ECHART

Matplotlib and Numpy - Create a calendar heatmap

@author: woldekidank
"""`enter code here`

import numpy as np
from datetime import date
import datetime
import matplotlib.pyplot as plt
import random


D = date(2016,1,1)
Dord = date.toordinal(D)
Dweekday = date.weekday(D)

Dsnday = Dord - Dweekday + 1 #find sunday
square = np.array([[0, 0],[ 0, 1], [1, 1], [1, 0], [0, 0]])#x and y to draw a square
row = 1
count = 0
while row != 0:
    for column in range(1,7+1):    #one week per row
        prof = np.ones([24, 1])
        hourly = np.zeros([24, 1])
        for i in range(1,24+1):
            prof[i-1, 0] = prof[i-1, 0] * random.uniform(0, 1)
            hourly[i-1, 0] = i / 24
        plt.title('Temperature Profile')
        plt.plot(square[:, 0] + column - 1, square[:, 1] - row + 1,color='r')    #go right each column, go down each row
        if date.fromordinal(Dsnday).month == D.month:
            if count == 0:
                plt.plot(hourly, prof)
            else:
                plt.plot(hourly + min(square[:, 0] + column - 1), prof + min(square[:, 1] - row + 1))

            plt.text(column - 0.5, 1.8 - row, datetime.datetime.strptime(str(date.fromordinal(Dsnday)),'%Y-%m-%d').strftime('%a'))
            plt.text(column - 0.5, 1.5 - row, date.fromordinal(Dsnday).day)

        Dsnday = Dsnday + 1
        count = count + 1

    if date.fromordinal(Dsnday).month == D.month:
        row = row + 1    #new row
    else:
        row = 0    #stop the while loop

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Calendar_Heatmaps

CALENDAR HEATMAP

use

# http://margintale.blogspot.in/2012/04/ggplot2-time-series-heatmaps.html
library(ggplot2)
library(plyr)
library(scales)
library(zoo)

df <- read.csv("https://raw.githubusercontent.com/selva86/datasets/master/yahoo.csv")
df$date <- as.Date(df$date)  # format date
df <- df[df$year >= 2012, ]  # filter reqd years
df <- df[df$month >= 10, ]  # filter reqd years

# Create Month Week
df$yearmonth <- as.yearmon(df$date)
df$yearmonthf <- factor(df$yearmonth)
df <- ddply(df,.(yearmonthf), transform, monthweek=1+week-min(week))  # compute week number of month
df <- df[, c("year", "yearmonthf", "monthf", "week", "monthweek", "weekdayf", "VIX.Close")]
head(df)
#>   year yearmonthf monthf week monthweek weekdayf VIX.Close
#> 1 2012   Jan 2012    Jan    1         1      Tue     22.97
#> 2 2012   Jan 2012    Jan    1         1      Wed     22.22
#> 3 2012   Jan 2012    Jan    1         1      Thu     21.48
#> 4 2012   Jan 2012    Jan    1         1      Fri     20.63
#> 5 2012   Jan 2012    Jan    2         2      Mon     21.07
#> 6 2012   Jan 2012    Jan    2         2      Tue     20.69


# Plot
ggplot(df, aes(monthweek, weekdayf, fill = VIX.Close)) +
  geom_tile(colour = "white") +
  facet_grid(year~monthf) +
  scale_fill_gradient(low="red", high="green") +
  labs(x="Week of Month",
       y="",
       title = "Time-Series Calendar Heatmap",
       subtitle="Yahoo Closing Price",
       fill="Close")
ggsave(file = "mtcars_plot.png", width = 5, height = 6, type = "cairo", dpi = 600)