擅长:python、mysql、java
<pre><code>from pathlib import Path
files = Path(".").glob("1*.csv")
my_df_list = []
bins = [650,1000,1350,1700,2050,2400,2750,3000]
columns = ("650-1000","1000-1350","1350-1700","1700-2050","2050-2400","2400-2750","2750-3000")
for file in files:
file_name = file.name
file_id = file_name.replace("*.csv","")
df = pd.read_csv(file_name)
print(df.columns)
bins = [650,1000,1350,1700,2050,2400,2750,3000]
a_bins = df.B.groupby(pd.cut(df['A'],bins))
a_bins = a_bins.agg([np.mean]).reset_index(drop=True)
a_bins_df = a_bins.T.copy()
a_bins_df.columns = columns
a_bins_df.index = [file_id]
my_df_list.append(a_bins_df)
df_total = pd.concat(my_df_list,axis=0)
</code></pre>
<p>假设所有的.csv文件都在同一个目录下,下面是输出,我将1.csv复制为2.csv来测试上面的脚本</p>
<pre><code> 650-1000 1000-1350 1350-1700 1700-2050 2050-2400 2400-2750 2750-3000
102 5.952381 7.142857 5.316993 6.422334 4.705882 NaN NaN
101 5.952381 7.142857 5.316993 6.422334 4.705882 NaN NaN
</code></pre>