How to append rows in pandas ,if column value is not in a external list

Question

I have a DataFrame you can have it by running this code:

df = """    
Facility    Quarter   Price
      F1    Q1         2.1  
      F1    Q2         1.2  
"""
df= pd.read_csv(StringIO(df.strip()), sep='ss+', engine='python')

And a list:

quarters=['Q1','Q2','Q3','Q4']

The logic is if the Quarter value is not in quarters list ,then append rows that assign the value of price to 0.

The output should looks like:

Facility    Quarter   Price
      F1    Q1         2.1  
      F1    Q2         1.2  
      F1    Q3         0
      F1    Q4         0

Asked By: William

||

Source

Answer 1

You can use pd.MultiIndex.from_product to recreate all combinations:

quarters=['Q1', 'Q2', 'Q3', 'Q4']
cols = ['Facility', 'Quarter']
mi = pd.MultiIndex.from_product([df['Facility'].unique(), quarters], names=cols)
out = df.set_index(cols).reindex(mi, fill_value=0).reset_index()
print(out)

# Output
  Facility Quarter  Price
0       F1      Q1    2.1
1       F1      Q2    1.2
2       F1      Q3    0.0
3       F1      Q4    0.0

Another way with pivot:

>>> (df.pivot(index='Facility', columns='Quarter', values='Price')
       .reindex(quarters, axis=1, fill_value=0)
       .stack().rename('Price').reset_index())

  Facility Quarter  Price
0       F1      Q1    2.1
1       F1      Q2    1.2
2       F1      Q3    0.0
3       F1      Q4    0.0

Answered By: Corralien

Answer 2

You can use janitor‘s complete:

# pip install janitor
import janitor

quarters=['Q1','Q2','Q3','Q4']

out = df.complete({'Quarter': quarters}, 'Facility', fill_value=0)

Output:

  Facility Quarter  Price
0       F1      Q1    2.1
1       F1      Q2    1.2
2       F1      Q3    0.0
3       F1      Q4    0.0

Answered By: mozway

Answer 3

this is my solution to your problem. I hope this helps.

import pandas as pd

data = {'Facility': ['F1', 'F1'], 'Quarter': ['Q1', 'Q2'], 'Price': [2.1, 1.2]}
df = pd.DataFrame(data)

quarters=['Q1','Q2','Q3','Q4']

#make dataframe bigger if needed
df = df.reindex(range(max(len(df), len(quarters))))

#turn list into pd.Series
se_quarters = pd.Series(quarters)

#repalce and add values to Quarter column
df['Quarter'] = se_quarters.values

#have everywhere the same value for column Facility
df['Facility'] = 'F1'

#replace the NaN values with 0
df = df.fillna(0)

Result:

Answered By: Aylinn

How to append rows in pandas ,if column value is not in a external list

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