CODEWITHSUNDEEP
python-3.xpandascsvdictionarynested
Maybe
Maybe

Reputation: 83

How do I create a nested dictonary from a specific file?

I have a CSV file with rows ordered like this. CSV Image

Table in text

0 EST Monday Tuesday Wednesday
1 12:00AM Starting
2 7:00PM Prayer Game Night
3 8:00PM Board game Ask anything

I'm trying to create a nested Dictionary so that when someone asks for a Day (eg: Monday), all the events happening that day together with the time would be produced.

my_dict = {'Monday':{'EST':'7:30: PM', 'Event': 'Prayer Meeting', 'EST':'8:00: PM', 'Event': 'Board Game',}}

If a nested dictonary is not the right way, please guide me.

Upvotes: 1

Views: 52

Answers (1)

jezrael
jezrael

Reputation: 862841

when someone asks for a Day (eg: Monday), all the events happening that day together with the time would be produced.

I think then dictionary should looks different:

First use DataFrame.melt for unpivot and then remove rows with missing values by DataFrame.dropna, last use DataFrame.groupby in dict comprehension and create nested dictionaries:

df1 = df.melt('EST').dropna(subset=['value'])

d = {k: dict(zip(v['EST'], v['value'])) for k, v in df1.groupby('variable')}
print (d)
{'Monday': {'7:00PM': 'Prayer', '8:00PM': 'Board game'},
 'Tuesday': {'12:00AM': 'Starting', '8:00PM': 'Ask anything'},
 'Wednesday': {'7:00PM': 'Game Night'}}

Another alternative with different ouput - for each day are create lists of dictionaries - in dict comprehension is used DataFrame.to_dict:

df1 = df.melt('EST', value_name='event').dropna(subset=['event'])

d = {k: v[['EST','event']].to_dict(orient='records') for k, v in df1.groupby('variable')}
print (d)
{'Monday': [{'EST': '7:00PM', 'event': 'Prayer'}, 
            {'EST': '8:00PM', 'event': 'Board game'}], 
 'Tuesday': [{'EST': '12:00AM', 'event': 'Starting'}, 
             {'EST': '8:00PM', 'event': 'Ask anything'}], 
 'Wednesday': [{'EST': '7:00PM', 'event': 'Game Night'}]}

Upvotes: 2

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