seaborn

问题 I produced a histogram which looks something like this: Code that I used to produce this plot: sns.countplot(table.column_name) As you can notice, the entire histogram gets clustered at the left end due to uneven distribution of data. How do I zoom in at the left end? One way that I tried and it gave me a marginally better result was : plt.xlim(0,25) Is there a better way to do this? 回答1: Looks like the data would be better viewed on a logarithmic scale. On your matplotlib plot axis, ax , use

问题 I produced a histogram which looks something like this: Code that I used to produce this plot: sns.countplot(table.column_name) As you can notice, the entire histogram gets clustered at the left end due to uneven distribution of data. How do I zoom in at the left end? One way that I tried and it gave me a marginally better result was : plt.xlim(0,25) Is there a better way to do this? 回答1: Looks like the data would be better viewed on a logarithmic scale. On your matplotlib plot axis, ax , use

问题 I produced a histogram which looks something like this: Code that I used to produce this plot: sns.countplot(table.column_name) As you can notice, the entire histogram gets clustered at the left end due to uneven distribution of data. How do I zoom in at the left end? One way that I tried and it gave me a marginally better result was : plt.xlim(0,25) Is there a better way to do this? 回答1: Looks like the data would be better viewed on a logarithmic scale. On your matplotlib plot axis, ax , use

问题 Is there a way to force scientific notation using Seaborn's Pairplot? I'm hoping for some consistency between plots (examples below). I've found suggestions for other seaborn plots, but have not successfully implemented anything with Pairplot. https://seaborn.pydata.org/generated/seaborn.pairplot.html Versions: seaborn 0.8.1 numpy 1.13.1 matplotlib 2.0.2 pandas 0.23.0 Current plot: import numpy as np import pandas as pd import seaborn as sns from scipy import stats import matplotlib.pyplot as

问题 I have three lists that I have loaded into a pandas dataframe. import pandas as pd df = pd.DataFrame({'x': location}) df = df.assign(y1 = variable1) df = df.assign(y2 = variable2) I would like to plot the correlation of y1 with y2 with x being the common x-axis. That is, really, I would like to bin y1 and y2 values according to x location, find the correlation of y1 with y2 within each bin and then plot a line of the correlations across the whole x domain. So my final plot will have

问题 I want to overlay a heatmap with a second chart (a KDEplot, but for this example I'll use a scatterplot, since it shows the same issue). Seaborn heatmaps have categorical axes, so overlaying a chart with numerical axes doesn't line up the two charts properly. Example: df = pd.DataFrame({2:[1,2,3],4:[1,3,5],6:[2,4,6]}, index=[3,6,9]) df 2 4 6 3 1 1 2 6 2 3 4 9 3 5 6 fig, ax1 = plt.subplots(1,1) sb.heatmap(df, ax=ax1, alpha=0.1) Overlaying this with a scatterplot: fig, ax1 = plt.subplots(1,1)

问题 I have a large df which I've grouped to plot in a bar chart. I made this mock df to show what I mean. (And I had way too much fun creating it...) my = pd.DataFrame( {'names': ['Andrea', 'Donna', 'Kelly', 'Brenda', 'Allison', 'Jo', 'Amanda', 'Jane', 'Kerry', 'Abby', 'Elizabeth', 'Haleh'], 'episodes': [ 147, 292, 292, 111, 160, 111, 199, 172, 250, 189, 160,184 ], 'tv-show' : ['Beverly Hills, 90210', 'Beverly Hills, 90210', 'Beverly Hills, 90210', 'Beverly Hills, 90210', 'Melrose place',

问题 I am plotting a grouped bar plot on which I overlay a swarmplot and errorbars. One of the groups only have one bar, which I want to appear (with the swarm and the errorbar) in the middle of the location allocated to this group of bars. I managed to move the bar and the errorbar, but not sure how to move the swarm. Here is the code I have: import seaborn as sns import matplotlib.pyplot as plt mypallet = sns.color_palette([(190/256,7/256, 18/256),(127/256, 127/256, 127/256)]) import itertools

问题 I am having trouble doing something that seems to me straightforward. My data is: ROE_SP500_Q2_2018_quantile.to_json() '{"index":{"0":0.0,"1":0.05,"2":0.1,"3":0.15,"4":0.2,"5":0.25,"6":0.3,"7":0.35,"8":0.4,"9":0.45,"10":0.5,"11":0.55,"12":0.6,"13":0.65,"14":0.7,"15":0.75,"16":0.8,"17":0.85,"18":0.9,"19":0.95},"ROE_Quantiles":{"0":-0.8931,"1":-0.0393,"2":0.00569,"3":0.03956,"4":0.05826,"5":0.075825,"6":0.09077,"7":0.10551,"8":0.12044,"9":0.14033,"10":0.15355,"11":0.17335,"12":0.1878,"13":0

问题 Is there a way to copy an axis (subplot) to a new figure? This is straightforward in other languages, but I understand that not even a deep copy would work with python's matplotlib. E.g. if I have a figure with 6 subplots, how can I copy 2 of those subplots to a new figure, with all the settings? Labels, tickmarks, legend, grid, etc. I have found this answer , which is actually 2 in 1: the first no longer works (deprecated syntax), while I couldn't get the second to work in my case. I manage