You can also set figure size by passing dictionary to rc parameter with key ‘figure.figsize’ in seaborn set method: import seaborn as sns sns.set(rc={‘figure.figsize’:(11.7,8.27)}) Other alternative may be to use figure.figsize of rcParams to set figure size as below: from matplotlib import rcParams # figure size in inches rcParams[‘figure.figsize’] = 11.7,8.27 More details can be … Read more
import matplotlib.pyplot as plt from matplotlib.dates import date2num import datetime x = [ datetime.datetime(2011, 1, 4, 0, 0), datetime.datetime(2011, 1, 5, 0, 0), datetime.datetime(2011, 1, 6, 0, 0) ] x = date2num(x) y = [4, 9, 2] z = [1, 2, 3] k = [11, 12, 13] ax = plt.subplot(111) ax.bar(x-0.2, y, width=0.2, color=”b”, align=’center’) … Read more
You can use text. plt.text(x, y, s, fontsize=12) text coordinates can be given relative to the axis, so the position of your text will be independent of the size of the plot: The default transform specifies that text is in data coords, alternatively, you can specify text in axis coords (0,0 is lower-left and 1,1 … Read more
Firstly freq_series.plot returns an axis not a figure so to make my answer a little more clear I’ve changed your given code to refer to it as ax rather than fig to be more consistent with other code examples. You can get the list of the bars produced in the plot from the ax.patches member. … Read more
According to the docs, the param fmt=”.2g” is being applied because you’ve set annot=True so you can modify the format being applied to: sns.heatmap(table2,annot=True,cmap=’Blues’, fmt=”g”)
A Seaborn box plot returns a Matplotlib axes instance. Unlike pyplot itself, which has a method plt.title(), the corresponding argument for an axes is ax.set_title(). Therefore you need to call sns.boxplot(‘Day’, ‘Count’, data=gg).set_title(‘lalala’) A complete example would be: import seaborn as sns import matplotlib.pyplot as plt tips = sns.load_dataset(“tips”) sns.boxplot(x=tips[“total_bill”]).set_title(“LaLaLa”) plt.show() Of course you could … Read more
You can manually create the subplots with matplotlib, and then plot the dataframes on a specific subplot using the ax keyword. For example for 4 subplots (2×2): import matplotlib.pyplot as plt fig, axes = plt.subplots(nrows=2, ncols=2) df1.plot(ax=axes[0,0]) df2.plot(ax=axes[0,1]) … Here axes is an array which holds the different subplot axes, and you can access one … Read more
It seems none of the other answers here actually answer the question. So here is a code that uses a scatter and shows an annotation upon hovering over the scatter points. import matplotlib.pyplot as plt import numpy as np; np.random.seed(1) x = np.random.rand(15) y = np.random.rand(15) names = np.array(list(“ABCDEFGHIJKLMNO”)) c = np.random.randint(1,5,size=15) norm = plt.Normalize(1,4) … Read more
Seaborn’s barplot returns an axis-object (not a figure). This means you can do the following: import pandas as pd import seaborn as sns import matplotlib.pyplot as plt fake = pd.DataFrame({‘cat’: [‘red’, ‘green’, ‘blue’], ‘val’: [1, 2, 3]}) ax = sns.barplot(x = ‘val’, y = ‘cat’, data = fake, color=”black”) ax.set(xlabel=”common xlabel”, ylabel=”common ylabel”) plt.show()
There are several ways to do it. The subplots method creates the figure along with the subplots that are then stored in the ax array. For example: import matplotlib.pyplot as plt x = range(10) y = range(10) fig, ax = plt.subplots(nrows=2, ncols=2) for row in ax: for col in row: col.plot(x, y) plt.show() However, something … Read more