[英]Is it possible to have a given number (n>2) of y-axes in matplotlib?
prices = pd.DataFrame(np.array([[1, 2, 3], [4, 5, 6], [7, 8, 9]]),
columns=['a', 'b', 'c'])
我有我的prices
數據框,它目前有 3 列。 但在其他時候,它可能有更多或更少的列。 有沒有辦法使用某種twinx()
循環來創建所有不同時間序列的折線圖,其中包含(可能)無限數量的 y 軸?
我嘗試了下面的雙循環,但我得到了typeError'd:bTypeError: 'AxesSubplot' object does not support item assignment
# for i in range(0,len(prices.columns)):
# for column in list(prices.columns):
# fig, ax[i] = plt.subplots()
# ax[i].set_xlabel(prices.index())
# ax[i].set_ylabel(column[i])
# ax[i].plot(prices.Date, prices[column])
# ax[i].tick_params(axis ='y')
#
# ax[i+1] = ax[i].twinx()
# ax[i+1].set_ylabel(column[i+1])
# ax[i+1].plot(prices.Date, column[i+1])
# ax[i+1].tick_params(axis ='y')
#
# fig.suptitle('matplotlib.pyplot.twinx() function \ Example\n\n', fontweight ="bold")
# plt.show()
# =============================================================================
我相信我明白為什么我會收到錯誤 - ax
對象不允許分配i
變量。 我希望有一些巧妙的方法來實現這一點。
原來,主要問題是你不應該將 Pandas 繪圖函數與 matplotlib 混合使用,這會導致軸重復。 否則,該實現是從這個matplotlib 示例中直接改編的。
from mpl_toolkits.axes_grid1 import host_subplot
import mpl_toolkits.axisartist as AA
from matplotlib import pyplot as plt
from itertools import cycle
import pandas as pd
#fake data creation with different spread for different axes
#this entire block can be deleted if you import your df
from pandas._testing import rands_array
import numpy as np
fakencol=5
fakenrow=7
np.random.seed(20200916)
df = pd.DataFrame(np.random.randint(1, 10, fakenrow*fakencol).reshape(fakenrow, fakencol), columns=rands_array(2, fakencol))
df = df.multiply(np.power(np.asarray([10]), np.arange(fakencol)))
df.index = pd.date_range("20200916", periods=fakenrow)
#defining a color scheme with unique colors
#if you want to include more than 20 axes, well, what can I say
sc_color = cycle(plt.cm.tab20.colors)
#defining the size of the figure in relation to the number of dataframe columns
#might need adjustment for optimal data presentation
offset = 60
plt.rcParams['figure.figsize'] = 10+df.shape[1], 5
#host figure and first plot
host = host_subplot(111, axes_class=AA.Axes)
h, = host.plot(df.index, df.iloc[:, 0], c=next(sc_color), label=df.columns[0])
host.set_ylabel(df.columns[0])
host.axis["left"].label.set_color(h.get_color())
host.set_xlabel("time")
#plotting the rest of the axes
for i, cols in enumerate(df.columns[1:]):
curr_ax = host.twinx()
new_fixed_axis = curr_ax.get_grid_helper().new_fixed_axis
curr_ax.axis["right"] = new_fixed_axis(loc="right",
axes=curr_ax,
offset=(offset*i, 0))
curr_p, = curr_ax.plot(df.index, df[cols], c=next(sc_color), label=cols)
curr_ax.axis["right"].label.set_color(curr_p.get_color())
curr_ax.set_ylabel(cols)
curr_ax.yaxis.label.set_color(curr_p.get_color())
plt.legend()
plt.tight_layout()
plt.show()
仔細想想 - 將軸平均分配到圖的左側和右側可能會更好。 那好吧。
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