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1. #Python ffmpeg install matplotlib mp4#
2. #Python ffmpeg install matplotlib full#
3. #Python ffmpeg install matplotlib code#
4. #Python ffmpeg install matplotlib windows#

Renderer = _renderer()ĪttributeError: 'FigureCanvasBase' object has no attribute 'get_renderer'ĭuring handling of the above exception, another exception occurred:įile "/Users/_/PycharmProjects/data_visualization/venv/lib/python3.6/site- packages/bar_chart_race/_make_chart.py", line 435, in make_animation

#Python ffmpeg install matplotlib mp4#

Second, you can create a GIF animated image from your MP4 file using or similar services.MovieWriter ffmpeg unavailable using Pillow instead.įile "/Users/_/PycharmProjects/data_visualization/venv/lib/python3.6/site- packages/matplotlib/animation.py", line 251, in savingįile "/Users/_/PycharmProjects/data_visualization/venv/lib/python3.6/site- packages/matplotlib/animation.py", line 1161, in saveįile "/Users/_/PycharmProjects/data_visualization/venv/lib/python3.6/site- packages/matplotlib/animation.py", line 549, in grab_frame And the loop attribute allows playing the video indefinitely. The controls attribute adds video controls, like play, pause, zoom, and volume. If they are not set, the page might flicker while the video loads. It’s a good idea to include width and height attributes.

#Python ffmpeg install matplotlib full#

You can download the notebook on GitHub to get the full code.įirst, you can embed it in your HTML using the tag: That’s it, our Matplotlib bar chart races are ready. It will be located in the same folder that contains our notebook with the bar chart race code.

#Python ffmpeg install matplotlib code#

The result of this code will be an MP4 file.

n_bars=7 sets the number of bars displayed in the chart (in our example, the library displays the top 7 countries with the highest values for each year).filename='refugees.mp4' is the name of the MP4 file with the output.Here are variables you may want to change: Title='Refugees in the United States, 2006–2015', Run this code to generate bar chart races: Now we’ve reached the most interesting part.

Read also my article 50+ Pandas Tricks to learn more about manipulations with datasets. Its index contains the time component, each row represents a period of time, and every column holds the value for a particular category. The data above is an example of properly formatted data to create bar chart races. 'North America', 'Oceania', 'South America'], axis = 1) Next, we’ll delete commas, convert integers to numeric type, transpose the table, and drop columns we don’t need:ĭata.replace(',','', regex=True, inplace=True)ĭata = data.apply(pd.to_numeric, errors='coerce', axis=1)ĭata = data.drop(['Other', 'Unknown', 'Total', 'Africa', 'Asia', 'Europe', Infer_datetime_format=1, parse_dates=True) The code below would read the file, determine which values to read as NaN, and parse dates: For this, we’ll use Kaggle’s “Refugees in the United States, 2006–2015” dataset, namely the refugee_status.csv file.įrom now on, we’ll be working in a Jupyter Notebook.įirst, import all the necessary libraries: We’ll generate our bar chart race from a CSV file. After installing, you may need to restart your computer. If, while installing FFmpeg, the system requires the vulkan-1.dll file, you can download it, rename it to vulkan-1.dll, put it into your C:\Windows\System32 folder (or the like), and run the C:\ffmpeg\bin\ffmpeg.exe -codecs command again. Pip install numpy scipy matplotlib ipython jupyter pandas sympy noseĪnd here’s the command to install Bar Chart Race with pip:Ĭonda install -c conda-forge bar_chart_raceįinally, download FFmpeg and install it using an instruction manual. To install Pandas, Matplotlib, and Jupyter Notebook, you’ll need to install recommended Scientific Python Distributions.

#Python ffmpeg install matplotlib windows#

You can download the latest version of Python for Windows on the official website. FFmpeg: a tool to generate a video file with the animated chart.Jupyter Notebook: an online editor for data visualization.Bar Chart Race: a library to create bar chart races with Matplotlib.Pandas: a library to prepare data for plotting.pip: package management system (it comes with Python) (alternatively, you can use Conda).See the final bar chart race video in a new window.

To create a chart of this type, you usually need a dataset that includes dates, categories (like countries, names, titles, etc.), and numeric values. An animated bar chart race helps visualize the change in trends over time.