How to add a row to a Pandas Dataframe

In this tutorial we’ll cover everything you might need in order to add new rows into an existing DataFrame. We’ll look specifically into a step-by-step process to append lists, dictionaries and Pandas Series objects into DataFrames.

1. Preparing the Data

We’ll first start by defining a few data objects that we’ll use throughout our examples.

import pandas as pd


# Create dummy data


survey_dict = {            'language': ['C++', 'VB.NET', 'Go', 'PHP', 'Perl'],
                          'avg_salary': [80,75,70,90,80],
                          'num_candidates': [122,154,138,120,145]
                                       }
# Build the Pandas DataFrame
survey = pd.DataFrame(survey_dict)

survey

Here’s our initial DataFrame:

	language	avg_salary	num_candidates
0	C++	80	122
1	VB.NET	75	154
2	Go	70	138
3	PHP	90	120
4	Perl	80	145

2. Insert row from Dictionary

Let’s define a new dictionary and insert it to the DataFrame using the append() DataFrame method. Note that we are able to pass the dictionary itself as a parameter of append().

new_dict = {'language': 'R', 'avg_salary': 80, 'num_candidates': 90 }
survey = survey.append(new_dict, ignore_index=True)
survey

Let’s take a look at the result:

	language	avg_salary	num_candidates
0	C++	80	122
1	VB.NET	75	154
2	Go	70	138
3	PHP	90	120
4	Perl	80	145
5	R	80	90

3. Append multiple rows without index

In this case we’ll use the pd.concat() method to join our survey DataFrame and a new DataFrame comprising multiple row.

# without index
new_dict = {'language': ['VB', 'HTML'], 'avg_salary': [70, 50], 'num_candidates': [100, 110] }
survey2 = pd.DataFrame(new_dict)
survey3 = pd.concat([survey, survey2],ignore_index=True)


survey3

Note :if you are passing only a scalar in your dictionary, you might get the following error: If using all scalar values, you must pass an index. In that case, make sure you pass a list as your dictionary value or use the parameter ignore_index=True.

Here’s our output:

	language	avg_salary	num_candidates
0	C++	80	122
1	VB.NET	75	154
2	Go	70	138
3	PHP	90	120
4	Perl	80	145
5	R	80	90
6	VB	70	100
7	HTML	50	11

4. Insert list at a specific index

In this example we’ll use the loc indexer to insert a list into a specific index. In this case we would like to append the new row as the last in our DF.

# insert row using index

new_row = ['Python', 120, 170]
survey = pd.DataFrame(survey_dict)
survey.loc[len(survey.index)] = new_row
survey

Here’s our output:

	language	avg_salary	num_candidates
0	C++	80	122
1	VB.NET	75	154
2	Go	70	138
3	PHP	90	120
4	Perl	80	145
5	Python	120	17

5. Insert row at top of Pandas DataFrame

In this example we’ll simply append two DataFrames, the trick would be to append the existing DF to the new one.

new_dict = {'language': 'R', 'avg_salary': [80], 'num_candidates': [90] }
survey = pd.DataFrame(survey_dict)
survey2 = pd.DataFrame(new_dict)
survey3 = survey2.append(survey, ignore_index=True)
survey3

Here’s the output:

	language	avg_salary	num_candidates
0	R	80	90
1	C++	80	122
2	VB.NET	75	154
3	Go	70	138
4	PHP	90	120
5	Perl	80	14

6. Add Pandas series as a column

In this example we’ll first create a Pandas Series from a dictionary and then join it to our DataFrame.

#add series to dataframe as row
new_dict = {'language': 'R', 'avg_salary': 80, 'num_candidates': 90 }
new_s = pd.Series(new_dict)
survey.append(new_s, ignore_index=True)

7. New row to empty DataFrame

In our last example for today, we’ll first create an empty Dataframe and then append the new data:

new_dict = {'language': 'R', 'avg_salary': 80, 'num_candidates': 90 }
survey4 = pd.DataFrame(columns = survey.columns)
survey4.append(new_dict,ignore_index=True)

And the output will be:

	language	avg_salary	num_candidates
0	R	80	90