DataFrame.plot(x=None, y=None, kind='line', ax=None, subplots=False,
sharex=None, sharey=False, layout=None,figsize=None,
use_index=True, title=None, grid=None, legend=True,
style=None, logx=False, logy=False, loglog=False,
xticks=None, yticks=None, xlim=None, ylim=None, rot=None,
xerr=None,secondary_y=False, sort_columns=False, **kwds)
参数详解
Parameters:
参数 | 方法及用法 |
---|---|
x | label or position, default None#指数据框列的标签或位置参数 |
y | label or position, default None |
kind |
str ‘line’ : line plot (default)#折线图 ‘bar’ : vertical bar plot#条形图 ‘barh’ : horizontal bar plot#横向条形图 ‘hist’ : histogram#柱状图 ‘box’ : boxplot#箱线图 ‘kde’ : Kernel Density Estimation plot#Kernel 的密度估计图,主要对柱状图添加Kernel 概率密度线 ‘density’ : same as ‘kde’ ‘area’ : area plot#不了解此图 ‘pie’ : pie plot#饼图 ‘scatter’ : scatter plot#散点图 需要传入columns方向的索引 ‘hexbin’ : hexbin plot#不了解此图 |
ax | matplotlib axes object, default None 子图(axes, 也可以理解成坐标轴) 要在其上进行绘制的matplotlib subplot对象。如果没有设置,则使用当前matplotlib subplot** 其中,变量和函数通过改变figure和axes中的元素(例如:title,label,点和线等等)一起描述figure和axes,也就是在画布上绘图。 |
subplots | boolean, default False判断图片中是否有子图 Make separate subplots for each column |
sharex | boolean, default True if ax is None else False#如果有子图,子图共x轴刻度,标签 In case subplots=True, share x axis and set some x axis labels to invisible; defaults to True if ax is None otherwise False if an ax is passed in; Be aware, that passing in both an ax and sharex=True will alter all x axis labels for all axis in a figure! |
sharey | boolean, default False#如果有子图,子图共y轴刻度,标签 In case subplots=True, share y axis and set some y axis labels to invisible |
layout : | tuple (optional)#子图的行列布局 (rows, columns) for the layout of subplots |
figsize | a tuple (width, height) in inches#图片尺寸大小 |
use_index | boolean, default True#默认用索引做x轴 Use index as ticks for x axis |
title | string#图片的标题用字符串Title to use for the plot |
grid | boolean, default None (matlab style default)#图片是否有网格 Axis grid lines |
legend | False/True/’reverse’#子图的图例,添加一个subplot图例(默认为True) Place legend on axis subplots |
style | list or dict#对每列折线图设置线的类型 matplotlib line style per column |
logx | boolean, default False#设置x轴刻度是否取对数 Use log scaling on x axis |
logy | boolean, default False,Use log scaling on y axis |
loglog | boolean, default False#同时设置x,y轴刻度是否取对数 Use log scaling on both x and y axes |
xticks | sequence#设置x轴刻度值,序列形式(比如列表) Values to use for the xticks |
yticks | sequence#设置y轴刻度,序列形式(比如列表) Values to use for the yticks |
xlim | 2-tuple/list#设置坐标轴的范围,列表或元组形式 |
ylim | 2-tuple/list |
rot | int, default None#设置轴标签(轴刻度)的显示旋转度数 Rotation for ticks (xticks for vertical, yticks for horizontal plots) |
fontsize | int, default None#设置轴刻度的字体大小 Font size for xticks and yticks |
colormap | str or matplotlib colormap object, default None#设置图的区域颜色 Colormap to select colors from. If string, load colormap with that name from matplotlib. |
colorbar | boolean, optional #图片柱子 If True, plot colorbar (only relevant for ‘scatter’ and ‘hexbin’ plots) |
position | floatSpecify relative alignments for bar plot layout. From 0 (left/bottom-end) to 1 (right/top-end). Default is 0.5 (center) |
layout | tuple (optional) #布局 (rows, columns) for the layout of the plot |
table | boolean, Series or DataFrame, default False #如果为正,则选择DataFrame类型的数据并且转换匹配matplotlib的布局。 If True, draw a table using the data in the DataFrame and the data will be transposed to meet matplotlib’s default layout. If a Series or DataFrame is passed, use passed data to draw a table. |
yerr | DataFrame, Series, array-like, dict and str See Plotting with Error Bars for detail. |
xerr | same types as yerr. |
stacked | boolean, default False in line and bar plots, and True in area plot. If True, create stacked plot. |
sort_columns | boolean, default False # 以字母表顺序绘制各列,默认使用前列顺序 |
secondary_y | boolean or sequence, default False ##设置第二个y轴(右y轴 Whether to plot on the secondary y-axis If a list/tuple, which columns to plot on secondary y-axis |
mark_right | boolean, default True When using a secondary_y axis, automatically mark the column labels with “(right)” in the legend |
kwds | keywords Options to pass to matplotlib plotting method Returns:axes : matplotlib.AxesSubplot or np.array of them |
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