擅长:python、mysql、java
<p>使用<a href="https://www.google.com/url?sa=t&rct=j&q=&esrc=s&source=web&cd=1&ved=2ahUKEwiui_eGtdTeAhVGWisKHe-kCrMQFjAAegQICRAB&url=https%3A%2F%2Fpandas.pydata.org%2Fpandas-docs%2Fstable%2Fgenerated%2Fpandas.to_datetime.html&usg=AOvVaw1Arlz9KbP1nOln9DAQPZLq" rel="nofollow noreferrer">^{<cd3>}</a>将<code>date</code>列转换为<code>datetime64[ns]</code>数据类型,然后按给定方式进行减法:</p>
<pre><code>df['date'] = pd.to_datetime(df['date'])
#if comparing with only 1st row
mask = (df['date']-df.loc[0,'date']).dt.days<=90
# alternative mask = (df['date']-df.loc[0,'date']).dt.days.le(90)
#if comparing with immediate rows.
mask = df['date'].diff().dt.days<=90
# alternative mask = df['date'].diff().dt.days.le(90)
df1 = df.loc[mask,:] #gives you required rows with all columns
</code></pre>