How to get mean of rows selected with another column's values in pandas
<p>I am trying to get calculate the mean for Score 1 only if column <code>Dates</code> is equal to <code>Oct-16</code>:</p>

<p><a href="https://i.stack.imgur.com/PR8jf.png" rel="nofollow"><img src="https://i.stack.imgur.com/PR8jf.png" alt="enter image description here"></a></p>

<p>What I originally tried was:</p>

<pre><code> import pandas as pd
 import numpy as np
 import os

 dataFrame = pd.read_csv("test.csv")

 for date in dataFrame["Dates"]:
    if date == "Oct-16":
        print(date)##Just checking
        print(dataFrame["Score 1"].mean())
</code></pre>

<p>But my results are the mean for the whole column <code>Score 1</code></p>

<p>Another thing I tried was manually telling it which indices to calculate the mean for:</p>

<pre><code>dataFrame["Score 1"].iloc[0:2].mean()
</code></pre>

<p>But ideally I would like to find a way to do it if <code>Dates == "Oct-16"</code>.</p>

<p>How about the mean for all dates</p>

<pre><code>dataframe.groupby('Dates').['Score 1'].mean()
</code></pre>

python pandas numpy