<p>你可以这样做。在</p>
<p><strong>更新:</strong></p>
<pre><code>df = pd.read_csv("your_csv_file")
'''df = pd.DataFrame({'Used CPU':['1','0','2','2','0','51550m'], \
'Used Memory':['4Gi','0','4Gi','4Gi','0', '39528Mi'], \
'Hard CPU':['50','0','4','4','100m','56'], \
'Hard Memory':['24Gi','0','8Gi', '8Gi', '128Mi', '47Gi']})'''
units = {'m':0.001,'Mi':0.00104858,'Gi':1.0737425}
def conversion(x):
for key in units.keys():
if key in str(x):
x = x.split(key)[0]
x = (int(x)*units[key])
return x
return str(x)
df = df.applymap(conversion)
df = df.apply(lambda x: x.astype(np.float64), axis=1)
print(df)
</code></pre>
<p>输入:</p>
^{pr2}$
<p><strong>输出:</strong></p>
<pre><code> Hard CPU Hard Memory Used CPU Used Memory
0 50.0 25.76980 1.00 4.29497
1 0.0 0.000000 0.00 0.00000
2 4.0 8.589940 2.00 4.29497
3 4.0 8.589940 2.00 4.29497
4 0.1 0.134218 0.00 0.00000
5 56.0 50.465898 51.55 41.44827
</code></pre>
<p>他们在浮动64。现在您可以使用<code>df['Hard Memory'] + df['Used Memory']</code></p>