in this python tutorial, I’ll share the python script to export dataframe into CSV format. Pandas is an open-source library that is built on top of the NumPy library.
CSV(comma-separated values) is the most common file format for storing plain text data. It is one of the most widely used data exchange formats between servers. Each data value is separated by a comma in the CSV files.
Exporting the DataFrame into a CSV file
The to_csv() method in Pandas exports a DataFrame to CSV format. The output will be a CSV file if a file option is provided. Otherwise, the return value is a string in CSV format.
What is Pandas DataFrame
Pandas DataFrames produce a data structure in Excel with labeled axes (rows and columns). To create a DataFrame, you’ll need at least the data rows and column names as header.
The sample example:
| Name | Age |
|---|---|
| John | 34 |
| Saroj | 29 |
| Adam | 24 |
Python Script To save Datatframe to CSV
Let’s create a python script that’ll save panda’s dataframe into the CSV.
import pandas as p
# list of name, age
emp_name = ["John", "Saroj", "Adam"]
age = [34, 29, 24]
# dictionary of lists
dict = {'name': emp_name, 'age': age}
df = p.DataFrame(dict)
# saving the dataframe
df.to_csv('file_name.csv')Let’s have a look at some of the program’s key features:
- Step 1: Defined emp_name and age list.
- Step 2: Created dict using above list.
- Step 3: Created dataframe using
DataFrame()method. - Step 4: save pandas dataframe into CSV using
to_csv()method
Let’s have a look at some common examples for Dataframe To CSV
Save CSV in relative path
saving the csv file into the relative path.
dt.to_csv('C:/Users/abc/Desktop/file_name.csv')
Custom Separator
we are passing separator tab.
dt.to_csv('file_name.csv',sep='\t')
Set missing value
We are setting the missing value is NAN.
dt.to_csv('file_name.csv',na_rep='NAN')
Enable Row Index
We can also enable/disable row index.
dt.to_csv('file_name.csv',index=False)
