擅长:python、mysql、java
<p>为了让初学者更清楚,您可以<strong>定义一个函数</strong>,该函数将相应地返回每个人的年龄组,然后<strong>使用<a href="https://pandas.pydata.org/pandas-docs/stable/reference/api/pandas.DataFrame.apply.html" rel="nofollow noreferrer">^{<cd1>}</a>将该函数应用于我们的<code>'Group'</code>列:</p>
<pre><code>import pandas as pd
def age(row):
a = row['Age']
if 0 < a <= 2:
return 'Baby'
elif 2 < a <= 12:
return 'Child'
elif 12 < a <= 18:
return 'Young'
elif 18 < a <= 30:
return 'Young Adult'
elif 30 < a <= 50:
return 'Adult'
elif 50 < a <= 65:
return 'Senior Adult'
df = pd.DataFrame({'Name':['Anthony','Albert','Zahra'],
'Country':['France','Belgium','Tunisia'],
'Age':[15,54,14]})
df['Group'] = df.apply(age, axis=1)
print(df)
</code></pre>
<p>输出:</p>
<pre><code> Name Country Age Group
0 Anthony France 15 Young
1 Albert Belgium 54 Senior Adult
2 Zahra Tunisia 14 Young
</code></pre>