擅长:python、mysql、java
<p>让我们试试这个例子。在</p>
<pre><code>import pandas as pd
import numpy as np
df = pd.DataFrame({'state':np.random.choice(['TX','CA','NY'],100),'measure_id':np.random.randint(1,5,100),'measure_name':np.nan,'score':np.random.randint(50,100,100)})
dict = {1:'Measure A',2:'Measure B',3:'Measure C',4:'Measure D',5:'Measure E'}
df['measure_name'] = df['measure_id'].map(dict)
</code></pre>
<p>输入数据:</p>
^{pr2}$
<p>输出:</p>
<pre><code> Measure ID Measure Name Average Maximum Minimum Standard Deviation
0 1 Measure A 74.346154 99 53 13.734460
1 2 Measure B 70.720000 97 50 16.084465
2 3 Measure C 76.130435 97 51 14.943239
3 4 Measure D 77.576923 97 56 10.756107
</code></pre>