<p>您可以使用自定义函数:</p>
<pre><code>cols = [col for col in df.columns if not col.startswith('Color')]
print (cols)
['Client', 'Date', 'Value_1', 'Value_2', 'Value_3']
def f(x):
return pd.Series(x.sort_values(ascending=False).values, index=x.sort_values().index)
df = df.set_index(cols).apply(f, axis=1).reset_index()
print (df)
Client Date Value_1 Value_2 Value_3 Color_3 Color_2 Color_4 \
0 ABC 2016-02-16 94 373 183 1739 73 38
Color_1
0 19
</code></pre>
<p>另一种解决方案:</p>
<pre><code>#select to Series all values from position 5
x = df.ix[0, 5:]
print (x)
Color_1 1739
Color_2 38
Color_3 19
Color_4 73
Name: 0, dtype: object
#create DataFrame with sorting values and index of Series x
a = pd.DataFrame([x.sort_values(ascending=False).values], columns=x.sort_values().index)
print (a)
Color_3 Color_2 Color_4 Color_1
0 1739 73 38 19
#concat to original
df = pd.concat([df[df.columns[:5]], a], axis=1)
print (df)
Client Date Value_1 Value_2 Value_3 Color_3 Color_2 Color_4 \
0 ABC 2016-02-16 94 373 183 1739 73 38
Color_1
0 19
</code></pre>
<p>编辑byu更改的问题:</p>
<pre><code>x = df.ix[:, 5:].sort_values(by=0, ascending=False, axis=1)
print (x)
Apple Banana Pear Kiwi
0 1739 73 38 19
df = pd.concat([df.ix[:, :5], x], axis=1)
print (df)
Client Date Value_1 Value_2 Value_3 Apple Banana Pear Kiwi
0 ABC 2016-02-16 94 373 183 1739 73 38 19
</code></pre>