The pandas module provides different methods to add and remove rows from a dataframe. In this article, we will discuss different ways to append a row to pandas dataframe using the append() method and the concat() function.
The Pandas append() Method
We use the append() method to append a dictionary, series, or dataframe object to another dataframe. It has the following syntax.
DataFrame.append(other, ignore_index=False, verify_integrity=False, sort=False)Here,
- The
otherparameter takes a pandas Series, dictionary, or another dataframe as its input argument. - We use the
ignore_indexparameter to specify if we want to preserve the index of the original dataframes. By default, it is set toFalse, which means that the output dataframe contains indices from the original dataframes. To reset the indices and create a new index in the output dataframe, you can set theignore_indexparameter toTrue. - We use the
verify_integrityparameter to specify if we want to allow duplicate indices in the output dataframe or not. By default, theverify_integrityparameter is set toFalse. It means that the output dataframe can contain duplicate indices. To disallow duplicate indices, you can set theverify_integrityparameter toTrue. - We use the
sortparameter to specify if we want to sort columns if the columns of the dataframes are not aligned.
After execution, the append() method returns a new dataframe.
Append Row at the Top of a Pandas DataFrame
To append a row at the top of a dataframe, we will use the append() method and the DataFrame() function.
Suppose that we want to append a new python dictionary as a row to an existing dataframe. For this, we will use the following steps.
- First, we will put the dictionary containing the row values into a list.
- Next, we will create a dataframe using the list and the
DataFrame()function. TheDataFrame()function takes the list containing the dictionary as its input and returns a dataframe after execution. - Now, we will invoke the
append()method on the newly created dataframe and pass the existing dataframe as its input argument.
After execution of the append() method, we will get the output dataframe with a new row appended at the top. You can observe this in the following example.
import pandas as pd
myDicts=[{"Roll":1,"Maths":100, "Physics":80, "Chemistry": 90},
{"Roll":2,"Maths":80, "Physics":100, "Chemistry": 90},
{"Roll":3,"Maths":90, "Physics":80, "Chemistry": 70},
{"Roll":4,"Maths":100, "Physics":100, "Chemistry": 90},
{"Roll":5,"Maths":90, "Physics":90, "Chemistry": 80},
{"Roll":6,"Maths":80, "Physics":70, "Chemistry": 70}]
df=pd.DataFrame(myDicts)
print("The original dataframe is:")
print(df)
newDict= {"Roll":11,"Maths":81, "Physics":74, "Chemistry": 93}
print("New row data is:")
print(newDict)
df1=pd.DataFrame([newDict])
df2=df1.append(df,ignore_index=True)
print("The output dataframe is:")
print(df2)Output:
The original dataframe is:
Roll Maths Physics Chemistry
0 1 100 80 90
1 2 80 100 90
2 3 90 80 70
3 4 100 100 90
4 5 90 90 80
5 6 80 70 70
New row data is:
{'Roll': 11, 'Maths': 81, 'Physics': 74, 'Chemistry': 93}
The output dataframe is:
Roll Maths Physics Chemistry
0 11 81 74 93
1 1 100 80 90
2 2 80 100 90
3 3 90 80 70
4 4 100 100 90
5 5 90 90 80
6 6 80 70 70The append() method will be deprecated from the upcoming pandas versions. Therefore, you can use the concat() function to concatenate the dataframes.
Pandas Append Row at the Top of a DataFrame Using The concat() Function
The contact() function takes a list of dataframes as its input argument and concatenates them into a single dataframe. As we want to append a new row to an existing dataframe, we will pass the dataframe containing the new row as the first element and the existing dataframe as the second element of the input list to the concat() function.
After execution of the concat() function, we will get the desired output dataframe as shown below.
import pandas as pd
myDicts=[{"Roll":1,"Maths":100, "Physics":80, "Chemistry": 90},
{"Roll":2,"Maths":80, "Physics":100, "Chemistry": 90},
{"Roll":3,"Maths":90, "Physics":80, "Chemistry": 70},
{"Roll":4,"Maths":100, "Physics":100, "Chemistry": 90},
{"Roll":5,"Maths":90, "Physics":90, "Chemistry": 80},
{"Roll":6,"Maths":80, "Physics":70, "Chemistry": 70}]
df=pd.DataFrame(myDicts)
print("The original dataframe is:")
print(df)
newDict= {"Roll":11,"Maths":81, "Physics":74, "Chemistry": 93}
print("New row data is:")
print(newDict)
df1=pd.DataFrame([newDict])
df2=pd.concat([df1,df],ignore_index=True)
print("The output dataframe is:")
print(df2)Output:
The original dataframe is:
Roll Maths Physics Chemistry
0 1 100 80 90
1 2 80 100 90
2 3 90 80 70
3 4 100 100 90
4 5 90 90 80
5 6 80 70 70
New row data is:
{'Roll': 11, 'Maths': 81, 'Physics': 74, 'Chemistry': 93}
The output dataframe is:
Roll Maths Physics Chemistry
0 11 81 74 93
1 1 100 80 90
2 2 80 100 90
3 3 90 80 70
4 4 100 100 90
5 5 90 90 80
6 6 80 70 70In the above examples, we have appended a new row at the top of a dataframe using the append() method and the concat() method one by one.
