CODEWITHSUNDEEP
pythonpandaslistdataframe
kluster
kluster

Reputation: 95

How can I transform items from a list into separate column values?

I am working on creating a dataframe in python, and I am struggling on how to proceed with this problem. I am trying to analyze skincare ingredients, and I want to create a dataframe that I can regularly update with new products.

The product ingredients are stored as list items.

In the end, the dataframe should look like this:

product 1 = [ingredient 1, ingredient 2, ingredient 3]

           ingredient 1  ingredient 2  ingredient 3  
product 1    XYZ             XYZ          XYZ  
product 2    XYZ             XYZ          XYZ   
product 3    XYZ             XYZ          XYZ

The XYZ values being the items from the lists that I use. How should I tackle this? It is also important to maintain the order of the items/ingredients, and to make sure they will correctly be assigned as ingredient 1 being the first item in the list, ingredient 2 being the second item in the list, etc..

I have only found solutions where items were transformed into a list of different observations, not into column values for one single observation.

Is there a function or a method I can use to solve this issue?

Upvotes: 0

Views: 100

Answers (1)

Anya Samadi
Anya Samadi

Reputation: 753

you can use panda data frame easily:

  my_data = np.array([['','ingredient1', 'ingredient2', 'ingredient3'],['product1', 45, 35, 25], ['product2', 44,34,24], ['product3', 43,33,23]])
my_data

which gives you:

array([['', 'ingredient1', 'ingredient2', 'ingredient3'],
       ['product1', '45', '35', '25'],
       ['product2', '44', '34', '24'],
       ['product3', '43', '33', '23']], dtype='|S11')

Then you can make a dataframe based on your data:

   df = pd.DataFrame(data=my_data[1:,1:],
                  index=my_data[1:,0],
                  columns=my_data[0,1:])
df

and produces:

enter image description here

Upvotes: 2

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