Plotly does not natively handle Python Pandas DataFrames. To make Plotly work with these, you’ll need to convert those to dictionaries first or use plugins.
A large collection of charts is available in this public repository and grouped into these categories:
Note: Plotly is free, and they offer paid versions including the Chart Studio platform where they say you can create charts without programming. That’s slightly misleading, as you would still need to write code to transform the data, but you can try that for yourself.
Plotly Python example with code and data
First, you need to use Zeppelin or Jupyter notebook for a graphical environment in which you can both draw charts and display graphics.
Then, add Plotly to Python like this.
pip install plotly==4.2.1
The code, explained
Before we get into the code, a couple notes:
- There might be some delay in generating the chart or it might not generate at all. We tested this code with Safari and Chrome browsers. If you search online, you’ll get conflicting instructions on how to display graphs in different graphical environments. If you’re still having problems generating a chart, get in touch with us at email@example.com, include your OS and browser details, and we’ll take a look.
Now for the complete code. The data we use is diet information over an 8-day period. The first part looks like this:
Next, we import a CSV file, then plot x and y, where x is the date and y is a chosen column:
Date was originally a column but since we grouped and summed the data by date…
daily = df.groupby('Date').sum()
…it became the dataframe index, so we use daily.index.values to get the values.
This is a simple bar chart (go.Bar) with x and y values.
from plotly.offline import plot import pandas as pd df = pd.read_csv("/home/ubuntu/Downloads/diet.csv") daily = df.groupby('Date').sum() import plotly.graph_objects as go fig = go.Figure( data=[go.Bar(x=daily.index.values,y=daily['Carbohydrates (g)'])], layout_title_text="A Figure Displayed with fig.show()" ) fig.show()