如何设置海洋点图的x轴范围？

Question

I created a pointplot() and I cannot change x-axis limit. Although my data only contains 9 months, I want to show all 12 on my axis.

fig,ax = plt.subplots(figsize=(12,4))
sns.pointplot(data=tr_df, x='Month', y='numOfTrips', hue='Year', ax=ax, palette='nipy_spectral')
# sns.plt.xlim(0, 12) # AttributeError: module 'seaborn' has no attribute 'plt'
# ax.set_xlim=(0, 12) # does nothing
ax.set(xlim=(0, 12))
ax.set(title="Number of trips each month")

What am I doing wrong?

Edit: data used to create the plot

    Year Month numOfTrips
0   2011   7     2608
1   2011   8     33579
2   2011   9     34756
3   2011   10    31423
4   2011   11    20746
5   2012   3     12240
6   2012   4     37637
7   2012   5     46056
8   2012   6     48315
9   2012   7     61659
10  2012   8     75443
11  2012   9     73012
12  2012   10    67372
13  2012   11    40862
14  2013   4     56625
15  2013   5     88105
16  2013   6     99301
17  2013   7     92504

Answer 1

IMHO, seaborn's pointplot is not the kind of plot you are looking for.

I'd suggest a simple lineplot , then your attempt to set the xlims work as expected:

fig,ax = plt.subplots(figsize=(12,4))
sns.lineplot(data=tr_df, x='Month', y='numOfTrips', hue='Year', ax=ax, palette='nipy_spectral')
ax.set(xlim=(0, 12))
ax.set(title="Number of trips each month")

leads to

However, I'd also recommend to set the xticks in this context to some list with 12 values, while 0...12 has 13 ... ;-)

Answer 2

It's a bit of a hack, but it seems to work. I believe the issue is that pointplot ignores the numerical value of the axis and treats it like an ordinal. This code is a manual override:

fig,ax = plt.subplots(figsize=(12,4))
sns.pointplot(data=tr_df, x='Month', y='numOfTrips', hue='Year', ax=ax, palette='nipy_spectral')
ax.set_xticks(range(-3,10))
ax.set_xticklabels(range(12))
ax.set(title="Number of trips each month")

You are basically forcing the plot to add more ticks to the left and right (using minus values) and then rename all the labels 1 through 12.

Answer 3

It appears the issue is that your data only vary between months 3 and 11. The month indexing then begins at 3 and this corresponds to the xmin . An example which shows this using some random data (I generated it before you added the data) is

import seaborn as sns
import pandas as pd
import numpy as np

y = [2011,2012,2013]
years = []
months = []
trips = []
np.random.seed(0)
for ii in range(27):
    years.append(y[ii / 9])
    months.append(ii % 9+3)
    trips.append(np.random.randint(0,10)+(ii / 12)*10)

tr_df = pd.DataFrame({'Month':months, 'Trips':trips, 'Year':years})
fig,ax = plt.subplots(figsize=(12,4))
sns.pointplot(data=tr_df, x='Month', y='Trips', hue='Year', ax=ax, 
              palette='nipy_spectral', scale=0.7)
ax.set(xlim=(0, 12))
ax.set(title="Number of trips each month")
plt.show()

This will produce

The easiest way to fix this (though it does not fix the underlying data and won't work in all cases) is simply to set the limits manually to account for the offset -

ax.set(xlim=(-0.5, 8.5))

Which will give you

If you want to include the months lower than the minimum (ie 0,1,2) you can set the xticks and xticklabels manually -

ax.set_xticks(range(-3,9))
ax.set_xticklabels(range(0,12))

Which will give you