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content/posts/170526-bar-charts-bokeh.markdown

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@@ -3,7 +3,7 @@ slug: responsive-bar-charts-bokeh-flask-python-3
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meta: How to build responsive bar charts with the Bokeh data visualization library, Flask and Pyton 3.
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category: post
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date: 2017-05-26
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modified: 2017-05-26
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modified: 2017-07-30
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headerimage: /img/170526-bar-charts-bokeh-flask/header.jpg
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headeralt: Python, Flask and Bokeh logos.
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@@ -88,8 +88,8 @@ pip install bokeh==0.12.5 flask==0.12.2 pandas==0.20.1
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```
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After a brief download and installation period our required dependencies
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should be installed within our virtualenv. Look for output like the
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following to confirm everything worked.
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should be installed within our virtualenv. Look for output to confirm
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everything worked.
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```
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Installing collected packages: six, requests, PyYAML, python-dateutil, MarkupSafe, Jinja2, numpy, tornado, bokeh, Werkzeug, itsdangerous, click, flask, pytz, pandas
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chart to the rendered page.
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Create a folder for your project then within it create a file named
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`app.py` with the following initial contents:
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`app.py` with these initial contents:
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```python
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from flask import Flask, render_template
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visualizations.
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We just need a few updates to our `templates/chart.html` file to display
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the visualization. Open the file and add the folloiwng 6 lines to the file.
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the visualization. Open the file and add these 6 lines to the file.
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Two of these lines are for the required CSS, two are JavaScript Bokeh
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files and the remaining two are the generated chart.
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## Adding a Hover Tool
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Within `app.py` modify the `create_hover`_tool to match the following
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Within `app.py` modify the `create_hover_tool` to match the following
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code.
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```python

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