Pandas Append

by Online Tutorials Library July 14, 2022

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:

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

Next TopicDataFrame.apply()