Pandas dataframe.append() – Python



Pandas dataframe.append() – Python

 

Pandas dataframe.append() function is used to append rows of other dataframe to the end of the given dataframe, returning a new dataframe object. Columns not in the original dataframes are added as new columns and the new cells are populated with NaN value.

Syntax: DataFrame.append(other, ignore_index=False, verify_integrity=False, sort=None)

Parameters :
other : DataFrame or Series/dict-like object, or list of these
ignore_index : If True, do not use the index labels.
verify_integrity : If True, raise ValueError on creating index with duplicates.
sort : Sort columns if the columns of self and other are not aligned. The default sorting is deprecated and will change to not-sorting in a future version of pandas. Explicitly pass sort=True to silence the warning and sort. Explicitly pass sort=False to silence the warning and not sort.

Returns: appended : DataFrame

Example #1: Create two data frames and append the second to the first one.



# Importing pandas as pd
import pandas as pd
 
# Creating the first Dataframe using dictionary
df1 = df = pd.DataFrame({"a":[1, 2, 3, 4],
                         "b":[5, 6, 7, 8]})
 
# Creating the Second Dataframe using dictionary
df2 = pd.DataFrame({"a":[1, 2, 3],
                    "b":[5, 6, 7]})
 
# Print df1
print(df1, "\n")
 
# Print df2
df2


Now append df2 at the end of df1.

# to append df2 at the end of df1 dataframe
df1.append(df2)



Output :

Notice the index value of second data frame is maintained in the appended data frame. If we do not want it to happen then we can set ignore_index=True.

# A continuous index value will be maintained
# across the rows in the new appended data frame.
df1.append(df2, ignore_index = True)

Output :

Example #2: Append dataframe of different shape.

For unequal no. of columns in the data frame, non-existent value in one of the dataframe will be filled with NaN values.



# Importing pandas as pd
import pandas as pd
 
# Creating the first Dataframe using dictionary
df1 = pd.DataFrame({"a":[1, 2, 3, 4],
                    "b":[5, 6, 7, 8]})
 
# Creating the Second Dataframe using dictionary
df2 = pd.DataFrame({"a":[1, 2, 3],
                    "b":[5, 6, 7], 
                    "c":[1, 5, 4]})
 
# for appending df2 at the end of df1
df1.append(df2, ignore_index = True)

Output :

Notice, the new cells are populated with NaN values.

Last Updated on October 8, 2021 by admin

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