How to Append dictionary to a dataframe in pandas

In this article, we will see how to append a dictionary to a dataframe, we could either append dictionary as rows or as a new column to the dataframe

Here are the steps that we will follow in this article to append dictionary as either row or column

• Create a test dataframe
• Create a dictionary of new row values
• Build a dataframe with the dictionary row values using pandas from_dict() function

• Append dictionary dataframe to the test dataframe using pandas concat()

• Create another dictionary with the list of values in a column
• Append dictionary as column to the test dataframe

Create a dataframe

We will create a test dataframe with student details. It has got three columns - Name, Grade and Score.

# importing required libraries
import pandas as pd
import numpy as np

# creating dataframe
df = pd.DataFrame(
        {'student': ['Alex', 'Sam', 'Mary', 
                     'Kayle', 'Paige'],
         'grade': ['A', 'A', 'B', 'C', 'A'],
         'score': [45, 48, 39, 35, 49]})

df

This is how our school dataframe looks like:

	Student	Grade	Score
0	Alex	A	45
1	Sam	A	48
2	Mary	B	39
3	Kayle	C	35
4	Paige	A	49

Append Dictionary as row to dataframe

New Dictionary:

We will create a dataframe with all the new row values that we want to append to the test dataframe created above.

These are the three new students and their corresponding row values, the key of dictionary is the index and the values in list is the row values for each column student, grade and score respectively

new_students = { 5:['stehany', 'C', 32], 
                 6:['Jon', 'A', 47], 
                 7:['Charles', 'B', 40]}

Next, we want to create a dataframe for these new students and let’s call it df_new_students, we will use pandas.from_dict() to build this dataframe from the above dictionary

pandas.from_dict() function creates DataFrame object from dictionary by columns or by index, we have selected the orient parameter as index since we want to add these dictionary values as rows

Dictionary to dataframe:

df_new_students = pd.DataFrame.from_dict(new_students, 
                       orient='index', 
                       columns=['student', 
                                'grade', 
                                'score'])
df_new_students

	Student	Grade	Score
5	stehany	C	32
6	Jon	A	47
7	Charles	B	40

Append Dictionary dataframe to test dataframe:

We will now append the dictionary to test dataframe using pd.concat() function, It concatenates pandas object along a particular axis

newdf = pd.concat([ df, df_new_students])
newdf

	Student	Grade	Score
0	Alex	A	45
1	Sam	A	48
2	Mary	B	39
3	Kayle	C	35
4	Paige	A	49
5	stehany	C	32
6	Jon	A	47
7	Charles	B	40

Append Dictionary as column to dataframe

Let’s create a new dictionary that we want to add as a new column to the test dataframe

ethnicity_col = { 
              'ethicity':
                   [
                    'Asian', 'American', 
                    'Hispanic', 'African-American', 
                    'Asian-American', 'American', 
                    'Hispanic', 'African-American'
                   ]
                }

Add this dictionary as pd.series and create a new column called ethicity

newdf['ethnicity'] = pd.Series(ethnicity_col['ethicity'])

	Student	Grade	Score	Ethnicity
0	Alex	A	45	Asian
1	Sam	A	48	American
2	Mary	B	39	Hispanic
3	Kayle	C	35	African-American
4	Paige	A	49	Asian-American
5	stehany	C	32	American
6	Jon	A	47	Hispanic
7	Charles	B	40	African-American

Let’s create another dictionary with column values and we will add this as a new column to the dataframe

zodiac_sign = { 
                'zodiac':
                   [
                    'capricorn', 'Sagittarius', 
                    'Pisces', 'Scorpio', 
                    'Libra', 'Virgo', 
                    'Leo', 'Cancer'
                   ]
              }

We will now add this dictionary as a new column to this dataframe(newdf) using pandas.from_dict(), the orient paramter will be changed to columns this time

newdf['zodiac_sign'] = newdf.from_dict(
                          zodiac_sign, 
                          orient='columns')
newdf

	Student	Grade	Score	Ethnicity	Zodiac_sign
0	Alex	A	45	Asian	Capricorn
1	Sam	A	48	American	Sagittarius
2	Mary	B	39	Hispanic	Pisces
3	Kayle	C	35	African-American	Scorpio
4	Paige	A	49	Asian-American	Libra
5	stehany	C	32	American	Virgo
6	Jon	A	47	Hispanic	Leo
7	Charles	B	40	African-American	Caner

Conclusion:

In this post we have seen how to append the dictionary as row and column in an existing dataframe, we have used pandas.from_dict() function to create the dataframe from the dictionary, the orient parameter index and columns let you decide whether you want to add the values from dictionary as rows or columns.

We have also seen how using pd.series() we can add the dictionary as column.