<p>请参阅<a href="https://pandas.pydata.org/pandas-docs/stable/user_guide/merging.html" rel="nofollow noreferrer">official page</a></p>
<hr/>
<h2>Concat多个数据帧</h2>
<pre><code>df1=pd.DataFrame(
{
"A":["A0","A1","A2","A3"]
},
index=[0, 1, 2, 3]
)
df2=pd.DataFrame(
{
"B":["B4","B5"]
},
index=[4, 5]
)
df3=pd.DataFrame(
{
"C":["C6", "C7", "C8", "C9", "C10"]
},
index=[6, 7, 8, 9, 10]
)
result = pd.concat([df1, df2, df3], axis=1)
display(result)
</code></pre>
<p>输出:</p>
<pre><code> A B C
0 A0 NaN NaN
1 A1 NaN NaN
2 A2 NaN NaN
3 A3 NaN NaN
4 NaN B4 NaN
5 NaN B5 NaN
6 NaN NaN C6
7 NaN NaN C7
8 NaN NaN C8
9 NaN NaN C9
10 NaN NaN C10
</code></pre>
<hr/>
<h2>通过循环将文件导入列表</h2>
<p>方法1:
您可以创建一个列表,将整个文件名放入列表中</p>
<pre><code>filenames = ['sample_20.csv', 'sample_25.csv', 'sample_30.csv', ...]
dataframes = [pd.read_csv(f) for f in filenames]
</code></pre>
<p>方法1-1:
如果您确实有很多文件,那么您需要一种更快的方法来创建名称列表</p>
<pre><code>filenames = ['sample_{}.csv'.format(i) for i in range(20, 90, 5)]
dataframes = [pd.read_csv(f) for f in filenames]
</code></pre>
<p>方法2:</p>
<pre><code>from glob import glob
filenames = glob('sample*.csv')
dataframes = [pd.read_csv(f) for f in filenames]
</code></pre>