I am trying to plot the "Tips" dataset from the Seaborn library, but when doing so I am only getting the dark background of the chart. The actual scatter plot and histogram along the edges are not showing.
I am running the code inside Spyder from the Anaconda distribution.
Where am I going wrong?
import seaborn as sns
import matplotlib as plt
sns.set(style="darkgrid", color_codes=True)
#Import data
tips = sns.load_dataset('tips')
tips.head()
sns.jointplot(x='total_bill', y='tip', data='tips')
plt.show()
here data="tips" is not a string
so you need to change the following line:
sns.jointplot(x='total_bill', y='tip', data=tips)
Related
I want to save a barplot, but found it was clipped when save it to a file.
import seaborn as sns
import matplotlib.pyplot as plt
tips = sns.load_dataset("tips")
sns.set_theme(font_scale=1.6)
fig,ax = plt.subplots(figsize=(8,6))
g = sns.barplot(x="tip", y="day", data=tips)
g.set(yticklabels=['Thur','Fri','Sat','Very long long long long Sun'])
fig.savefig('1.png',dpi=400)
Here is the figure shown in jupyter notebook
However, the figure saved was looked like this:
You should add bbox_index='tight' as a parameter and argument to plt.savefig()
fig.savefig('1.png',dpi=400, bbox_inches='tight')
Seaborn distplot is deprecated.
With distplot I get the following graph
with this code:
import matplotlib.pyplot as plt
import seaborn as sns
sns.distplot(random.normal(loc=177.8, scale=10.2, size=1000), kde=True)
sns.distplot(random.normal(loc=165.1, scale=8.9, size=1000), kde=True)
plt.show()
How do I achieve the same with displot please? If I just substitute displot for distplot, the histograms are displayed separately.
Any particular reason you want to use displot? Using histplot accomplishes your goal.
I have a problem with the use of tight_layout combined with jointplot. I have a dataframe df with my datas in two columns.
I create a jointplot with the command:
import seaborn as sns
import numpy as np
import matplotlib.pyplot as plt
sns.jointplot(df["time (ns)"],df["intesity (counts/s)"], kind='kde', shade=True, cmap="RdBu_r", n_levels=1000, space=0)
The problem is that the axis labels are partially outside of the figure: I solved using
plt.tight_layout()
Anyway this have the side effect to "erase" the space=0 option, resulting in a graph different from what I would like to obtain. Does someone knows how I can solve this problem?
try adding
plt.subplots_adjust(hspace=0, wspace=0)
after tight_layout()
I am new to matplotlib and seaborn and is currently trying to practice the two libraries using the classic titanic dataset. This might be elementary, but I'm trying to plot two factorplots side by side by inputting the argument ax = matplotlib axis as shown in the code below:
import matploblib.pyplot as plt
import seaborn as sns
%matplotlib inline
fig, (axis1,axis2) = plt.subplots(1,2,figsize=(15,4))
sns.factorplot(x='Pclass',data=titanic_df,kind='count',hue='Survived',ax=axis1)
sns.factorplot(x='SibSp',data=titanic_df,kind='count',hue='Survived',ax=axis2)
I was expecting the two factorplots side by side, but instead of just that, I ended up with two extra blank subplots as shown above
Edited: image was not there
Any call to sns.factorplot() actually creates a new figure, although the contents are drawn to the existing axes (axes1, axes2). Those figures are shown together with the original fig.
I guess the easiest way to prevent those unused figures from showing up is to close them, using plt.close(<figure number>).
Here is a solution for a notebook
import matplotlib.pyplot as plt
import seaborn as sns
import pandas as pd
%matplotlib inline
titanic_df = pd.read_csv(r"https://github.com/pcsanwald/kaggle-titanic/raw/master/train.csv")
fig, (axis1,axis2) = plt.subplots(1,2,figsize=(15,4))
sns.factorplot(x='pclass',data=titanic_df,kind='count',hue='survived',ax=axis1)
sns.factorplot(x='sibsp',data=titanic_df,kind='count',hue='survived',ax=axis2)
plt.close(2)
plt.close(3)
(For normal console plotting, remove the %matplotlib inline command and add plt.show() at the end.)
I am trying to generate the log-log plot of a vector, and save the generated plot to file.
This is what I have tried so far:
import matplotlib.pyplot as plt
...
plt.loglog(deg_distribution,'b-',marker='o')
plt.savefig('LogLog.png')
I am using Jupyter Notebook, in which I get the generated graph as output after statement 2 in the above code, but the saved file is blank.
Notice that pyplot has the concept of the current figure and the current axes. All plotting commands apply to the current axes. So, make sure you plot in the right axes. Here is a WME.
import matplotlib.pyplot as plt
fig, ax = plt.subplots()
ax.loglog(range(100), 'b-',marker='o')
plt.savefig('test.png') # apply to the axes `ax`