You may use the following template to convert a dictionary to Pandas DataFrame:
import pandas as pd
my_dict = {key:value,key:value,key:value,...}
df = pd.DataFrame(list(my_dict.items()),columns = ['column1','column2'])
In this short tutorial, you’ll see the complete steps to convert a dictionary to a DataFrame.
Steps to Convert a Dictionary to Pandas DataFrame
Step 1: Gather the Data for the Dictionary
To start, gather the data for your dictionary.
For example, let’s gather the following data about products and prices:
| Product | Price |
| Computer | 1500 |
| Monitor | 300 |
| Printer | 150 |
| Desk | 250 |
Step 2: Create the Dictionary
Next, create the dictionary.
For our example, you may use the following code to create the dictionary:
my_dict = {'Computer':1500,'Monitor':300,'Printer':150,'Desk':250}
print (my_dict)
print (type(my_dict))
Run the code in Python, and you’ll get the following dictionary:
{'Computer': 1500, 'Monitor': 300, 'Printer': 150, 'Desk': 250}
<class 'dict'>
Notice that the syntax of print (type(my_dict)) was add at the bottom of the code to confirm that we indeed got a dictionary.
Step 3: Convert the Dictionary to a DataFrame
For the final step, convert the dictionary to a DataFrame using this template:
import pandas as pd
my_dict = {key:value,key:value,key:value,...}
df = pd.DataFrame(list(my_dict.items()),columns = ['column1','column2'])
For our example, here is the complete Python code to convert the dictionary to a DataFrame:
import pandas as pd
my_dict = {'Computer':1500,'Monitor':300,'Printer':150,'Desk':250}
df = pd.DataFrame(list(my_dict.items()),columns = ['Products','Prices'])
print (df)
print (type(df))
As you can see, the dictionary got converted to Pandas DataFrame:
Products Prices
0 Computer 1500
1 Monitor 300
2 Printer 150
3 Desk 250
<class 'pandas.core.frame.DataFrame'>
Note that the syntax of print (type(df)) was added at the bottom of the code to confirm that we actually got a DataFrame.