XYZ massive data for heatmap
I could not find a consensus answer on this question or one that suits my needs. I have data in three columns of a text file: X, Y and Z. The columns are separated by tabs. I would like to make a heatmap view of this data with Python where the X and Y positions are shaded by a value in Z that ranges from 0 to 1 (the discrete probability of X and Y). I tried the nautical heatmap and matplotlib pcolormesh package, but unfortunately they need two dimensional datasets.
My data goes through X from 1 to 37 for constant y, and then iterates by 0.1 into y. y max fluctuates depending on the dataset, but ymin is always 0.
[XYZ] row1 [1 ... 37 0.0000 Zvalue], row2 [1 ... 37 0.1000 Zvalue], etc.
import numpy as np
from numpy import *
import pandas as pd
import seaborn as sns
sns.set()
df = np.loadtxt(open("file.txt", "rb"), delimiter="\t").astype("float")
Any hints for the next steps?
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If you understood correctly, you have three columns with X and Y indicating the position of the Z value.
Consider the following example. There are three columns: X and Y contain positional information (categories in this case) and Z contains values for shading the heat map.
x = np.array(['a','b','c','a','b','c','a','b','c'])
y = np.array(['a','a','a','b','b','b','c','c','c'])
z = np.array([0.3,-0.3,1,0.5,-0.25,-1,0.25,-0.23,0.25])
We then create a dataframe from those columns and wrap them around (so x, y and z actually become columns). Provide column names and make sure Z_value is a number.
df = pd.DataFrame.from_dict(np.array([x,y,z]).T)
df.columns = ['X_value','Y_value','Z_value']
df['Z_value'] = pd.to_numeric(df['Z_value'])
resulting in this data frame.
X_value Y_value Z_value
0 a a 0.30
1 b a -0.30
2 c a 1.00
3 a b 0.50
4 b b -0.25
5 c b -1.00
6 a c 0.25
7 b c -0.23
8 c c 0.25
You cannot create a heatmap from this, however, by calling df.pivot('Y_value','X_value','Z_value')
, you rotate the data frame into a shape that can be used for a heatmap.
pivotted= df.pivot('Y_value','X_value','Z_value')
The resulting data file looks like this.
X_value a b c
Y_value
a 0.30 -0.30 1.00
b 0.50 -0.25 -1.00
c 0.25 -0.23 0.25
Then you can send pivotted
in sns.heatmap
to create your memory card.
sns.heatmap(pivotted,cmap='RdBu')
The result is in this heatmap.
You may need to make some code changes for your exact needs. But since I didn't have any data for the example, I had to make my own example.
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