To ensure the labels are visible, you have to set the parameters xticklabels, yticklabels to True, like so. import seaborn as sns sns.heatmap(dataframe, xticklabels=True, yticklabels=True) Here’s the documentation for the heatmap function.
If you have a standard python installation, update with pip: pip install -U seaborn If you are using an Anaconda distribution, at the anaconda prompt (base) environment, or activate the appropriate environment: # update all the packages in the environment conda update –all # or conda update seaborn See Anaconda: Managing Packages
Very easy with Pandas. import pandas from collections import Counter a = [‘a’, ‘a’, ‘a’, ‘a’, ‘b’, ‘b’, ‘c’, ‘c’, ‘c’, ‘d’, ‘e’, ‘e’, ‘e’, ‘e’, ‘e’] letter_counts = Counter(a) df = pandas.DataFrame.from_dict(letter_counts, orient=”index”) df.plot(kind=’bar’) Notice that Counter is making a frequency count, so our plot type is ‘bar’ not ‘hist’.
IIUC you can format the xticks and set these: In[60]: #generate some psuedo data df = pd.DataFrame({‘num’:[50000, 75000, 100000, 125000], ‘Rent/Sqft’:np.random.randn(4), ‘Region’:list(‘abcd’)}) df Out[60]: num Rent/Sqft Region 0 50000 0.109196 a 1 75000 0.566553 b 2 100000 -0.274064 c 3 125000 -0.636492 d In[61]: import matplotlib.pyplot as plt import matplotlib.ticker as ticker import seaborn as … Read more
Use the scatter_kws argument. For example: ax = sb.regplot(x=”total_bill”, y=”tip”, data=tips, scatter_kws={‘alpha’:0.3})
The answer from here makes fonts larger in seaborn … import pandas as pd, numpy as np, seaborn as sns from matplotlib import pyplot as plt # Generate data df = pd.DataFrame({“Draughts”: np.random.randn(100)}) # Plot using seaborn sns.set(font_scale = 2) b = sns.violinplot(y = “Draughts”, data = df) plt.show()
As part of the update to matplotlib 2.0 the edges on bar plots are turned off by default. However, this behavior can be globally changed with rcParams. plt.rcParams[“patch.force_edgecolor”] = True Alternatively, set the edgecolor / ec parameter in the plot call, and potentially increase the linewidth / lw parameter. Tested in python 3.11.4, pandas 2.0.3, … Read more
You get that error because matplotlib and its objects are completely unaware of seaborn functions. Pass your axes objects (i.e., ax1 and ax2) to seaborn.regplot or you can skip defining those and use the col kwarg of seaborn.lmplot With your same imports, pre-defining your axes and using regplot looks like this: # create df x … Read more
Have you tried the ci argument? According to the documentation: ci : float or None, optional Size of confidence intervals to draw around estimated values. If None, no bootstrapping will be performed, and error bars will not be drawn. sns.barplot(x=df[‘Time’], y=df[‘Volume_Count’], ax=ax7, ci=None)
you can use the order parameter for this. sns.barplot(x=’Id’, y=”Speed”, data=df, order=result[‘Id’]) Credits to Wayne. See the rest of his code. This link is still working for me. But, for the sake of convenience, I’m pasting the author’s code here. result = df.groupby([“Id”])[‘Speed’].aggregate(np.median).reset_index().sort_values(‘Speed’) sns.barplot(x=’Id’, y=”Speed”, data=df, order=result[‘Id’]) plt.show() df Id Speed 0 1 30 1 … Read more