df_podcast have been defined at the beginning with all possible keys in the dictionary.

Below is the sample of a code which is not completed yet

df_podcast=pd.DataFrame(columns=podcast_cols)

podcast_dict={}
for j in range(len(podcast[0])):
    if podcast[0][j].tag=="key":
        podcast_dict[podcast[0][j].text]=podcast[0][j+1].text
### Have to append dict to pandas df ############

I have append podcast_dict to df_podcast. Podcast is actually a list of lists, here I'm just considering only 1st row of the list

pandas python-3.x python
3 Answers

You need:

df  = pd.DataFrame([podcast_dict], columns=podcast_dict.keys())
df_podcast = pd.concat([df_podcast, df], axis =0).reset_index()
user_72951570

If you want to simply append new data from a created dictionary within a loop to an existening Dataframe:

df = pd.DataFrame()
for i in range(n):
    dict_new = dict(i)
    df = df.append(dict_new, ignore_index=True)
print(df)

NOTE: As long as the keys in your created dictionary are the same, appending it to an existing dataframe shouldn't be cumbersome. Source

user_73338830
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