How to draw a multiple line chart using plotly_express?

With version 4.8 of Plotly.py, the code in the original question is now supported almost unmodified:

pd.options.plotting.backend = "plotly"
df.plot(x='date', y=['sessions', 'cost'])

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Previous answer, as of July 2019

For this example, you could prepare the data slightly differently.

df_melt = df.melt(id_vars='date', value_vars=['sessions', 'cost'])

If you transpose/melt your columns (sessions, cost) into additional rows, then you can specify the new column 'variable' to partition by in the color parameter.

px.line(df_melt, x='date' , y='value' , color='variable')

Example plotly_express output

With newer versions of plotly, all you need is:

df.plot()

As long as you remember to set pandas plotting backend to plotly:

pd.options.plotting.backend = "plotly"

From here you can easily adjust your plot to your liking, for example setting the theme:

df.plot(template='plotly_dark')

Plot with dark theme:

One particularly awesome feature with newer versions of plotly is that you no longer have to worry whether your pandas dataframe is of a wide or long format. Either way, all you need is df.plot(). Check out the details in the snippet below.

Complete code:

# imports
import plotly.express as px
import pandas as pd
import numpy as np

# settings
pd.options.plotting.backend = "plotly"

# sample dataframe of a wide format
np.random.seed(4); cols = list('abc')
X = np.random.randn(50,len(cols))  
df=pd.DataFrame(X, columns=cols)
df.iloc[0]=0; df=df.cumsum()

# plotly figure
df.plot(template = 'plotly_dark')

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Answer for older versions:

I would highly suggest using iplot() instead if you'd like to use plotly in a Jupyter Notebook for example:

Plot:

Code:

import plotly
import cufflinks as cf
from plotly.offline import download_plotlyjs, init_notebook_mode, plot, iplot
import pandas as pd
import numpy as np


# setup
init_notebook_mode(connected=True)
np.random.seed(123)
cf.set_config_file(theme='pearl')

# Random data using cufflinks
df1 = cf.datagen.lines()
df2 = cf.datagen.lines()
df3 = cf.datagen.lines()
df = pd.merge(df1, df2, how='left',left_index = True, right_index = True)
df = pd.merge(df, df3, how='left',left_index = True, right_index = True)

fig = df1.iplot(asFigure=True, kind='scatter',xTitle='Dates',yTitle='Returns',title='Returns')
iplot(fig)