Marine bypass for thin-film web
I have the following on the laptop DataFrame Jupyter , which shows using sea boat:
day_index avg_duration trips
0 0 708.852242 114586
1 1 676.702190 120936
2 2 684.572677 118882
3 3 708.925340 117868
4 4 781.767476 108036
5 5 1626.575057 43740
6 6 1729.155673 37508
daysOfWeek = ['Monday', 'Tuesday', 'Wednesday', 'Thursday\n', \
'Friday', 'Saturday', 'Sunday']
plt.figure(figsize=(16,10));
sns.set_style('ticks')
ax = sns.barplot(data=dfGroupedAgg, \
x='day_index', \
y='avg_duration', \
hue='trips', \
palette=sns.color_palette("Reds_d", n_colors=7, desat=1))
ax.set_xlabel("Week Days", fontsize=18, alpha=0.8)
ax.set_ylabel("Duration (seconds)", fontsize=18, alpha=0.8)
ax.set_title("Week average Trip Duration", fontsize=24)
ax.set_xticklabels(daysOfWeek, fontsize=16)
ax.legend(fontsize=15)
sns.despine()
plt.show()
Section A:
As you can see, the stripes do not match the x_ticklabels and are very thin.
This is all fixed, if I remove part hue='trips'
it is a known seafloor issue. Although it is very important to show the number of trips in the render like this: is there a way around nautical (perhaps with matplotlib directly) to add a tint attribute?
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I think you don't need to specify the parameter in this case hue
:
In [136]: ax = sns.barplot(data=dfGroupedAgg, \
...: x='day_index', \
...: y='avg_duration', \
...: palette=sns.color_palette("Reds_d", n_colors=7, desat=1))
...:
you can add the trip count as annotations:
def autolabel(rects, labels=None, height_factor=1.05):
for i, rect in enumerate(rects):
height = rect.get_height()
if labels is not None:
try:
label = labels[i]
except (TypeError, KeyError):
label = ' '
else:
label = '%d' % int(height)
ax.text(rect.get_x() + rect.get_width()/2., height_factor*height,
'{}'.format(label),
ha='center', va='bottom')
autolabel(ax.patches, labels=df.trips, height_factor=1.02)
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The argument hue
probably makes sense to introduce a new dimension to the graph, rather than showing a different quantity in one dimension.
It is most likely best to construct the rows with no argument hue
(this is quite misleading to actually call it a shade) and just color the rows according to the values in the column "trips"
.
This is also shown in this question: Seaborn Barplot - Displaying Values .
The code looks like this:
import matplotlib.pyplot as plt
import seaborn as sns
import pandas as pd
import numpy as np
di = np.arange(0,7)
avg = np.array([708.852242,676.702190,684.572677,708.925340,781.767476,
1626.575057,1729.155673])
trips = np.array([114586,120936,118882,117868,108036,43740,37508])
df = pd.DataFrame(np.c_[di, avg, trips], columns=["day_index","avg_duration", "trips"])
daysOfWeek = ['Monday', 'Tuesday', 'Wednesday', 'Thursday', \
'Friday', 'Saturday', 'Sunday']
plt.figure(figsize=(10,7));
sns.set_style('ticks')
v = df.trips.values
colors=plt.cm.viridis((v-v.min())/(v.max()-v.min()))
ax = sns.barplot(data=df, x='day_index', y='avg_duration', palette=colors)
for index, row in df.iterrows():
ax.text(row.day_index,row.avg_duration, row.trips, color='black', ha="center")
ax.set_xlabel("Week Days", fontsize=16, alpha=0.8)
ax.set_ylabel("Duration (seconds)", fontsize=16, alpha=0.8)
ax.set_title("Week average Trip Duration", fontsize=18)
ax.set_xticklabels(daysOfWeek, fontsize=14)
ax.legend(fontsize=15)
sns.despine()
plt.show()
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