seaborn

问题 I am struggling to plot my data using pyplot.imshow . I use the 'RdBu_r' colormap, and I need the white color to be at value 1 on a logarithmic scale which is not centered at 1. But how can I do it? I tried 'center=1' which works for seaborn, but there is no such attribute in matplotlib. I also tried this: import matplotlib.pyplot as plt im=plt.imshow(proportion, cmap="RdBu_r", norm=LogNorm(), vmin=0.01, vmax=10) axs=plt.gca() cb = plt.colorbar(im, ax=axs,extend="both") where proportion is my

问题 I am trying to plot a heatmap using seaborn library. The plotting function looks like this: def plot_confusion_matrix(data, labels, **kwargs): """Visualize confusion matrix as a heat map.""" col_map = kwargs.get('color_palette', sns.light_palette('navy', n_colors=5, as_cmap=False)) sns.heatmap( vmin=0.0, vmax=1.0, data=data, cmap=col_map, xticklabels=labels, yticklabels=labels, linewidths=0.75, ) The histogram of the data , however, looks like this: Now the issue I am struggling with is that

问题 I have some data, based on which I am trying to build a countplot in seaborn. So I do something like this: data = np.hstack((np.random.normal(10, 5, 10000), np.random.normal(30, 8, 10000))).astype(int) plot_ = sns.countplot(data) and get my countplot: The problem is that ticks on the x-axis are too dense (which makes them useless). I tried to decrease the density with plot_.xticks=np.arange(0, 40, 10) but it didn't help. Also is there a way to make the plot in one color? 回答1: Tick frequency

问题 I have some data, based on which I am trying to build a countplot in seaborn. So I do something like this: data = np.hstack((np.random.normal(10, 5, 10000), np.random.normal(30, 8, 10000))).astype(int) plot_ = sns.countplot(data) and get my countplot: The problem is that ticks on the x-axis are too dense (which makes them useless). I tried to decrease the density with plot_.xticks=np.arange(0, 40, 10) but it didn't help. Also is there a way to make the plot in one color? 回答1: Tick frequency

问题 Can anyone give me a way to do a qq plot in Seaborn as a test for normality of data? Or failing that, at least in matplotlib. Thanks in advance 回答1: After reading the wikipedia article, I understand that the Q-Q plot is a plot of the quantiles of two distributions against each other. numpy.percentile allows to obtain the percentile of a distribution. Hence you can call numpy.percentile on each of the distributions and plot the results against each other. import numpy as np import matplotlib

问题 Is it possible to change the colors of the ytick labels in seaborn.clustermap? So for the seaborn Iris example, it is possible to set row colors based on species and plot a clustermap: import seaborn as sns iris = sns.load_dataset("iris") species = iris.pop("species") lut = dict(zip(species.unique(), "rbg")) row_colors = species.map(lut) g = sns.clustermap(iris) And it is possible to get a 1-1 correspondence between the plotted row and row label: g.ax_heatmap.yaxis.get_majorticklabels() Is

问题 I have a pandas dataframe with a datetime column. I would like to plot the distribution of the rows according to that date column, but I'm currenty getting an unhelpful error. I have: df['Date'] = pd.to_datetime(df['Date'], errors='raise') s = sns.distplot(df['Date']) which throws the error: TypeError: ufunc add cannot use operands with types dtype('<M8[ns]') and dtype('<M8[ns]') If I change the column I'm plotting to numeric data then it all works fine. How can I get the datetime column to

问题 I have a pandas dataframe with a datetime column. I would like to plot the distribution of the rows according to that date column, but I'm currenty getting an unhelpful error. I have: df['Date'] = pd.to_datetime(df['Date'], errors='raise') s = sns.distplot(df['Date']) which throws the error: TypeError: ufunc add cannot use operands with types dtype('<M8[ns]') and dtype('<M8[ns]') If I change the column I'm plotting to numeric data then it all works fine. How can I get the datetime column to

问题 I have a pandas dataframe with a datetime column. I would like to plot the distribution of the rows according to that date column, but I'm currenty getting an unhelpful error. I have: df['Date'] = pd.to_datetime(df['Date'], errors='raise') s = sns.distplot(df['Date']) which throws the error: TypeError: ufunc add cannot use operands with types dtype('<M8[ns]') and dtype('<M8[ns]') If I change the column I'm plotting to numeric data then it all works fine. How can I get the datetime column to

问题 I'm trying to look at a Seaborn pairplot for two different classes of variables and I'd like to see KDEs on the offdiagonals instead of scatterplots. The documentation has instructions on how to do a KDE for all of the data, but I want to see separate KDEs for each subclass of data. Suggestions welcome! My code looks something like this: plot = sns.pairplot( df, vars=labels, hue='has_accident', palette='Set1', diag_kind='kde', ) which results in: As you can see the data are sufficiently dense