Pandas Append Rows & Columns to Empty DataFrame
Let’s discuss how to create an empty DataFrame and append rows & columns to it in Pandas and Python. There are multiple ways in which we can do this task. Here we will cover the following section:
- Creating an empty Dataframe in Pandas
- Append row to Dataframe in Pandas
- Append row to Dataframe in Pandas
Creating empty Dataframe
Creating an Empty DataFrame object.
Python3
import pandas as pd
df = pd.DataFrame()
print (df)
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Output:
Empty DataFrame
Columns: []
Index: []
Append Column to Dataframe to Empty DataFrame
Example 1: Create a complete empty DataFrame without any column name or indices and then append columns in Pandas one by one to it.
Python3
import pandas as pd
df = pd.DataFrame()
print (df)
df[ 'Name' ] = [ 'Ankit' , 'Ankita' , 'Yashvardhan' ]
df[ 'Articles' ] = [ 97 , 600 , 200 ]
df[ 'Improved' ] = [ 2200 , 75 , 100 ]
df
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Output:
Example 2: This method will create a new Dataframe with a new column added to the old Dataframe using assign in Pandas.
Python3
import pandas as pd
data = { 'Name' : [ 'Jai' , 'Princi' , 'Gaurav' , 'Anuj' ],
'Height' : [ 5.1 , 6.2 , 5.1 , 5.2 ],
'Qualification' : [ 'Msc' , 'MA' , 'Msc' , 'Msc' ]}
df = pd.DataFrame(data)
df2 = df.assign(address = [ 'Delhi' , 'Bangalore' , 'Chennai' , 'Patna' ])
print (df2)
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Output:
Append row to Empty DataFrame
Example 1: Create an empty DataFrame with columns name only then append rows one by one to it using append() method.
Python3
import pandas as pd
df = pd.DataFrame(columns = [ 'Name' , 'Articles' , 'Improved' ])
print (df)
df = df.append({ 'Name' : 'Ankit' , 'Articles' : 97 , 'Improved' : 2200 },
ignore_index = True )
df = df.append({ 'Name' : 'Aishwary' , 'Articles' : 30 , 'Improved' : 50 },
ignore_index = True )
df = df.append({ 'Name' : 'yash' , 'Articles' : 17 , 'Improved' : 220 },
ignore_index = True )
df
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Output:
Example 2: Create an empty DataFrame with a column name and indices and then append rows one by one to it using the loc[] method.
Python3
import pandas as pd
df = pd.DataFrame(columns = [ 'Name' , 'Articles' , 'Improved' ],
index = [ 'a' , 'b' , 'c' ])
print ( "Empty DataFrame With NaN values : \n\n" , df)
df.loc[ 'a' ] = [ 'Ankita' , 50 , 100 ]
df.loc[ 'b' ] = [ 'Ankit' , 60 , 120 ]
df.loc[ 'c' ] = [ 'Harsh' , 30 , 60 ]
df
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Output:
Last Updated :
29 Sep, 2023
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