How to append row to dataframe

Append Rows to a Pandas DataFrame

While working with dataframes, it may happen that you’d want to add a few rows to a dataframe. Pandas dataframes are quite versatile when it comes to handing and manipulating tabular data. Among other features, they allow you the flexibility to append rows to an existing dataframe. In this tutorial, we’ll look at how to append one or more rows to a pandas dataframe through some examples.

The pandas dataframe append() function

The pandas dataframe append() function is used to add one or more rows to the end of a dataframe. The following is the syntax if you say want to append the rows of the dataframe df2 to the dataframe df1

Examples

Let’s see some of the different use-cases of the append() function through some examples –

1. Append rows of another dataframe

You can append another dataframe’s rows at the end of a dataframe. Pass the dataframe whose rows you want to append as an argument to the append() function.

2. Append rows with a mismatch in columns

Columns that are not present in the original dataframe (the one on which the append function is applied) are added as new columns. See the example below:

Note that you can also use the pandas concat() function to concatenate dataframes.

3. Append a list as a row to a dataframe

If you want to append a list as a row to a pandas dataframe you can convert it to a pandas series first and then use the append() function to add it to the dataframe. See the example below:

For more on the pandas append() function, refer to its official documentation.

With this, we come to the end of this tutorial. The code examples and results presented in this tutorial have been implemented in a Jupyter Notebook with a python (version 3.8.3) kernel having pandas version 1.0.5

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How to append new row to dataframe in pandas?

This is the code I have used:

How to store the name, password and email in the csv file by using pandas dataframe?

5 Answers 5

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Another simple approach is to use pd.Dataframe.loc method.

Output

You can use pd.DataFrame.loc to add a row to your dataframe:

A good way is to create an empty list first, populate it and then add to the empty data frame like this

it will give the results like this

The accepted answer is good if all you are doing is appending rows. However, if you do other operations such as:

then some of the index values will be greater than the size of the dataframe, and the accepted answer may overwrite an existing row.

In that case, I recommend:

which, if the dataframe could be empty, may have to become:

Pandas Add Row to DataFrame – Definitive Guide

Pandas dataframe is a two-dimensional data structure. When using the dataframe for data analysis, you may need to create a new dataframe and selectively add rows for creating a dataframe with specific records.

You can add rows to the pandas dataframe using df.iLOC[i] = [‘col-1-value’, ‘col-2-value‘, ‘ col-3-value ‘] statement.

Other options available to add rows to the dataframe are,

If You’re in Hurry…

You can use the below code snippet to add rows to the dataframe.

Snippet

Dataframe Will Look Like

If You Want to Understand Details, Read on…

In this tutorial, you’ll learn the different methods available to add rows to a dataframe. You’ll also learn how to insert a row into an empty dataframe.

Table of Contents

Creating an Empty Dataframe

First, you need to create an empty dataframe to add rows to it. You can do it by using DataFrame() method as shown below.

Snippet

Add Row to Dataframe

Let’s have a look at it one by one.

To create a new row, you need to know the columns already available in the dataframe. Read How to Get Column Name in Pandas to know the columns in the dataframe.

Alternatively, you can print the dataframe using print(df) to know the dataframe columns.

Using Append

You can use the append() method to append a row to an existing dataframe.

Parameters

inplace append is not possible. Hence, do not forget to assign the result to a dataframe object to access it later.

In the below example, a dictionary is created with values for the columns which already exist in the target dataframe. Then it is appended to the target dataframe using the append() method.

Now, you’ve appended one row to the dataframe.

Dataframe Will Look Like

This is how you can insert a row to the dataframe using append.

Using Concat

You can append a row to the dataframe using concat() method. It concatenates two dataframe into one.

To add one row, create a dataframe with one row and concatenate it to the existing dataframe.

Parameters

It returns a new dataframe object which has the rows concatenated from two dataframes.

inplace concatenation is not supported. Hence, remember to assign the result to a variable for later use.

Snippet

Both df and df2 will be concatenated and you’ll see two rows in the resultant dataframe.

