[英]Pandas bar graph using original dataframe
I have a pandas dataframe and I'm attempting to plot the number of subscription types purchased by gender the original dataframe resemblems我有一个熊猫数据框,我正在尝试绘制按性别购买的订阅类型的数量,原始数据框类似于
df =
Memb_ID Gender 1_Month 3_Month 6_Month 1_Year
1 Male 6 0 3 0
2 Male 0 0 0 4
3 Female 0 4 3 1
4 Male 2 1 0 1
5 Female 1 4 0 2
...
At the moment I make a temp_df
where I sum up the data so that I have目前我做了一个
temp_df
,我总结了数据,以便我有
temp_df = pd.DataFrame(columns=['Gender', '1_Year', '1_Month', '3_Month','6_Month'])
sex = ['Male', 'Female']
temp_df['Gender'] = sex
for i in list(temp_df.columns.values)[1:]:
temp = [df.loc[df['Gender'] == 'Male', i].sum(),\
df.loc[df['Gender'] == 'Female', i].sum()]
temp_df[i] = temp
temp_df.plot(x='Gender', kind='bar', grid=True)
plt.show()
This fills up temp_df
and I'm able to graph it.这填满了
temp_df
并且我可以绘制它。 Is there an eloquent way of performing the same thing using just df
?是否有一种雄辩的方法可以仅使用
df
来执行相同的操作?
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