Cara menggunakan 3d waterfall plot python

import plotly.graph_objects as go fig = go.Figure() fig.add_trace(go.Waterfall( x = [["2016", "2017", "2017", "2017", "2017", "2018", "2018", "2018", "2018"], ["initial", "q1", "q2", "q3", "total", "q1", "q2", "q3", "total"]], measure = ["absolute", "relative", "relative", "relative", "total", "relative", "relative", "relative", "total"], y = [1, 2, 3, -1, None, 1, 2, -4, None], base = 1000 )) fig.add_trace(go.Waterfall( x = [["2016", "2017", "2017", "2017", "2017", "2018", "2018", "2018", "2018"], ["initial", "q1", "q2", "q3", "total", "q1", "q2", "q3", "total"]], measure = ["absolute", "relative", "relative", "relative", "total", "relative", "relative", "relative", "total"], y = [1.1, 2.2, 3.3, -1.1, None, 1.1, 2.2, -4.4, None], base = 1000 )) fig.update_layout( waterfallgroupgap = 0.5, ) fig.show()

This tutorial will tackle how you can create a waterfall plot or chart in Python. We will use the Matplotlib and waterfall_chart library for two dimensions and three-dimension waterfall plots.

Create 2D Waterfall Plot With Matplotlib in Python

The waterfall chart is common in finance, but the waterfall is not so effective when you have part-to-whole relationships.

Let’s say you want to show our project cost breakdown. How it looks like in a table takes a bit of time for people to go through the table and compare the numbers.

Take note that the waterfall charts do not come with Python default packages. First, we need to install the python -m pip install --upgrade pip 2 package.

pip install waterfallcharts

If you get any error during installation, upgrade your python -m pip install --upgrade pip 3 using the following command.

python -m pip install --upgrade pip

We need to import the required libraries to create a waterfall chart or plot.

import matplotlib.pyplot as plot import waterfall_chart as waterfall

The python -m pip install --upgrade pip 4 parameter takes the key-value pair. Using this parameter is to access figure elements like the figure size and face color.

plot.rcParams["figure.figsize"] = (8,6) plot.rcParams["figure.facecolor"]="yellow"

Then we create a data set for XYZ company. We are going to visualize the sale of XYZ company with corresponding months.

x1,y1=["Jan","Feb","March","April","May","jun","July","Aug"],[10,25,30,50,-10,15,-5,10] waterfall.plot(x1, y1,)

Full Code - 2D waterfall plot:

import matplotlib.pyplot as plot import waterfall_chart as waterfall # Set set width and height and face color as yellow plot.rcParams["figure.figsize"] = (8,6) plot.rcParams["figure.facecolor"]="yellow" # dependant and independent variables x1,y1=["Jan","Feb","March","April","May","jun","July","Aug"],[10,25,30,50,-10,15,-5,10] waterfall.plot(x1, y1,) # Set x labels with 45 rotation plot.xticks(rotation=45) plot.title("2D Waterfall plot") # Add the padding and merging for visual elements plot.tight_layout() plot.show()

Output:

The profit raised with a green plot and lost means the minus points go with the red plot, and the net sale of XYZ company goes with a blue plot.

Create 3D Waterfall Plot With Matplotlib in Python

In the previous example, we’ve learned how to create a 2D waterfall plot. This section will demonstrate creating a 3D waterfall plot using the python -m pip install --upgrade pip 5 class from the Matplotlib library.

We will import the following required libraries to create a 3D waterfall plot.

from matplotlib.collections import PolyCollection import matplotlib.pyplot as plt from matplotlib import colors as mcolors import numpy as np

If we want to create a 3D plot, we need to call the python -m pip install --upgrade pip 6 method from python -m pip install --upgrade pip 7.

axes=plt.axes(projection="3d")

Now we generate some random data sets for three dimensions. The python -m pip install --upgrade pip 8 variable stores the given range using the python -m pip install --upgrade pip 9 numpy method, and the import matplotlib.pyplot as plot import waterfall_chart as waterfall 0 variable will generate a random integer number in every iteration using the Numpy import matplotlib.pyplot as plot import waterfall_chart as waterfall 1 method.

x1 = np.arange(0, 10, 0.4) verts = [] z1 = [0.0, 1.0, 2.0, 3.0] for z in z1: y1 = np.random.rand(len(x1)) y1[0], y1[-1] = 0, 0 verts.append(list(zip(x1, y1)))

The import matplotlib.pyplot as plot import waterfall_chart as waterfall 2 function takes the first parameter as a list of data points, and the second parameter is import matplotlib.pyplot as plot import waterfall_chart as waterfall 3 that help us display specific colors. We have already imported colors as import matplotlib.pyplot as plot import waterfall_chart as waterfall 4 from Matplotlib, and we have defined our custom function called import matplotlib.pyplot as plot import waterfall_chart as waterfall 5.

The import matplotlib.pyplot as plot import waterfall_chart as waterfall 6 function is called with a color value parameter and this function returns the import matplotlib.pyplot as plot import waterfall_chart as waterfall 7 method with color and alpha parameters.