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