How to Show a Pandas Dataframe into a Existing Flask HTML Table

How to show a pandas dataframe into a existing flask html table?

working example:

python code:

from flask import Flask, request, render_template, session, redirect
import numpy as np
import pandas as pd


app = Flask(__name__)

df = pd.DataFrame({'A': [0, 1, 2, 3, 4],
                   'B': [5, 6, 7, 8, 9],
                   'C': ['a', 'b', 'c--', 'd', 'e']})


@app.route('/', methods=("POST", "GET"))
def html_table():

    return render_template('simple.html',  tables=[df.to_html(classes='data')], titles=df.columns.values)



if __name__ == '__main__':
    app.run(host='0.0.0.0')

html:

<!DOCTYPE html>
<html lang="en">
<head>
    <meta charset="UTF-8">
    <title>Title</title>
</head>
<body>

{% for table in tables %}
            {{titles[loop.index]}}
            {{ table|safe }}
{% endfor %}
</body>
</html>

or else use

return render_template('simple.html',  tables=[df.to_html(classes='data', header="true")])

and remove {{titles[loop.index]}} line from html

if you inspect element on html

<html lang="en"><head>    <meta charset="UTF-8">    <title>Title</title></head><body style="">

            <table border="1" class="dataframe data">  <thead>    <tr style="text-align: right;">      <th></th>      <th>A</th>      <th>B</th>      <th>C</th>    </tr>  </thead>  <tbody>    <tr>      <th>0</th>      <td>0</td>      <td>5</td>      <td>a</td>    </tr>    <tr>      <th>1</th>      <td>1</td>      <td>6</td>      <td>b</td>    </tr>    <tr>      <th>2</th>      <td>2</td>      <td>7</td>      <td>c--</td>    </tr>    <tr>      <th>3</th>      <td>3</td>      <td>8</td>      <td>d</td>    </tr>    <tr>      <th>4</th>      <td>4</td>      <td>9</td>      <td>e</td>    </tr>  </tbody></table>

</body></html>

Show pandas dataframe in an existing flask html table, and send in parameter for subset in get?

You just need to query your dataframe before making the table.

#not sure why you need POST but Okay
@app.route('/<id>',methods=("POST", "GET"))
def page(id):
    subset_id = id
    df_filtered = df.loc[df["<id_column_name>"]==subset_id]
    return render_template('simple.html', tables=[df_filtered.to_html(classes='data')], titles=df.columns.values)

Flask: How can I add a table with pandas dataframe

panda work with flask its not an issue..
This is the syntax what i used and it works fine...
render_template('index.html') without slash and template is in 'templates' folder

def index():
    data = pd.read_csv("data.csv")
    data.set_index(['Name'], inplace=True)
    data.index.name=None

    df = data.loc[data.Sex=='male']
    df = df[['Sex']]
    return render_template('index.html',tables=[df.to_html(header=False)],titles=['na','Males'])

How to show a pandas dataframe as a flask-boostrap table?

The problem here is with the data.csv file. When you do read_csv() on it:

In [45]: pd.read_csv("/tmp/a.csv")
Out[45]: 
  Name    Birth Month Origin  Age Gender
0                  Carly   Jan Uk  10  F
1                  Rachel  Sep UK  20  F
2                  Nicky   Sep MEX 30  F
3                  Wendy   Oct UK  40  F
4                  Judith  Nov MEX 39  F

In [46]: df = pd.read_csv("/tmp/a.csv")

In [47]: df.columns
Out[47]: Index([u'Name    Birth Month Origin  Age Gender'], dtype='object')

As you can see, there is only one column, instead of four, because it can't understand that 'Birth Month' is supposed to be one column. To fix this, you can open the file and change the first line to:

"Name" "Birth Month" "Origin"  "Age" "Gender"

And, then while reading the csv:

In [62]: pd.read_csv("/tmp/a.csv", sep='\s+', quotechar='"')
Out[62]: 
     Name Birth Month Origin  Age Gender
0   Carly         Jan     Uk   10      F
1  Rachel         Sep     UK   20      F
2   Nicky         Sep    MEX   30      F
3   Wendy         Oct     UK   40      F
4  Judith         Nov    MEX   39      F

