You need to import aes: from ggplot import aes Alternatively, you can just import everything in the ggplot namespace: from ggplot import * ...

python,matplotlib,seaborn,python-ggplot

The first part of your question can be done using colorbar and specifying the colours to be the Cluster array. I have vaguely understood the second part of your question, but I believe this is what you are looking for. import numpy as np import matplotlib.pyplot as plt x =...

python,python-2.7,matplotlib,ggplot2,python-ggplot

This is now available in version 0.5.3 (I just pushed this). >>> from ggplot import * >>> import numpy as np >>> import pandas as pd >>> df = pd.DataFrame({ "x": np.arange(0, 10), "y": np.arange(0, 1, 0.1) }) >>> ggplot(df, aes(x='x', y='y')) +\ ... geom_point() +\ ... scale_y_continuous(labels='percent') ...

This is more of a workaround but you can use qplot for quick, shorthand plots using series. from ggplot import * qplot(meat.beef) ...

Use parameters "binwidth", "limits" and "breaks" like this : ggplot.ggplot(ggplot.aes(x='pips', weight='events'), frame) + ggplot.geom_bar(binwidth=1) + ggplot.scale_x_continuous(limits = (1,6), breaks = range(1,7)) Which gives me : ...

I assume you are referring to the ggplot package from http://ggplot.yhathq.com/? There does not seem to be any equivalent to the theme_set function of the ggplot2 R package, the default theme is currently hardcoded to be theme_grey(). I think the best you can do is to define your theme in...

How about: ggplot(aes(x='date', y='entries_sum'), data=data) + geom_bar(stat='identity') ...

You probably need to install ggplot via the terminal first. Assuming you already have pip installed, run this in the terminal:$ pip install ggplot You should see the package download. Then go back to your notebook and run your same commands again. ...