散点图

气泡散点图

代码：
sales_store_data = go.Scatter(
y = sales_across_store_df.avg_sale.values,
mode=’markers’,
marker=dict(
size = sales_across_store_df.avg_sale.values,
color = sales_across_store_df.avg_sale.values,
colorscale=’Viridis’,
showscale=True
),
text = sales_across_store_df.index.values
)
data = [sales_store_data]

sales_store_layout = go.Layout(
autosize= True,
title= ‘Scatter plot of avg sales per store’,
hovermode= ‘closest’,
xaxis= dict(
title= ‘Stores’,
ticklen= 10,
zeroline= False,
gridwidth= 1,
),
yaxis=dict(
title= ‘Avg Sales’,
ticklen= 10,
zeroline= False,
gridwidth= 1,
),
showlegend= False
)
fig = go.Figure(data=data, layout=sales_store_layout)
py.iplot(fig,filename=’scatter_sales_store’)

输出结果

分箱图

分箱统计图

def salesdist(data):
“””
Salesdist used for Checing Sales Distribution.
data : contain data frame which contain sales data
“””
sales_df = data.copy(deep=True)
sales_df[‘sales_bins’] = pd.cut(sales_df.sales, [0, 50, 100, 150, 200, 250])
return sales_df
sales_df = sales_dist(train_df)

salescount = pd.value_counts(sales_df.sales_bins)
sales_count.sort_values(ascending=True).plot(kind=’barh’, title=’Sales distribution’, );
# sns.countplot(salescount)

_

数据大屏

再弹数据大屏制作中.py