Question

不幸的是，我对python还是很陌生，现在没有时间进行更深入的了解，因此我无法通过python控制台理解和解决错误显示程序。我正在尝试使用此代码从多个位置的多个netCDF文件中提取数据：

#this is for reading the .nc in the working folder
import glob
#this is reaquired ti read the netCDF4 data
from netCDF4 import Dataset 
#required to read and write the csv files
import pandas as pd
#required for using the array functions
import numpy as np


# Record all the years of the netCDF files into a Python list
all_years = []

for file in glob.glob('*.nc'):
    print(file)
    #reading the files
    data = Dataset(file, 'r')
    #saving the data variable time
    time = data.variables['time']
    #saving the year which is written in the file
    year = time.units[11:15]
    #once we have acquired the data for one year then it will combine it for all the years as we are using for loop here
    all_years.append(year)

# Creating an empty Pandas DataFrame covering the whole range of data and then we will read the required data and put it here
year_start = min(all_years) 
end_year = max(all_years)
date_range = pd.date_range(start = str(year_start) + '-01-01', 
                           end = str(end_year) + '-12-31', 
                           freq = 'D')

#an empty having 0.0 values dataframe will be created with two columns date_range and temperature
df = pd.DataFrame(0.0, columns = ['Precipitation'], index = date_range)
    

# Defining the names, lat, lon for the locations of your interest into a csv file
#this will read the file locations
locations = pd.read_csv('stations_locations.csv')

#we would use a for loop as we are interested in aquiring all the information one by one from the rows
for index, row in locations.iterrows():
    # one by one we will extract the information from the csv and put it into temp. variables
    location = row['names']
    location_lat = row['latitude']
    location_lon = row['longitude']

# Sorting the all_years just to be sure that model writes the data correctly
    all_years.sort()
    
    
    #now we will read the netCDF file and here I have used netCDF file from FGOALS model
    for yr in all_years:
        # Reading-in the data 
        data = Dataset('pr_day_CNRM-CM5_historical_r1i1p1_%s0101-%s1231.nc'%(yr,yr), 'r')
    
        # Storing the lat and lon data of the netCDF file into variables 
        lat = data.variables['lat'][:]
        lon = data.variables['lon'][:]
        
        #as we already have the co-ordinates of the point which needs to be downloaded
        #in order to find the closest point around it we need to substract the cordinates
        #and check which ever has the minimun distance
        # Squared difference between the specified lat,lon and the lat,lon of the netCDF 
        sq_diff_lat = (lat - location_lat)**2 
        sq_diff_lon = (lon - location_lon)**2
    
        # Identify the index of the min value for lat and lon
        min_index_lat = sq_diff_lat.argmin()
        min_index_lon = sq_diff_lon.argmin()
    
        # Accessing the average temparature data
        temp = data.variables['pr']
    
        # Creating the date range for each year during each iteration
        start = str(yr) + '-01-01'
        end = str(yr) + '-12-31'
        d_range = pd.date_range(start = start, 
                            end = end, 
                            freq = 'D')
    
        for t_index in np.arange(0, len(d_range)):
            print('Recording the value for: ' + str(location)+'_'+ str(d_range[t_index]))
            df.loc[d_range[t_index]]['Temparature'] = temp[t_index, min_index_lat, min_index_lon]

    df.to_csv(str(location) + '.csv')

这是显示的错误代码：

File "G:\Selection Cannon\Historical\CNRM-CM5_r1i1p1\pr\extracting data_CNRM-CM5_pr.py", line 62, in <module>
    data = Dataset('pr_day_CNRM-CM5_historical_r1i1p1_%s0101-%s1231.nc'%(yr,yr), 'r')

  File "netCDF4\_netCDF4.pyx", line 2321, in netCDF4._netCDF4.Dataset.__init__

  File "netCDF4\_netCDF4.pyx", line 1885, in netCDF4._netCDF4._ensure_nc_success

FileNotFoundError: [Errno 2] No such file or directory: b'pr_day_CNRM-CM5_historical_r1i1p1_18500101-18501231.nc'

当我检查变量/函数'time.units'时，它说“从1850-1-1开始的天数”，但文件夹中只有1975-2005年的文件。如果我勾选“ all_years”，它将仅显示“ 1850”七次。我认为这与“ year = time.units [11:15]”行有关，但这是youtube视频中的家伙这样做的方式。有人可以帮我解决这个问题，以便这段代码提取1975年及以后的文件吗？

最好的问候，亚历克斯

PS：这是我的第一篇文章，如果需要任何补充信息和数据，请告诉我：）

Answer 1

在进行其他任何操作之前，似乎您没有提供正确的路径。应当类似于“ G：/path/to/pr_day_CNRM-CM5_historical_r1i1p1_18500101-18501231.nc”。

使用python从netCDF文件中提取数据

1 个答案: