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I have a Julia DataFrame like so:
│ Row │ date │ users │ posts │ topics │ likes │ pageviews │
│ │ Date │ Int64 │ Int64 │ Int64 │ Int64 │ Int64 │
├──────┼────────────────────┼───────┼───────┼────────┼───────┼───────────┤
│ 1 │ Date("2020-06-16") │ 1 │ 3 │ 4 │ 7 │ 10000 │
│ 2 │ Date("2020-06-15") │ 2 │ 2 │ 5 │ 8 │ 20000 │
│ 3 │ Date("2020-06-14") │ 3 │ 3 │ 6 │ 9 │ 30000 │
I would like a plot of posts vs date, but the daily data is too noisy, so I'd like to take sum the posts for every week and plot that instead? What's the easiest way to achieve that.
1000
This is how the DataFrame would look like: Finally, plot the DataFrame by adding the following syntax: You’ll notice that the kind is now set to ‘line’ in order to plot the line chart. Here is the complete Python code: And once you run the code, you’ll get this line chart: Bar charts are used to display categorical data.
Finally, you can plot the DataFrame by adding the following syntax: Notice that you can specify the type of chart by setting kind = ‘scatter’ You’ll also need to add the Matplotlib syntax to show the plot (ensure that the Matplotlib package is install in Python ):
Plot a Pie Chart using Pandas Step 1: Prepare your data For demonstration purposes, the following data about the status of tasks was prepared: Tasks... Step 2: Create the DataFrame You can then create the DataFrame using this code: import pandas as pd data = {'Tasks':... Step 3: Plot the DataFrame ...
In other words, when the number of data points is enormous, and each data point can’t be plotted separately, it’s better to use this kind of plot that represents data in the form of a honeycomb. Also, the color of each hexbin defines the density of data points in that range.
The TimeSeries package provides various utilities to work with TimeSeries data.
In this case, you can use the collapse to convert from daily to weekly data:
julia> using TimeSeries, DataFrames
julia> ta = TimeArray(df.date, df.posts)
1311×1 TimeArray{Int64,1,Date,Array{Int64,1}} 2016-10-19 to 2020-06-16
│ │ A │
├────────────┼───────┤
│ 2016-10-19 │ 1 │
│ 2016-10-20 │ 2 │
│ 2016-10-21 │ 3 │
│ 2016-10-23 │ 4 │
...
julia> weekly = collapse(ta, week, last, sum)
192×1 TimeArray{Int64,1,Date,Array{Int64,1}} 2016-10-23 to 2020-06-16
│ │ A │
├────────────┼───────┤
│ 2016-10-23 │ 10 │
│ 2016-10-28 │ 22 │
│ 2016-11-06 │ 34 │
...
julia> using Gadfly
julia> plot(DataFrame(weekly)[1:end-1,:], x=:timestamp, y=:A, Geom.line(), Guide.ylabel("Weekly sum of Posts"), Guide.xlabel("Week"))
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