擅长:python、mysql、java
<p>使用dict映射到<code>map</code>带有HHT标签的HHT数值将更加健壮:</p>
<pre class="lang-py prettyprint-override"><code>hht_map = {
1: 'Married couple household',
2: 'Nonfamily household:Male',
3: 'Nonfamily household:Female',
4: 'Other family household:Male',
5: 'Other family household:Female',
6: 'Nonfamily household:Male',
7: 'Nonfamily household:Female',
}
df.index = df.index.map(hht_map)
print(df)
</code></pre>
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<p><strong>编辑:</strong>在分组之前,请在<code>pums_df</code>上尝试映射</p>
<p>使用<code>map</code>创建一个新的<code>label</code>列:</p>
<pre class="lang-py prettyprint-override"><code>pums_df['label'] = pums_df.HHT.map(hht_map)
</code></pre>
<p>使用新的<code>label</code>到<code>groupby</code>:</p>
<pre class="lang-py prettyprint-override"><code>table = pums_df['HINCP'].groupby(pums_df['label'])
</code></pre>