Consider the following example dataset (and the MWE
):
import pandas as pd
import matplotlib.pyplot as plt
import matplotlib.colors as mcolors
import seaborn as sns
data = {'trajectory': [101,102,102,102,102,102,102,102,104,104,104,104,104,104,104,107,107,107,107,
107,107,107,107,107,108,108,108,108,108,108,108,109,109,109,109,109,109,112,
112,112,112,112,113,113,113,113,114,114,114,114],
'segment': [1,1,1,1,2,2,3,3,1,1,2,2,2,3,3,1,1,2,2,2,2,3,3,3,1,1,1,
2,2,2,2,1,1,1,2,2,2,1,1,2,2,2,1,2,2,3,1,2,2,2],
'prediction': [3,0,0,1,3,3,2,2,0,0,4,4,2,0,0,0,0,2,2,2,3,0,0,2,0,0,1,1,
1,1,0,1,2,1,3,3,3,1,1,4,4,2,1,4,4,3,0,3,3,2]}
df = pd.DataFrame(data)
df.head(2)
trajectory segment prediction
0 101 1 3
1 102 1 0
Then I plot a heatmap of filtered data like so:
plot_data = (df.value_counts()
.sort_values(ascending=False).reset_index()
.drop_duplicates(['trajectory', 'segment'])
.pivot_table(index='trajectory', columns='segment', values='prediction'))
cmap = mcolors.ListedColormap(['c', 'b', 'g', 'y','m',])
fig, ax = plt.subplots(figsize=(10,6))
ax.set_facecolor('black')
sns.heatmap(plot_data, vmin=-0.5, vmax=4.5,cmap=cmap, annot=True)
colorbar = ax.collections[0].colorbar
colorbar.set_ticks([0, 1., 2., 3, 4])
colorbar.set_ticklabels(['Foot', 'Bike', 'Bus', 'Car', 'Metro'])
To produce:
But then I want to plot the heatmap with input 0
first, followed by inputs 1
, 2
, etc..
Required output:
CodePudding user response:
(in your desired result, the Bike values for trajectories 109, 112 and 113 should be in segment 1 instead of 2)