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import pandas as pd | |
import tablespoon as tbsp | |
from tablespoon.data import WALMART | |
from mizani.breaks import date_breaks | |
from plotnine import * | |
from datetime import datetime | |
# make date string a date object | |
df_WALMART = WALMART | |
df_WALMART = df_WALMART.assign(ds = lambda df: pd.to_datetime(df.ds)).query("ds > '2016-03-01'") | |
df_WALMART | |
n = tbsp.Snaive() | |
df_n = (n.predict(df_WALMART, horizon=7*4, frequency="D", lag = 7, uncertainty_samples = 1000).assign(model = 'snaive')) | |
df_n.head(14) | |
theme_set(theme_538) | |
palette = ["#000000", "#ee1d52"] | |
df_actuals_forecasts_n = pd.concat([df_WALMART, df_n]) | |
p = ( | |
ggplot(df_actuals_forecasts_n, aes(x="ds", y="y")) | |
+ geom_line(aes(y = 'y'), color = palette[0]) | |
+ geom_point(aes(y = 'y_sim'), color = palette[1], size = 0.1, alpha = 0.1) | |
+ scale_x_datetime(breaks=date_breaks("1 month")) | |
+ theme(axis_text_x=element_text(angle=45)) | |
+ xlab("") | |
+ ggtitle("Log Sales (Snaive)") | |
+ scale_color_manual(palette) | |
) | |
p |
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