Append list of dictionary and series to a existing Pandas DataFrame in Python



Append list of dictionary and series to a existing Pandas DataFrame in Python

In this article, we will discuss how values from a list of dictionaries or Pandas Series can be appended to an already existing pandas dataframe. For this purpose append() function of pandas, the module is sufficient.

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

Approach 

  • Import module
  • Create data frame or series
  • Create a list with dictionaries
  • Append this list to existing data frame or series

Example 1:

# import pandas
import pandas as pd
# create dataframe
df = pd.DataFrame({
    'Employs Name': ['Rishabh', 'Rahul', 'Suraj', 'Mukul', 'Vinit'],
    'Location': ['Saharanpur', 'Meerut', 'Saharanpur', 'Meerut', 'Saharanpur'],
    'Pay': [21000, 22000, 23000, 24000, 22000]})
# print dataframe
print("\n  ***  Original DataFrames  **  \n")
print(df)
# create dictionaries
dicts = [{'Employs Name': 'Anuj', 'Location': 'Meerut', 'Roll No': 30000},
         {'Employs Name': 'Arun', 'Location': 'Saharanpur', 'Roll No': 32000}]
# print dictionaries
print("\n  **  Dictionary  ** ")
print(dicts)
# combined data
df = df.append(dicts, ignore_index=True, sort=False)
# print combined dataframe
print("\n\n  **  Combined Data  **\n")
print(df)

Output:

 

 

Example 2:

# import pandas
import pandas as pd
# create dataframe
df = pd.DataFrame({
    'Name': ['Mukul', 'Rohit', 'Suraj', 'Rohan', 'Rajan'],
    'Course': ['BBA', 'BCA', 'MBA', 'BCA', 'BBA'],
    'Roll No': [21, 22, 23, 24, 25]})
# print dataframe
print("\n  ***  Original DataFrames  ** ")
display(df)
# create series
s6 = pd.Series(['Vedansh', 'MBA', 29], index=['Name', 'Course', 'Roll No'])
# print series
print("\n  ***  series  ** ")
print(s6)
# create dictionaries
dicts = [{'Name': 'Aakash', 'Course': 'BCA', 'Roll No': 30}]
# print dictionaries
print("\n  **  Dictionary  ** ")
print(dicts)
# combined data
df = df.append(dicts, ignore_index=True, sort=False)
print("\n  **  Combined Data  **")
display(df)

Output:

 

Last Updated on October 19, 2021 by admin

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