import netCDF4 as nc import pandas as pd import numpy as np #文件读取 diri = 'D:/Science/graduation/data/result/' file = '成都平原背景.xlsx' sfile = 'cdpypre.xlsx' #输出文件 outfile = pd.ExcelWriter('D:/Science/graduation/data/result/sx成都平原背景.xlsx') #读取数据 data = pd.read_excel(diri+file,sheet_name='O3污染季节',header = 0) date = pd.read_excel(diri+sfile) #筛选掉降水量大于2mm的天数 data = data.loc[data.isin(date)].dropna() print(data)
时间: 2023-06-15 18:08:24 浏览: 48
这段代码是用来读取 netCDF4 格式文件中的数据,并进行简单的数据处理。具体来说,它使用了 pandas 库读取了两个 Excel 文件,一个是成都平原背景.xlsx,另一个是cdpypre.xlsx。然后使用 pd.ExcelWriter() 创建了一个名字为 sx成都平原背景.xlsx 的 Excel 输出文件。接着,利用 pd.read_excel() 读取了成都平原背景.xlsx 文件中 "O3污染季节" 工作表的数据,再次使用 pd.read_excel() 读取了 cdpypre.xlsx 文件中的数据。最后,它对 data 中的数据进行了筛选,把日期在 date 中的数据留下,去掉了降水量大于2mm的天数。输出了筛选后的 data 数据。
相关问题
import matplotlib.pyplot as plt import numpy as np import netCDF4 as nc import cartopy.crs as ccrs from cartopy.util import add_cyclic_point
I'm sorry, as an AI language model, I am not capable of displaying images or visualizations. However, I can provide you with the code for displaying a map using Cartopy and NetCDF4. Here's an example code:
```
import matplotlib.pyplot as plt
import numpy as np
import netCDF4 as nc
import cartopy.crs as ccrs
from cartopy.util import add_cyclic_point
# Load the NetCDF data
data = nc.Dataset('data.nc')
# Extract the variables
lon = data.variables['lon'][:]
lat = data.variables['lat'][:]
temp = data.variables['temp'][:]
# Add a cyclic point for plotting
temp, lon = add_cyclic_point(temp, coord=lon)
# Create a map projection
projection = ccrs.PlateCarree()
# Create a figure and axis
fig, ax = plt.subplots(subplot_kw={'projection': projection})
# Add coastlines
ax.coastlines()
# Plot the data
plt.contourf(lon, lat, temp, cmap='coolwarm', transform=projection)
# Add a colorbar
plt.colorbar()
plt.show()
```
In this example, we first load the NetCDF data and extract the variables we need. We then add a cyclic point to the temperature data to ensure it wraps around the plot correctly. Next, we create a map projection and a figure with an axis that uses the projection. We add coastlines to the plot and use `plt.contourf()` to plot the temperature data on the map. Finally, we add a colorbar to the plot and display it using `plt.show()`.
import xarray as xr import pandas as pd import cftime ds = xr.open_dataset('/Users/guodongjie/Documents/科研/data/Temp/2016-2023.nc')
看起来您正在使用xarray库打开一个名为'2016-2023.nc'的NetCDF文件。请继续,我会尽力帮助您解决任何问题。
请注意,要成功打开NetCDF文件,您需要确保已经安装了相关的依赖项,如netcdf4、h5py等。如果您尚未安装这些依赖项,您可以使用以下命令来安装它们:
```python
pip install netcdf4 h5py
```
如果您已经安装了这些依赖项,您可以尝试运行您的代码并将结果传递给变量'ds'。如果出现错误或异常,请提供完整的错误消息以便我能更好地帮助您。