Plotting 2dhistogram With Sum Value Rather Than Count

Beginner user on the forum. Help please. I have a data set: x, y coordinates, each x, y has a value. I want to plot a 2d histogram displaying the sum of the values in each bin with

Solution 1:

You could calculate the values to show in the binned 2D plot prior to plotting and then show as an imshow plot.

If you're happy to use pandas, one option would be to group the mass data accordings to cut (pandas.cut) x and y data. Then apply the sum (.sum()) and unstack to obtain a pivot table.

df.mass.groupby([pd.cut(df.x, bins=xbins, include_lowest=True), 
                 pd.cut(df.y, bins=ybins, include_lowest=True)]) \
               .sum().unstack(fill_value=0)

Here is a complete example:

import numpy as np; np.random.seed(1)
import pandas as pd
import matplotlib.pyplot as plt
import  matplotlib.colors

xpos = np.random.randint(0,10, size=50)
ypos = np.random.randint(0,10, size=50)
mass = np.random.randint(0,75, size=50)

df = pd.DataFrame({"x":xpos, "y":ypos, "mass":mass})

xbins = range(10)
ybins = range(10)
su = df.mass.groupby([pd.cut(df.x, bins=xbins, include_lowest=True), 
                     pd.cut(df.y, bins=ybins, include_lowest=True)]) \
            .sum().unstack(fill_value=0)
print su
im = plt.imshow(su.values, norm=matplotlib.colors.LogNorm(1,300))
plt.xticks(range(len(su.index)), su.index, rotation=90)
plt.yticks(range(len(su.columns)), su.columns)
plt.colorbar(im)
plt.show()