Экспорт фрейма данных Pandas в файл CSV
Suppose you are working on a Data Science project and you tackle one of the most important tasks, i.e, Data Cleaning. After data cleaning, you don’t want to lose your cleaned data frame, so you want to save your cleaned data frame as a CSV. Let us see how to export a Pandas DataFrame to a CSV file.
Pandas enable us to do so with its inbuilt to_csv() function.
First, let’s create a sample data frame
# importing the moduleimport pandas as pd # making the datascores = {"Name": ["a", "b", "c", "d"], "Score": [90, 80, 95, 20]} # creating the DataFramedf = pd.DataFrame(scores) # displaying the DataFrameprint(df) |
Output :

Now let us export this DatFrame as a CSV file named your_name.csv :
# converting to CSV filedf.to_csv("your_name.csv") |
Output

File Successfully saved

In case you get a UnicodeEncodeError, just pass the encoding parameter with ‘utf-8’ value.
# converting to CSV filedf.to_csv("your_name.csv", encoding = "utf-8") |
Possible Customizations
1. Include index number
You can choose if you want to add automatic index. The default value is True. To set it to False.
# converting to CSV filedf.to_csv("your_name.csv", index = False) |
Output :
2. Export only selected columns
If you want to export only a few selected columns, you may pass it in to_csv() as ‘columns = [“col1”, “col2”]
# converting to CSV filedf.to_csv("your_name.csv", columns = ["Name"]) |
Output :
3. Export header
You can choose if you want your column names to be exported or not by setting the header parameter to True or False. The default value is True.
# converting to CSV filedf.to_csv("your_name.csv", header = False) |
Output :
4. Handle NaN
In case your data frame has NaN values, you can choose it to replace by some other string. The default value is ”.
# converting to CSV filedf.to_csv("your_name.csv", na_rep = "nothing") |
5. Seperate with something else
If instead of separating the values with a ‘comma’, we can separate it using custom values.
# converting to CSV file# seperated with tabsdf.to_csv("your_name.csv", sep =" ") |
Output :
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