<commit_before># ``pdvega``

This package is an experiment in making [vega](https://vega.github.io/) and [vega-lite](https://vega.github.io/vega-lite/) plots easier to generate in Python.

Pandas currently has a built-in set of [Visualization tools](https://pandas.pydata.org/pandas-docs/stable/visualization.html) based on matplotlib. So, for example, you can create a plot this way:

```python
import numpy as np
import pandas as pd

df = pd.DataFrame({'x': np.random.randn(100), 'y': np.random.randn(100)})
df.plot.scatter(x='x', y='y')
```

![matplotlib scatter output](images/mpl-scatter.png?raw=true)

The goal of ``pdvega`` is that any time you use ``df.plot``, you'll be able to replace it with ``pd.vgplot`` and instead get a similar (but not identical) outpuut in Vega or Vega-Lite:

```
import pdplot  # import adds pdplot attribute to pandas
df.vgplot.scatter(x='x', y='y')
```
<commit_msg>Adjust code formatting in README<commit_after># ``pdvega``

This package is an experiment in making [vega](https://vega.github.io/) and [vega-lite](https://vega.github.io/vega-lite/) plots easier to generate in Python.

Pandas currently has a built-in set of [Visualization tools](https://pandas.pydata.org/pandas-docs/stable/visualization.html) based on matplotlib. So, for example, you can create a plot this way:

```python
import numpy as np
import pandas as pd

df = pd.DataFrame({'x': np.random.randn(100), 'y': np.random.randn(100)})
df.plot.scatter(x='x', y='y')
```

![matplotlib scatter output](images/mpl-scatter.png?raw=true)

The goal of ``pdvega`` is that any time you use ``df.plot``, you'll be able to replace it with ``pd.vgplot`` and instead get a similar (but not identical) outpuut in Vega or Vega-Lite:

```python
import pdplot  # import adds pdplot attribute to pandas

df.vgplot.scatter(x='x', y='y')
```

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