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<p>嗨,我想根据学生最喜欢的科目的当前分数+分数给他们一个最终分数</p>
<pre><code>import pandas as pd
new_data = [['tom', 31, 50, 30, 20, 'English'], ['nick', 30, 42, 23, 21, 'Math'], ['juli', 39, 14, 40, 38, 'Science']]
df = pd.DataFrame(new_data, columns = ['Name','Current_Score','English','Science','Math','Favourite_Subject'])
for subj in df['Favourite_Subject'].unique():
mask = (df['Favourite_Subject'] == subj)
df['Final_Score'] = df[mask].apply(lambda row: row['Current_Score'] + row[subj], axis=1)
Name Score English Science Math Favourite_Subject Final_Score
0 tom 31 50 30 20 English NaN
1 nick 30 42 23 21 Math NaN
2 juli 39 14 40 38 Science 79.0
</code></pre>
<p>当我应用上述函数时,我在“Final_Score”列的其他两个条目中得到了NaN,如何在不覆盖NaN的情况下得到以下结果?谢谢</p>
<pre><code>
Name Score English Science Math Favourite_Subject Final_Score
0 tom 31 50 30 20 English 81
1 nick 30 42 23 21 Math 51
2 juli 39 14 40 38 Science 79
</code></pre>