CODEWITHSUNDEEP
csvpandasjupyter-notebook
Tom Slee
Tom Slee

Reputation: 960

Download CSV from an iPython Notebook

I run an iPython Notebook server, and would like users to be able to download a pandas dataframe as a csv file so that they can use it in their own environment. There's no personal data, so if the solution involves writing the file at the server (which I can do) and then downloading that file, I'd be happy with that.

Upvotes: 35

Views: 71049

Answers (7)

Maria Rodriguez
Maria Rodriguez

Reputation: 9

The simple method that I found was:

df.to_csv('~/Desktop/file_name.csv')

Upvotes: 0

Paul Rougieux
Paul Rougieux

Reputation: 11399

A function that creates a csv download link, based on Coen Jonker's answer and similar to Yasin Zähringer's answer except that it uses IPython.display.FileLink so that there is no need to create html code.

The function has an optional delete prompt so you can delete the file after download to keep the notebook server clean.

# Import a module to create a data frame
import pandas
# Import a module to display a link to the file
from IPython.display import FileLink
# Import a module to delete the file
import os
# Create a download function
def csv_download_link(df, csv_file_name, delete_prompt=True):
    """Display a download link to load a data frame as csv within a Jupyter notebook

    Parameters
    ----------
    df : pandas data frame
    csv_file_name : str
    delete_prompt : bool
    """
    df.to_csv(csv_file_name, index=False)
    display(FileLink(csv_file_name))
    if delete_prompt:
        a = input('Press enter to delete the file after you have downloaded it.')
        os.remove(csv_file_name)

# Create an example data frame
df = pandas.DataFrame({'x':[1,2,3],'y':['a','b','c']})
# Use the function to diplay a download link
csv_download_link(df, 'file_name.csv')

This is mostly for people who use jupyter notebooks on their own machine. On a shared machine, the use of os.remove might be problematic depending on how you set up file write permissions.

Upvotes: 4

Coen Jonker
Coen Jonker

Reputation: 451

How about using the FileLinks class from IPython? I use this to provide access to data directly from Jupyter notebooks. Assuming your data is in pandas dataframe p_df:

from IPython.display import FileLink, FileLinks

p_df.to_csv('/path/to/data.csv', index=False)
p_df.to_excel('/path/to/data.xlsx', index=False)

FileLinks('/path/to/')

Run this as a notebook cell and the result will be a list of links to files downloadable directly from the notebook. '/path/to' needs to be accessible for the notebook user of course.

Upvotes: 44

Ash Upadhyay
Ash Upadhyay

Reputation: 1966

My simple approach to download all the files from the jupyter notebook would be by simply using this wonderful command

!tar cvfz my_compressed_file_name.tar.gz *

This will download all the files of the server including the notebooks.

In case if your server has multiple folders, you might be willing to use the following command. write ../ before the * for every step up the directory.

tar cvfz zipname.tar.gz ../../*

Hope it helps..

Upvotes: -1

Yasin Zähringer
Yasin Zähringer

Reputation: 641

For not too large tables you can use the following code:

import base64
import pandas as pd
from IPython.display import HTML

def create_download_link( df, title = "Download CSV file", filename = "data.csv"):
    csv = df.to_csv()
    b64 = base64.b64encode(csv.encode())
    payload = b64.decode()
    html = '<a download="{filename}" href="data:text/csv;base64,{payload}" target="_blank">{title}</a>'
    html = html.format(payload=payload,title=title,filename=filename)
    return HTML(html)

df = pd.DataFrame(data = [[1,2],[3,4]], columns=['Col 1', 'Col 2'])
create_download_link(df)

Upvotes: 37

Kim C.
Kim C.

Reputation: 151

If you want to avoid storing CSVs on the server, you can use this Javascript alternative that create the CSV on the client-side:

from IPython.display import Javascript
js_download = """
var csv = '%s';

var filename = 'results.csv';
var blob = new Blob([csv], { type: 'text/csv;charset=utf-8;' });
if (navigator.msSaveBlob) { // IE 10+
    navigator.msSaveBlob(blob, filename);
} else {
    var link = document.createElement("a");
    if (link.download !== undefined) { // feature detection
        // Browsers that support HTML5 download attribute
        var url = URL.createObjectURL(blob);
        link.setAttribute("href", url);
        link.setAttribute("download", filename);
        link.style.visibility = 'hidden';
        document.body.appendChild(link);
        link.click();
        document.body.removeChild(link);
    }
}
""" % data_in_dataframes.to_csv(index=False).replace('\n','\\n').replace("'","\'")

Javascript(js_download)

Basically, it creates a CSV string in python from the pd dataframe and use it in a small js script that creates a CSV file on the client side and open a saving dialog to save it on the user computer. I tested in my iPython env and it works like a charm!

Note that I am escaping the \n. If I don't do so, the js script string will have the CSV variable written on multiple lines.

For example, print "var csv = '%s'" % industries_revenues.to_csv(index=False).replace('\n','\\n') results to this:

var csv = 'Industry,sum_Amount\nBanking,65892584.0\n(...)Finance,20211917.0\n'

Instead of print "var csv = '%s'" % industries_revenues.to_csv(index=False) without the \n escaping that results on a multiple lined and therefore errored javascript:

var csv = 'Industry,sum_Amount
Banking,65892584.0
(...)
Finance,20211917.0
'

I also escape the ' not to break the variable string in javascript.

Upvotes: 11

frankjania
frankjania

Reputation: 21

You can use the fact that the notebook can display html for objects, and data urls, to make the content of a csv downloadable:

import urllib

class CSV(object):
    def _repr_html_(self):
        html = []

        html.append("{},{},{}".format(
                "user",
                "age",
                "city"
            )
        )

        html.append("{},{},{}".format(
                "Alice",
                "39",
                "New York"
            )
        )

        html.append("{},{},{}".format(
                "Bob",
                "30",
                "Denver"
            )
        )

        html.append("{},{},{}".format(
                "Carol",
                "27",
                "Tulsa"
            )
        )


        export = '\n'.join(html)
        export = urllib.quote(export.encode("utf-8"))
        csvData = 'data:application/csv;charset=utf-8,' + export
        return "<a download='export.csv' href='{}' target='_blank'>csv file</a>".format(csvData)

CSV()

Upvotes: 1

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