python可视化分析绘制带趋势线的散点图和边缘直方图

import pandas as pd
import matplotlib as mpl
import matplotlib.pyplot as plt
import seaborn as sns
import warnings
warnings.filterwarnings(action='once')
plt.style.use('seaborn-whitegrid')
sns.set_style("whitegrid")
print(mpl.__version__)
print(sns.__version__)
def draw_scatter(file):
    # Import Data
    df = pd.read_csv(file)
    df_select = df.loc[df.cyl.isin([4, 8]), :]

    # Plot
    gridobj = sns.lmplot(
        x="displ",
        y="hwy",
        hue="cyl",
        data=df_select,
        height=7,
        aspect=1.6,
        palette='Set1',
        scatter_kws=dict(s=60, linewidths=.7, edgecolors='black'))
    # Decorations
    sns.set(style="whitegrid", font_scale=1.5)
    gridobj.set(xlim=(0.5, 7.5), ylim=(10, 50))
    gridobj.fig.set_size_inches(10, 6)
    plt.tight_layout()
    plt.title("Scatterplot with line of best fit grouped by number of cylinders")
    plt.show()
draw_scatter("F:\数据杂坛\datasets\mpg_ggplot2.csv")

import pandas as pd
import matplotlib as mpl
import matplotlib.pyplot as plt
import seaborn as sns
import warnings
warnings.filterwarnings(action='once')
plt.style.use('seaborn-whitegrid')
sns.set_style("whitegrid")
print(mpl.__version__)
print(sns.__version__)
def draw_Marginal_Histogram(file):
    # Import Data
    df = pd.read_csv(file)

    # Create Fig and gridspec
    fig = plt.figure(figsize=(10, 6), dpi=100)
    grid = plt.GridSpec(4, 4, hspace=0.5, wspace=0.2)
    # Define the axes
    ax_main = fig.add_subplot(grid[:-1, :-1])
    ax_right = fig.add_subplot(grid[:-1, -1], xticklabels=[], yticklabels=[])
    ax_bottom = fig.add_subplot(grid[-1, 0:-1], xticklabels=[], yticklabels=[])
    # Scatterplot on main ax
    ax_main.scatter('displ',
                    'hwy',
                    s=df.cty * 4,
                    c=df.manufacturer.astype('category').cat.codes,
                    alpha=.9,
                    data=df,
                    cmap="Set1",
                    edgecolors='gray',
                    linewidths=.5)
    # histogram on the right
    ax_bottom.hist(df.displ,
                   40,
                   histtype='stepfilled',
                   orientation='vertical',
                   color='#098154')
    ax_bottom.invert_yaxis()
    # histogram in the bottom
    ax_right.hist(df.hwy,
                  40,
                  histtype='stepfilled',
                  orientation='horizontal',
                  color='#098154')
    # Decorations
    ax_main.set(title='Scatterplot with Histograms \n displ vs hwy',
                xlabel='displ',
                ylabel='hwy')
    ax_main.title.set_fontsize(10)
    for item in ([ax_main.xaxis.label, ax_main.yaxis.label] +
                 ax_main.get_xticklabels() + ax_main.get_yticklabels()):
        item.set_fontsize(10)

    xlabels = ax_main.get_xticks().tolist()
    ax_main.set_xticklabels(xlabels)
    plt.show()
draw_Marginal_Histogram("F:\数据杂坛\datasets\mpg_ggplot2.csv")