How to Convert a Dictionary to a DataFrame

Dictionary is a built-in data structure of Python, which consists of key-value pairs. In this short how-to article, we will learn how to convert a dictionary to a DataFrame in Pandas and PySpark.

Pandas DataFrame from Dictionary .dict()

The DataFrame constructor can be used to create a DataFrame from a dictionary. The keys represent the column names and the dictionary values become the rows.

import pandas as pd

# create a dictionary
A = {
    "name": ["John", "Jane"],
    "age": [20, 24]
}

# convert to a DataFrame
df = pd.DataFrame(A)				

PySpark DataFrame from Dictionary .dict()

Although there exist some alternatives, the most practical way of creating a PySpark DataFrame from a dictionary is to first convert the dictionary to a Pandas DataFrame and then converting it to a PySpark DataFrame.

import pandas as pd
spark = SparkSession.builder.getOrCreate()

# create a dictionary
A = {
    "name": ["John", "Jane"],
    "age": [20, 24]
}

# convert to a Pandas DataFrame
df = pd.DataFrame(A)

# from Pandas to PySpark
df_pyspark = spark.createDataFrame(df)

This question is also being asked as:

• Convert dict of scalars to Pandas DataFrame

People have also asked for:

• Selecting multiple columns in a Pandas DataFrame
• How to change the order of DataFrame columns?
• Delete a column from a Pandas DataFrame

Aporia Team

Sometimes, writing is a joint effort.

building a RAG app?

Read about Aporia’s AI Guardrails

Learn more