擅长:python、mysql、java
<blockquote>
<p>I am trying to calculate the means of all previous rows for each column of the DataFrame </p>
</blockquote>
<p>要获取所有列,可以执行以下操作:</p>
<pre><code>df_means = df.join(df.cumsum()/
df.applymap(lambda x:1).cumsum(),
r_suffix = "_mean")
</code></pre>
<p>但是,如果<code>Team</code>是一个列而不是索引,那么您应该去掉它:</p>
<pre><code>df_data = df.drop('Teams', axis=1)
df_means = df.join(df_data.cumsum()/
df_data.applymap(lambda x:1).cumsum(),
r_suffix = "_mean")
</code></pre>
<p>你也可以这样做</p>
<pre><code>import numpy as np
df_data = df[[col for col in df.columns
if np.issubdtype(df[col],np.number)]]
</code></pre>
<p>或者手动定义要取平均值的列的列表<code>cols_for_mean</code>,然后执行以下操作</p>
<pre><code>df_data = df[cols_for_mean]
</code></pre>