我是熊猫数据框的新手,我需要帮助来了解百分比变化。
我确实从查询生成了一个csv,以便通过为列分配排名来计算平均值。
rank ds continent region device traffic
1 08/13 North america US mobile 7300
1 08/13 North america US desktop 2500
2 08/06 Europe UK mobile 3300
2 08/06 Europe Italy desktop 5600
然后,我确实在第二个CSV中计算了“ 1周”和“ 3周”的平均点击量。
df_1 = df.loc[df['rank'] == '1']
df_1['traffic'] = df_1['traffic'].astype(float).fillna(0)
avg_1 = df_1.groupby(['continent','region','device']).mean()
avg_1['ds'] = '1 week'
last_3 = df.loc[df['rank'].isin(['2','3','4'])]
last_3['traffic'] = last_3['traffic'].astype(float).fillna(0)
avg_3 = last_3.groupby(['continent','region','device']).mean()
avg_3['ds'] = '3 week'
最终平均值输出:
market country traffic device ds
North america US 36015.33 mobile 1week
North america US 40663.67 desktop 3week
Europe UK 360270.7 mobile 1week
Europe Italy 1363183 desktop 3week
有人可以帮我计算1周和3周的变化流量百分比吗?谢谢!
答案 0 :(得分:0)
明白了这一点。使用了pct_change()