Pandas: Append a list of dictioneries or series to a existing DataFrame
4. Append List of Dictionaries/Series
Write a Pandas program to append a list of dictioneries or series to a existing DataFrame and display the combined data.
Test Data:
student_id name marks 0 S1 Danniella Fenton 200 1 S2 Ryder Storey 210 2 S3 Bryce Jensen 190 3 S4 Ed Bernal 222 4 S5 Kwame Morin 199
Dictionary: student_id S6 name Scarlette Fisher marks 205 dtype: object
Sample Solution:
Python Code :
import pandas as pd
student_data1 = pd.DataFrame({
'student_id': ['S1', 'S2', 'S3', 'S4', 'S5'],
'name': ['Danniella Fenton', 'Ryder Storey', 'Bryce Jensen', 'Ed Bernal', 'Kwame Morin'],
'marks': [200, 210, 190, 222, 199]})
s6 = pd.Series(['S6', 'Scarlette Fisher', 205], index=['student_id', 'name', 'marks'])
dicts = [{'student_id': 'S6', 'name': 'Scarlette Fisher', 'marks': 203},
{'student_id': 'S7', 'name': 'Bryce Jensen', 'marks': 207}]
print("Original DataFrames:")
print(student_data1)
print("\nDictionary:")
print(s6)
combined_data = student_data1.append(dicts, ignore_index=True, sort=False)
print("\nCombined Data:")
print(combined_data)
Sample Output:
Original DataFrames: student_id name marks 0 S1 Danniella Fenton 200 1 S2 Ryder Storey 210 2 S3 Bryce Jensen 190 3 S4 Ed Bernal 222 4 S5 Kwame Morin 199 Dictionary: student_id S6 name Scarlette Fisher marks 205 dtype: object Combined Data: student_id name marks 0 S1 Danniella Fenton 200 1 S2 Ryder Storey 210 2 S3 Bryce Jensen 190 3 S4 Ed Bernal 222 4 S5 Kwame Morin 199 5 S6 Scarlette Fisher 203 6 S7 Bryce Jensen 207
For more Practice: Solve these Related Problems:
- Write a Pandas program to append a list of dictionaries to an existing DataFrame and then sort by a specified column.
- Write a Pandas program to add multiple Series as rows to a DataFrame and then reindex the final DataFrame.
- Write a Pandas program to convert a list of dictionaries into a DataFrame and then concatenate it with an existing DataFrame.
- Write a Pandas program to append a list of dictionaries to a DataFrame and then fill missing values with the column mean.
Python Code Editor:
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