Append a Row at The Bottom of a DataFrame
To append a row at the bottom of a dataframe, we just need to invoke the append() method on the original dataframe and pass the python dictionary containing the row data as an input argument. After execution of the append() method, we will get the desired output dataframe as shown below.
import pandas as pd
myDicts=[{"Roll":1,"Maths":100, "Physics":80, "Chemistry": 90},
{"Roll":2,"Maths":80, "Physics":100, "Chemistry": 90},
{"Roll":3,"Maths":90, "Physics":80, "Chemistry": 70},
{"Roll":4,"Maths":100, "Physics":100, "Chemistry": 90},
{"Roll":5,"Maths":90, "Physics":90, "Chemistry": 80},
{"Roll":6,"Maths":80, "Physics":70, "Chemistry": 70}]
df=pd.DataFrame(myDicts)
print("The original dataframe is:")
print(df)
newDict= {"Roll":11,"Maths":81, "Physics":74, "Chemistry": 93}
print("New row data is:")
print(newDict)
df2=df.append(newDict,ignore_index=True)
print("The output dataframe is:")
print(df2)Output:
The original dataframe is:
Roll Maths Physics Chemistry
0 1 100 80 90
1 2 80 100 90
2 3 90 80 70
3 4 100 100 90
4 5 90 90 80
5 6 80 70 70
New row data is:
{'Roll': 11, 'Maths': 81, 'Physics': 74, 'Chemistry': 93}
The output dataframe is:
Roll Maths Physics Chemistry
0 1 100 80 90
1 2 80 100 90
2 3 90 80 70
3 4 100 100 90
4 5 90 90 80
5 6 80 70 70
6 11 81 74 93While using the append() method in the above example, we have set the ignore_index parameter to True. This is necessary because the append() method will run into an error if we don’t do so. While appending a dictionary to the pandas dataframe using the append() method, you always need to set the ignore_index parameter to True.
Pandas Append Row at the Bottom of a DataFrame Using The concat() Function
To append a row at the bottom of a dataframe using the contact() function, you first need to create a dataframe from the dictionary containing the row data.
Then, you can pass the existing dataframe as the first element and the dataframe containing the new row as the second element of the input list to the concat() function. After execution of the concat() function, you will get the desired dataframe as shown in the following example.
import pandas as pd
myDicts=[{"Roll":1,"Maths":100, "Physics":80, "Chemistry": 90},
{"Roll":2,"Maths":80, "Physics":100, "Chemistry": 90},
{"Roll":3,"Maths":90, "Physics":80, "Chemistry": 70},
{"Roll":4,"Maths":100, "Physics":100, "Chemistry": 90},
{"Roll":5,"Maths":90, "Physics":90, "Chemistry": 80},
{"Roll":6,"Maths":80, "Physics":70, "Chemistry": 70}]
df=pd.DataFrame(myDicts)
print("The original dataframe is:")
print(df)
newDict= {"Roll":11,"Maths":81, "Physics":74, "Chemistry": 93}
print("New row data is:")
print(newDict)
df1=pd.DataFrame([newDict])
df2=pd.concat([df,df1],ignore_index=True)
print("The output dataframe is:")
print(df2)Output:
The original dataframe is:
Roll Maths Physics Chemistry
0 1 100 80 90
1 2 80 100 90
2 3 90 80 70
3 4 100 100 90
4 5 90 90 80
5 6 80 70 70
New row data is:
{'Roll': 11, 'Maths': 81, 'Physics': 74, 'Chemistry': 93}
The output dataframe is:
Roll Maths Physics Chemistry
0 1 100 80 90
1 2 80 100 90
2 3 90 80 70
3 4 100 100 90
4 5 90 90 80
5 6 80 70 70
6 11 81 74 93As you can observe in the above output, we have appended a new row at the bottom of an existing dataframe using the contact() function.
Conclusion
In this article, we discussed how to append a row to a dataframe. To learn more about python programming, you can read this article on how to convert string to dataframe in python. You might also like this article on how to convert pandas dataframe to a list in python.
I hope you enjoyed reading this article. Stay tuned for more informative articles.
Happy Learning!
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