Dataframe Will Look Like

This is how you can use the concat() method to add rows to the dataframe.

Using iLOC

You can use the iLoc[] attribute to add a row at a specific position in the dataframe. iloc is an integer-based indexing for selecting rows from the dataframe. You can also use it to assign new rows at that position.

Adding a row at a specific index position will replace the existing row at that position.

Snippet

Dataframe Will Look Like

This is how you can use the iloc[] to insert a row to the existing dataframe.

Using LOC

You can add a row to the dataframe using the loc parameter. loc[] is used to access a set of rows from the dataframe using the index label. You can also assign rows with a specific index label using the loc attribute.

When using the loc[] attribute, it’s not mandatory that a row already exists with a specific label. It’ll automatically extend the dataframe and add a row with that label, unlike the iloc[] method.

A full program is demonstrated for this method because previous methods have the dataframe with the row indexes 1,2,3.

Snippet

Dataframe Will Look Like

This is how you can use the loc[] method to add rows to the dataframe. Either it is an empty dataframe or it already has values.

Once the rows are added, you select rows from pandas dataframe based on column values to check if the rows are added properly.

Pandas Insert Row at Specific Index

You can insert rows at a specific index in a dataframe using the loc method.

This will be useful when you want to insert a row between two rows in a dataframe.

Alternatively, you can also use the iloc[] method to add rows at a specific index. However, there must be a row already existing with a specific index.

Note

Snippet

Dataframe Will Look Like

This is how you can append rows at a specific index in a dataframe.

Pandas Insert Row At top

Now indexes of the rows in the dataframe will be 0,1,2. n-1.

Note

To use this method, the index labels of the rows must be integers. Otherwise, it won’t work.

Snippet

Dataframe Will Look Like

This is how you can insert a row at top of the dataframe.

Pandas Insert Row at Bottom

df.shape[0] returns the length of the dataframe.

Snippet

A new row will be added at the index position 4 as you see below.

Dataframe Will Look Like

Pandas Insert Empty Row

You may need to append an empty row to the pandas dataframe for adding a row to it later. You can also fill values for specific columns in the dataframe after creating an empty row.

Empty rows can be appended by using the df.loc[df.shape[0]] and assigning None values for all the existing columns.

For example, if your dataframe has three columns, you can create a series with 3 None values and assign it at the last position of the dataframe.

That is how you can insert an empty row into the dataframe.

Snippet

An empty row is added at the end of the dataframe.

Dataframe Will Look Like

This is how you can add an empty row to the end of the dataframe.

Pandas Append Two Dataframe Pandas

You can append a dataframe to another dataframe using the dataframe append() method.

append() method accepts a dataframe and appends it to the calling dataframe and returns a new dataframe object.

inplace append is not possible. hence you need to assign the result a dataframe object if you want to use it later.

ignore_index can be used to ignore the index of the dataframe that is assigned to the target dataframe.

Snippet

In the above example, dataframe df2 is appended to df and assigned it back to the df object.

Dataframe Will Look Like

This is how you can append two dataframe in pandas using the append() method.

Why You Should Not Add Rows One By One To Dataframe

You may need to create a dataframe and append one row at a time in various scenarios.

In that case, it is advisable to create a list first to hold all the records and create a dataframe with all the records in one shot using the pd.DataFrame() method.

Calling the append() method for each row is a costlier operation. But adding the rows to the list is not costlier. Hence, you can add to the list and create a dataframe using that list.

Snippet

For more details about this scenario, refer StackOverflow answer.

Dataframe Will Look Like

This is how you can create a pandas dataframe by appending one row at a time.

Conclusion

Also, how these methods can be used to insert a row at a specific index, add a row to the top or bottom of the dataframe, how to add an empty row to the dataframe which can be used at a later point.

In addition to that, you’ve learned why you should not create a pandas dataframe by appending one row at a time and use a list in such scenarios and create a dataframe using the list.

How to Append Row to pandas DataFrame

Table of Contents

You can append one row or multiple rows to an existing pandas DataFrame in several ways, one way would be creating a list or dict with the details and appending it to DataFrame.

