Pandas Append

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Pandas DataFrame.append()

The Pandas append() function is used to add the rows of other dataframe to the end of the given dataframe, returning a new dataframe object. The new columns and the new cells are inserted into the original DataFrame that 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 a list of these
It refers to the data to be appended.
ignore_index: If it is true, it does not use the index labels.
verify_integrity: If it is true, it raises ValueError on creating an index with duplicates.
sort: It sorts the columns if the columns of self and other are not aligned. The default sorting is deprecated, and it will change to not-sorting in a future version of pandas. We pass sort=True Explicitly for silence the warning and the sort, whereas we pass sort=False Explicitly for silence the warning and not the sort.

Returns:

It returns the appended DataFrame as an output.

Example1:

import pandas as pd 
# Create first Dataframe using dictionary 
info1 = pd.DataFrame({"x":[25,15,12,19], 
                    "y":[47, 24, 17, 29]})   
# Create second Dataframe using dictionary 
Info2 = pd.DataFrame({"x":[25, 15, 12], 
                    "y":[47, 24, 17],  
                    "z":[38, 12, 45]}) 
# append info2 at end in info1 
info.append(info2, ignore_index = True)

Output

     x       y      z
0    25      47     NaN  
1    15      24     NaN
2    12      17     NaN
3    19      29     NaN
4    25      47     38.0
5    15      24     12.0
6    12      17     45.0

Example2:

import pandas as pd   
# Create first Dataframe using dictionary 
info1 = info = pd.DataFrame({"x":[15, 25, 37, 42], 
                         "y":[24, 38, 18, 45]})   
# Create second Dataframe using dictionary 
info2 = pd.DataFrame({"x":[15, 25, 37], 
                    "y":[24, 38, 45]})   
# print value of info1 
print(info1, "\n")  
# print values of info2 
info2 
# append info2 at the end of info1 dataframe 
info1.append(df2) 
# Continuous index value will maintained 
# across rows in the new appended data frame. 
info.append(info2, ignore_index = True)

Output

     x     y
0    15   24
1    25   38
2    37   18
3    42   45
4    15   24
5    25   38
6    37   45

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