CODEWITHSUNDEEP
pythonpandascsv
Tony
Tony

Reputation: 793

Pandas DataFrame to 'traditional' file loading

I have a python script that initially loads a csv file:

data= []
with open('data.csv', 'r') as f:
    for line in f.readlines()[1:]:
        data.append(re.split(r',',line.rstrip()))

But now I am dynamically generating the contents of this csv within python in what results to be a pandas DataFrame. My question is what is the most efficient way to get the data to the desired format (list of lists).

An obvious way would be to save the dataframe to a csv and then load it back as above, and another one to convert directly somehow. Is the approach below the way to go?

data = df.values.tolist()

Upvotes: 0

Views: 31

Answers (1)

Mohamed Ali JAMAOUI
Mohamed Ali JAMAOUI

Reputation: 14699

As you suggested, if you have a pandas dataframe df, you can use df.values.tolist() to get a list of lists of the values.

Here's an example: 

>>> import pandas as pd  
>>> df = pd.DataFrame([[1,2],[3,4],[5,6]]) 
>>> df.values 
array([[1, 2],
       [3, 4],
       [5, 6]])
>>> df.values.tolist() 
[[1, 2], [3, 4], [5, 6]]
>>>

Upvotes: 1

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