Or you could have also just changed Birth Month to Birth_Month

For the '404 Not Found' error, the problem is that you have not defined any route for '/'. So, (after editing the header of the csv) I would do something like:

from flask import *
import pandas as pd
app = Flask(__name__)

@app.route("/tables")
def show_tables():
    data = pd.read_csv("/tmp/a.csv", sep='\s+', quotechar='"')
    data.set_index(['Name'], inplace=True)
    data.index.name=None
    females = data.loc[data.Gender=='F']
    return render_template('view.html',tables=[females.to_html(classes='female')],

    titles = ['na', 'Female surfers'])

@app.route("/")
def show_home():
    return "Hello Guys! Visit: <a href='/tables'> this link </a>"

if __name__ == "__main__":
    app.run(debug=True)

Pandas Dataframe display on a webpage

The following should work:

@app.route('/analysis/<filename>')
def analysis(filename):
    x = pd.DataFrame(np.random.randn(20, 5))
    return render_template("analysis.html", name=filename, data=x.to_html())
                                                                # ^^^^^^^^^

Check the documentation for additional options like CSS styling.

Additionally, you need to adjust your template like so:

{% extends "base.html" %}
{% block content %}
<h1>{{name}}</h1>
{{data | safe}}
{% endblock %}

in order to tell Jinja you're passing in markup. Thanks to @SeanVieira for the tip.

Flask return pd dataframe groupby - how to delete column that is used to group?

Try this:

import io
import pandas

from flask import Flask, jsonify

# Create a flask app
app = Flask(__name__)


@app.route("/")
def index():

    # Your data
    data = io.StringIO(
    """
    id   VALUE1  VALUE2  VALUE3
    1         1      11     abc
    2         1      22     def
    3         2      33     ghi
    4         2      44     jkl
    """
    )
    df = pandas.read_table(data, sep="\s+")

    # Create a placeholder for the output
    output = {}

    # Loop all the groups in your groupby
    for group_id, group in df.groupby('VALUE1'):

        # Add a dict representation of the group to the output, without the columns you don't want
        output[group_id] = group.drop(columns=["VALUE1", "id"]).to_dict(orient="records")


    # Return the output in JSON format
    return jsonify(output)


if __name__ == "__main__":
    app.run(debug=True)

Output:

{
  "1": [
    {
      "VALUE2": 11, 
      "VALUE3": "abc"
    }, 
    {
      "VALUE2": 22, 
      "VALUE3": "def"
    }
  ], 
  "2": [
    {
      "VALUE2": 33, 
      "VALUE3": "ghi"
    }, 
    {
      "VALUE2": 44, 
      "VALUE3": "jkl"
    }
  ]
}

pandas/flask: buttons to download dataframes

What ended up working was including the file-creation commands in the first view along with the dataframes, then setting a session variable to pass the file name of the output file to the download view.

def df_test():
    df1 = pd.DataFrame(
        {
        'terms' : ['term1','term2'],
        'code1': ['1234x', '4321y'],
        'code2': ['2345x','5432y'],
        'code3': ['3456x','6543y']
        }
        )
    df2 = pd.DataFrame(
         {
        'name': ['Dan','Sara','Conroy'],
        'rate': ['3','3.5','5.2'],
        'location': ['FL','OH','NM'],
        'code': ['4444g','6543y','2345x']                           
         })
    writer = pd.ExcelWriter(output_file, engine='xlsxwriter')
    df1.to_excel(writer, sheet_name="Codes")
    df2.to_excel(writer, sheet_name="People")
    workbook  = writer.book
    worksheet1 = writer.sheets['Codes']
    worksheet2 = writer.sheets['People']
    writer.save()
    return render_template('view.html',tables=[df1.to_html(classes='female'), df2.to_html(classes='male')],
    titles = ['na', 'Codes', 'People'])
    output_file = 'codes_people.xlsx'

    session['otpt_file'] = 'tmp/' + output_file


def download_df():
    output_file = session.get('otpt_file', None)
    #return output_file
    return send_file(output_file, attachment_filename='output.xlsx', as_attachment=True,mimetype='text/xlsx')

How to Show a Pandas Dataframe into a Existing Flask HTML Table