How to append Dataframe by using Pandas in Python?

Data Science, AI and ML
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#1

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