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<meta name="description" content="usage: eval [-q QUERY [QUERY ...]] [-h] [--export EXPORT] Create custom data column from loaded datasets. Can be mathematical expressions supported by pandas.eval() function. Example. If I have loaded fred dgs2 dgs5 and I want to create a new column that is the difference between these two, I can create a new column by doing eval spread = dgs2 - dgs5.
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Note that for division, the / operator will cause issues, so one should do *N**-1 where N is the number you are dividing by">
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<meta name="description" content="usage: eval [-q QUERY [QUERY ...]] [-h] [--export EXPORT] Create custom data column from loaded datasets. Can be mathematical expressions supported by pandas.eval() function. Example. If I have loaded fred DGS2,DGS5 and I want to create a new column that is the difference between these two, I can create a new column by doing eval spread = DGS2 - DGS5.
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Notice that the command is case sensitive, i.e., DGS2 is not the same as dgs2.">
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@@ -47214,8 +47214,9 @@ code, img {
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<h1>Eval</h1>
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<pre><code>usage: eval [-q QUERY [QUERY ...]] [-h] [--export EXPORT]
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</code></pre><p>Create custom data column from loaded datasets. Can be mathematical expressions supported by pandas.eval() function.
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Example. If I have loaded <code>fred dgs2 dgs5</code> and I want to create a new column that is the difference between these two,
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I can create a new column by doing <code>eval spread = dgs2 - dgs5</code>.</p>
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Example. If I have loaded <code>fred DGS2,DGS5</code> and I want to create a new column that is the difference between these two,
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I can create a new column by doing <code>eval spread = DGS2 - DGS5</code>.</p>
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<p>Notice that the command is case sensitive, i.e., <code>DGS2</code> is not the same as <code>dgs2</code>.</p>
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<p>Note that for division, the / operator will cause issues, so one should do <code>*N**-1</code> where N is the number you are dividing by</p>
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<pre><code>options:
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-q QUERY [QUERY ...], --query QUERY [QUERY ...]
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