擅长:python、mysql、java
<p>这就是你要找的吗?注意:为了便于打印,我将列重命名为“call_v”和“call_d”。在</p>
<pre><code> kpi_date ssaname bts_name call_v call_d
0 2015-09-01 Bangalore 1002_NUc_Marathalli 8962 0.62
1 2015-09-03 Bangalore 1002_NUc_Marathalli 6567 1.19
2 2015-09-02 Bangalore 1002_NUc_Marathalli 7033 0.63
3 2015-09-01 Bangalore 1003_IU2_Munnekolalu 4659 1.17
4 2015-09-02 Bangalore 1003_IU2_Munnekolalu 6671 0.46
df.groupby(['bts_name','kpi_date']).mean().stack().unstack(level=1).unstack(level=1)
kpi_date 2015-09-01 2015-09-02 2015-09-03
call_v call_d call_v call_d call_v call_d
bts_name
1002_NUc_Marathalli 8962 0.62 7033 0.63 6567 1.19
1003_IU2_Munnekolalu 4659 1.17 6671 0.46 NaN NaN
</code></pre>
<p>基本上是堆积后的物质的聚集。在</p>