You can append a row to DataFrame by using append(), pandas.concat(), and loc[], in this article I will explain how to append a python list, dict (dictionary) as a row to pandas DataFrame, which ideally inserts a new row(s) to the DataFrame with elements specified by a list and dict.

1. Quick Examples of Append Row to DataFrame

If you are in a hurry, below are some quick examples of how to append a row to pandas DataFrame.

Yields below output.

2. Append Dict as Row to DataFrame

You can create a DataFrame and append a new row to this DataFrame from dict, first create a Python Dictionary and use append() function, this method is required to pass ignore_index=True in order to append dict as a row to DataFrame, not using this will get you an error.

Yields below output.

3. Append List to DataFrame

4. Append Row at the Specific Index Name

Note that in this example, first we are creating a new DataFrame/Series and append this to another DataFrame at the specified index.

Yields below output for both examples.

5. Use concat() to Append

Use pd.concat([new_row,df.loc[:]]).reset_index(drop=True) to append the row to the first position of the DataFrame as Index starts from zero.

Yields below output.

6. Use DataFrame.loc[] to Append Row

By using df.loc[Index_label]=new_row you can append a list as a row to the DataFrame at a specified index.

Yields below output.

7. Complete Example of Append Row to DataFrame

Conclusion

Add Row to Dataframe in Pandas

In this article, we will discuss how to add / append a single or multiple rows in a dataframe using dataframe.append() or loc & iloc.

Table of Contents

Overview of pandas dataframe append()

Pandas Dataframe provides a function dataframe.append() to add rows to a dataframe i.e.

Here, the ‘other’ parameter can be a DataFrame or Series or Dictionary or list of these. Also, if ignore_index is True then it will not use indexes.

Examples of adding row to the dataframe

Suppose we have a dataframe df, whose contents are as follows,

Add dictionary as a row to dataframe

In dataframe.append() we can pass a dictionary of key value pairs i.e.

Let’s add a new row in above dataframe by passing dictionary i.e.

It will not modify the existing dataframe object mod_df, it will return a new dataframe containing copy of contents of existing dataframe and with a new row appended at it’s end. Contents of the dataframe returned are,

New DataFrame’s index is not same as original dataframe because ignore_index is passed as True in append() function. Also, for columns which were not present in the dictionary NaN value is added.

Passing ignore_index=True is necessary while passing dictionary or series otherwise following TypeError error will come i.e.

“TypeError: Can only append a Series if ignore_index=True or if the Series has a name”

Complete example to add a dictionary as row to the dataframe is as follows,

Output:

Add Series as a row in the dataframe

We can also pass a series object to the append() function to append a new row to the dataframe i.e.

While creating a series object we passed the index names same as index of dataframe. Contents of the dataframe returned are,

Checkout the complete example to a append a series as row to dataframe,

Output:

Add multiple rows to pandas dataframe

We can pass a list of series too in the dataframe.append() for appending multiple rows in dataframe. For example, we can create a list of series with same column names as dataframe i.e.

Now pass this list of series to the append() function i.e.

Contents of the dataframe returned are,

Complete example to add multiple rows to dataframe is as follows,

Output

Add row from one dataframe to another dataframe

We can select a row from dataframe by its name using loc[] attribute and the pass the selected row as an argument to the append() function. It will add the that row to the another dataframe. Let’s see an example where we will select a row with index label ‘b’ and append it to another dataframe using append(). For example,

Output

Add list as a row to pandas dataframe using loc[]

Adding a list as a row to the dataframe in pandas is very simple and easy. We can just pass the new index label in loc[] attribute and assign list object to it. For example,

It will append a new row to the dataframe with index label ‘k’. Let’s see a complete example to append a list as row to the dataframe,

Output:

Add a row in the dataframe at index position using iloc[]

We can add a row at specific position too in the dataframe using iloc[] attribute. Checkout the example, where we will add a list as the 3rd row the dataframe. For example,

Output:

Summary:

We learned about different ways to add / append rows to the dataframe in pandas.

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