擅长:python、mysql、java
<p>试着这样做:</p>
<p>根据<code>Home</code>和<code>Away</code>目标分成两个数据帧</p>
<pre><code>df1=df[['Date','Home','HomeGoal']]
df2 = df[['Date','Away','AwayGoal']]
all_dfs=[df1,df2]
</code></pre>
<p>列的名称</p>
<pre><code>for dfs in all_dfs:
dfs.columns = ['Date','Team', 'Goal']
</code></pre>
<p>将两个dfs连接在一起</p>
<pre><code>new_df=pd.concat(all_dfs,ignore_index=True).reset_index(drop=True)
</code></pre>
<h2>输出:</h2>
<pre><code>Date Team Goal
0 2019 Arsenal 5
1 2019 Mcity 2
2 2019 MU 3
3 2019 Mcity 0
4 2019 MU 1
5 2019 Liv 2
6 2019 Liv 4
7 2019 MU 0
</code></pre>
<p>最近两场比赛的平均成绩:</p>
<pre><code>new_df[new_df['Team'] == 'MU'].sort_values('Date')['Goal'][:2].sum()/2
</code></pre>
<p>在客场和主场比赛中,球队的总进球数</p>
<pre><code>new_df.groupby('Team')['Goal'].sum()
</code></pre>
<h2>输出:</h2>
<pre><code>Team
Arsenal 5
Liv 6
MU 4
Mcity 2
</code></pre>