请问python出现这个问题Figures now render in the Plots pane by default. To make them also appear inline in the Console, uncheck "Mute Inline Plotting" under the Plots pane options menu.怎么办
时间: 2023-12-06 09:41:28 浏览: 25
这个问题是提示你在Jupyter Notebook中,图形默认会在Plots面板中渲染。如果你想将它们同时显示在Notebook中,需要取消选中Plots面板选项菜单下的"Mute Inline Plotting"选项。
解决方法:
1. 在Notebook中找到Plots面板选项菜单。
2. 取消"Mute Inline Plotting"选项。
3. 重新运行代码,图形会同时在Notebook中呈现。
相关问题
python报错: Warning Figures now render in the Plots pane by default. To make them also appear inline in the Console, uncheck "Mute Inline Plotting" under the Plots pane options menu.
这个警告信息是因为在 Jupyter Notebook 中,默认情况下会在 Plots pane 中渲染图形,而不是在 Notebook 的输出中显示。如果你想要在 Notebook 的输出中显示图形,可以按照警告信息中的提示,在 Plots pane 的选项菜单中取消 "Mute Inline Plotting" 的勾选即可。如果你不需要在 Notebook 中显示图形,忽略这个警告信息即可。
Open the data file using pandas and push data in numpy.array for plotting hydraulic fracturing operation diagram using matplotlib. You should obtain 4 figures something like.
Sure! To open the data file using pandas and plot the hydraulic fracturing operation diagram using matplotlib, you can follow the steps below:
1. Install the required libraries if you haven't already:
```python
pip install pandas matplotlib
```
2. Import the necessary libraries:
```python
import pandas as pd
import numpy as np
import matplotlib.pyplot as plt
```
3. Load the data file using pandas:
```python
data = pd.read_excel('path/to/data_file.xlsx')
```
Replace `'path/to/data_file.xlsx'` with the actual path to your data file.
4. Extract the necessary columns from the data:
Assuming your data file contains columns named `'Stage'`, `'Time'`, `'Pressure'`, and `'Rate'`, you can extract them as follows:
```python
stage = data['Stage']
time = data['Time']
pressure = data['Pressure']
rate = data['Rate']
```
5. Plot the hydraulic fracturing operation diagram:
```python
fig, axs = plt.subplots(2, 2, figsize=(12, 8))
axs[0, 0].plot(stage, pressure)
axs[0, 0].set_xlabel('Stage')
axs[0, 0].set_ylabel('Pressure')
axs[0, 1].plot(stage, rate)
axs[0, 1].set_xlabel('Stage')
axs[0, 1].set_ylabel('Rate')
axs[1, 0].plot(time, pressure)
axs[1, 0].set_xlabel('Time')
axs[1, 0].set_ylabel('Pressure')
axs[1, 1].plot(time, rate)
axs[1, 1].set_xlabel('Time')
axs[1, 1].set_ylabel('Rate')
plt.tight_layout()
plt.show()
```
The above code will create a 2x2 grid of subplots, where each subplot represents a different combination of `'Stage'`, `'Time'`, `'Pressure'`, and `'Rate'`. Adjust the size of the figure (`figsize`) as needed.
Make sure to replace `'Stage'`, `'Time'`, `'Pressure'`, and `'Rate'` with the actual column names in your data file.
Hope this helps! Let me know if you have any further questions.