In this post, we will see examples of saving a Pandas dataframe as Excel file. Pandas has to_excel() function to write a dataframe into Excel file.
Let us load Pandas.
# load pandas import pandas as pd
We will create two lists and us these to create a dataframe as before.
education = ["Bachelor's", "Less than Bachelor's","Master's","PhD","Professional"] salary = [110000,105000,126000,144200,96000]
We can create a Pandas dataframe using the two lists to make a dictionary with DataFrame() function. Our toy dataframe contains two columns.
# Create dataframe in one step
df = pd.DataFrame({"Education":education,
"Salary":salary})
df
Education Salary
0 Bachelor's 110000
1 Less than Bachelor's 105000
2 Master's 126000
3 PhD 144200
4 Professional 95967
Now we have the dataframe ready and we can use Pandas’ to_excel() function to write the dataframe to excel file. In the example, below we specify the Excel file name as argument to to_excel() function.
# wrkite dataframe to excel file
df.to_excel("education_salary.xls")
Pandas to_excel() function has number of useful arguments to customize the excel file. For example, we can save the dataframe as excel file without index using “index=False” as additional argument.
# wrkite dataframe to excel file with no index
df.to_excel("education_salary.xls", index=False)
One of the common uses in excel file is naming the excel sheet. We can name the sheet using “sheet_name” argument as shown below.
# write dataframe to excel file with sheet name
df.to_excel("education_salary.xls",
index=False,
sheet_name="data")
This post is part of the series on Byte Size Pandas: Pandas 101, a tutorial covering tips and tricks on using Pandas for data munging and analysis.
