尝试其他导入方法:如果上述方法都不起作用,尝试不使用matplotlib_inline,而是直接在代码中导入Matplotlib,例如: import matplotlib.pyplot as plt 而不是使用matplotlib_inline。通过遵循这些步骤,你应该能够解决“cannot import name ‘backend_inline’ from ‘m
gui, backend = self.shell.enable_matplotlib(args.gui) File "F:\Program Files\Python\Python36\Lib\site-packages\IPython\core\interactiveshell.py", line 3051, in enable_matplotlib pt.activate_matplotlib(backend) File "F:\Program Files\Python\Python36\Lib\site-packages\IPython\core\pylabtools.py"...
另外,值得一提的是,当在使用ipython或jupyter notebook等交互式环境下使用matplotlib时,可以在代码中使用%matplotlib魔术命令来设置后端。例如,%matplotlib inline将matplotlib的后端设置为inline,使得图形直接嵌入...
from plotly.subplots import make_subplots # 多子图 # 2、基于matplotlib importmatplotlib.pyplot as plt import matplotlib.patches as mpatches %matplotlib inline # 中文显示问题 plt.rcParams["font.sans-serif"]=["SimHei"] #设置字体 plt.rcParams["axes.unicode_minus"]=False #正常显示负号 # 3、基于...
matplotlib-inline 0.1.7 Inline Matplotlib backend f... mdurl 0.1.2 Markdown URL utilities mistune 3.1.3 A sane and fast Markdown pa... monotonic 1.6 An implementation of time.m... more-itertools 10.7.0 More routines for operating... msgpack 1.1.0 MessagePack serializer multidict 6.4.3 ...
pyplot as plt from matplotlib.patches import Ellipse import seaborn as sns import tensorflow as tf # importing Tensorflow import tensorflow_probability as tfp # and Tensorflow probability from tensorflow_probability import edward2 as ed # Edwardlib extension tfd = tfp.distributions # Basic probability ...
import matplotlib; matplotlib.use('Agg') # pylint: disable=multiple-statements The backend was *originally* set to 'module://ipykernel.pylab.backend_inline' by the following code: File "f:\program files\python\python36\lib\runpy.py", line 193, in _run_module_as_main ...
%matplotlib inline #正常显示画图时出现的中文和负号 from pylab import mpl mpl.rcParams['font.sans-serif']=['SimHei'] mpl.rcParams['axes.unicode_minus']=False 数据获取 用tushare获取上证行情数据作为分析样本。 #默认以上证指数交易数据为例
Thanks, this confirms that the issue ismatplotlib_inlinebeing imported beforepyqtgraph.canvas. I think I'll add explicit import suppression formatplotlib_inlineto our binary dependency analysis setup. Now that I think about it, we probably also need to ensure that collected Qt bindings packages are...
"matplotlib-inline==0.1.6", "multidict==6.0.4", "multidict==6.0.5", "natsort==8.4.0", "odfpy==1.4.1", "openpyxl==3.1.2", "oscrypto==1.3.0", "parso==0.8.3", "pexpect==4.9.0", "pillow==10.2.0", "prompt-toolkit==3.0.43", "psycopg[binary]==3.1.17", "psycopg==3.1....