擅长:python、mysql、java
<p>使用<a href="https://stackoverflow.com/questions/38212697/confirming-equality-of-two-pandas-dataframes?noredirect=1#comment63849479_38212697">elegant @Divakar's idea</a>-numpy的<a href="http://docs.scipy.org/doc/numpy/reference/generated/numpy.allclose.html" rel="nofollow noreferrer">allclose()</a>将完成数字的主要技巧:</p>
<pre><code>In [128]: df1
Out[128]:
0 s n
0 1 aaa 1
1 2 aaa 2
2 3 aaa 3
In [129]: df2
Out[129]:
0 s n
0 1.0 aaa 1.0
1 2.0 aaa 2.0
2 3.0 aaa 3.0
In [130]: (np.allclose(df1.select_dtypes(exclude=[object]), df2.select_dtypes(exclude=[object]))
.....: &
.....: df1.select_dtypes(include=[object]).equals(df2.select_dtypes(include=[object]))
.....: )
Out[130]: True
</code></pre>
<p><a href="http://pandas.pydata.org/pandas-docs/stable/generated/pandas.DataFrame.select_dtypes.html" rel="nofollow noreferrer">select_dtypes()</a>将帮助您分离字符串和所有其他数字数据类型</p>