Create Pandas DataFrame in Python (4 Examples)

Create Pandas DataFrame in Python (4 Examples)

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In this tutorial, you will learn how to create Pandas DataFrame in Python with multiple examples.

Example 1: Create Pandas DataFrame from a CSV in Python

In the following example, it will make the SFrame to CSV and then create the DataFrame from CSV:

sf = sframe.SFrame('yourFolder/')'yourFolder/big_data.csv', format='csv')
df = pandas.read_csv('yourFolder/big_data.csv.csv')

Example 2: Create DataFrame from HTML Data

Below example shows how to create Pandas DataFrame from the HTML data:

import pandas as pd
from bs4 import BeautifulSoup

html_doc = """

soup = BeautifulSoup(html_doc, "html.parser")

car_names = soup.find_all("h3")

data = []
for name in car_names:
    data.append({"Car Name": name.text})

df = pd.DataFrame(data)


Car Name
0     Ford
1   Toyota
2    Škoda

Example 3: Creating a DataFrame by Merging 2 Dictionaries in Python

The below example will merge the two dictionaries and will create a DataFrame:

adBasicInfo = {} # dictionary
adOtherInfo = {} # 2.nd dictionary
adFullInfo = {}  # Merged dictionary
adFullList = []  # List for appending merged dictionaries

# In each iteration merge dicts and append them in the list
 for div in soup.findAll('a', {'class': 'result'}):
           ..some code...
            adBasicInfo = {
                              u'adThumbImg':...some code...,
                              u'adCounty':...some code...

        adOtherInfo = getFullAdInfo(adLink)      # Get complex dict      
        adFull = {**adBasicInfo,**adOtherInfo} # Merge dicts
        adFullList.append(adFull)              # Append dicts to list

# Save final version of list as pandas dataframe
adFullDF = pd.DataFrame(data=adFullList) # Save final list to dataframe

Example 4: Create Pandas DataFrame from Excel File

Below Python code will create the Pandas DataFrame from an Excel file:

import pandas as pd

data = pd.read_excel(r'YourExcelFilePath\Filename.xlsx') 
df = pd.DataFrame(data, columns = ['Column1','Column2','Column3',...])

print (df)

See also: