擅长:python、mysql、java
<p>如果要经常使用数据文件,我建议使用<code>pandas</code>库。使用<code>pandas</code>,您可以执行以下操作:</p>
<pre class="lang-py prettyprint-override"><code>import pandas as pd
df = pd.read_csv('/home/lamma/local-blast/scripts/test.csv')
# access row by index
row = df.iloc[1]
# convert the pandas series to a list
row_list = row.tolist()
# access cell by index
cell = df.iloc[1, 1]
</code></pre>
<p>一般来说,它使处理表格数据变得非常容易</p>
<p>查看<a href="https://pandas.pydata.org/pandas-docs/stable/reference/api/pandas.DataFrame.iloc.html" rel="nofollow noreferrer">iloc</a>和<a href="https://pandas.pydata.org/pandas-docs/stable/reference/api/pandas.DataFrame.loc.html" rel="nofollow noreferrer">loc</a>的文档</p>
<p>您也可以轻松地选择列作为列表:</p>
<pre class="lang-py prettyprint-override"><code>import pandas as pd
df = pd.read_csv('/home/lamma/local-blast/scripts/test.csv')
# get the columns as lists
samples = df['Sample'].tolist()
forward = df['Forward'].tolist()
reverse = df['Reverse'].tolist()
</code></pre>