我正在尝试在每个分组的条形下方添加日期,即y轴的0和x轴的产品标签之间的日期。列出的是代表。
df1 <- data.frame(product = c("A","A","A","A","A","A","A","B","B","B","B","B","B","B","C","C","C","C","C","C","C","D","D","D","D","D","D","D"),
start_date =as.Date(c('2020-02-01', '2020-02-02', '2020-02-03', '2020-02-04', '2020-02-05', '2020-02-06', '2020-02-07')),
value = c(15.71,17.37,19.93,14.28,15.85,10.5,8.58,5.62,5.19,5.44,4.6,7.04,6.29,3.3,20.35,27.92,23.07,12.83,22.28,21.32,31.46,34.82,23.68,29.11,14.48,25.2,16.91,27.79))
graph <- ggplot(df1, aes(y = value, x = product, fill = product, group = factor(start_date))) +
geom_col(data = df1, stat = "identity",position = position_dodge(width = 0.8), width = 0.7, inherit.aes = TRUE, size = 0) +
geom_text(aes(label= format(as.Date(start_date,format="%Y-%m-%d"), format = "%d")), vjust = "bottom", position = position_dodge(width = 0.8), inherit.aes = TRUE) +
xlab("Product") + ylab("Values")
答案 0 :(得分:0)
您几乎拥有了它,但是关键是要认识到所有文本都具有相同的y值:在这种情况下,它的值比0略低。
@app.route('/predict', methods=["GET"])
def predict():
message = "some message" # hardcode a value
prediction = model.predict([message]) # feeds to model
classification = encoder.inverse_transform(prediction) # decodes prediction
return render_template('index.html', message=message, classification=classification)
还要注意,我在这里和那里删除了不需要的位,因为它们是继承的:(1)graph <- ggplot(df1, aes(y = value, x = product, fill = product, group = factor(start_date))) +
geom_col(position = position_dodge(width = 0.8),
width = 0.7, inherit.aes = TRUE, size = 0) +
geom_text(aes(
label= format(as.Date(start_date,format="%Y-%m-%d"), format = "%d"),
y=-0.5
),
position = position_dodge(width = 0.8), size=2) +
xlab("Product") + ylab("Values")
调用data=
,(2)geom_col
调用{{ 1}}。