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<a href="dataplot-module.html">Package dataplot</a> ::
Package R
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<h2 class="package">Package dataplot.R</h2>
Plots using R base graphics code and the rpy backend.
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<b><a href="dataplot.R.barplot-class.html"><code>barplot</code></a></b></td>
<td>Standard boring barplot.</td></tr>
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<b><a href="dataplot.R.CorrScatter-class.html"><code>CorrScatter</code></a></b></td>
<td>Scatterplot used to judge correlation between 2 variables.</td></tr>
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<b><a href="dataplot.R.Histogram-class.html"><code>Histogram</code></a></b></td>
<td>generic histogram for showing a univariate distribution.</td></tr>
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<b><a href="dataplot.R.multi_time_series-class.html"><code>multi_time_series</code></a></b></td>
<td>Multiple time series superimposed for comparison.</td></tr>
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<b><a href="dataplot.R.NormalQQPlot-class.html"><code>NormalQQPlot</code></a></b></td>
<td>Use to see if univariate data are approximately normal.</td></tr>
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<b><a href="dataplot.R.Plot-class.html"><code>Plot</code></a></b></td>
<td>R plot for the web.</td></tr>
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<b><a href="dataplot.R.Scatter-class.html"><code>Scatter</code></a></b></td>
<td>Simple x-y scatterplot.</td></tr>
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<b><a href="dataplot.R.SquareScatter-class.html"><code>SquareScatter</code></a></b></td>
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<b><a href="dataplot.R.TimeSeries-class.html"><code>TimeSeries</code></a></b></td>
<td>Simple cumulative time series.</td></tr>
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<td><code><span class="summary-sig"><a href="dataplot.R-module.html#values_to_df" class="summary-sig-name"><code>values_to_df</code></a>(<span class=summary-sig-arg>values</span>)</span></code>
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Django values list of dicts -> R data.frame</td></tr>
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<h3><span class="sig"><span class="sig-name">values_to_df</span>(<span class=sig-arg>values</span>)</span>
</h3>
<p>Django values list of dicts -> R data.frame</p>
This makes writing Django and R code easy, since querysets and
data.frames are the native ways of describing data tables in the
respective programming paradigms.
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