重命名数据框的行和列

Rename the row and columns of a dataframe

我使用 python 提取了一个 NC 文件,在处理数据后,最终输出是一个包含 (199, 314) 的数组。我将数组转换为数据框,但行和列名称(索引)分别从零开始到 199 和 314。

from netCDF4 import Dataset
import numpy as np
import pandas as pd
data = Dataset('GolestanM.nc', 'r')
dims = data.dimensions
ndims = len(dims)
vars = data.variables
nvars = len(vars)
attrs = data.ncattrs
lon = data.variables['lon'][:]
lat = data.variables['lat'][:]
t = data.variables['time'][496]
fire = data.variables['FireMask'][496,:,:]                           
dataset = pd.DataFrame(fire)

但是,我想使用以下格式重命名这些索引: 列:名字 53.7042 然后 +0.0083 直到名字达到 56.3208

[0-->53.7042, 1-->53.7.25, ..., 314-->53.3208]

行数:名字 38.1125,然后是 -0.0083,直到名字达到 36.4625

[0-->38.1125, 1-->38.1042, ..., 199-->36.4625]

为此,我有以下代码:

dataset = dataset.rename(index={0: "38.1125"})
dataset = dataset.rename(columns={0: "53.7042"})
dataset = dataset.rename(index = lambda x: x + (0.0083),
                         columns = lambda x: x + (0.0083))

但是这样做会给我以下错误:

TypeError: can only concatenate str (not "float") to str

谁能帮我解决这个问题。

lambda 函数中的想法是多个 x(列或索引名称):

#sample data
dataset = pd.DataFrame(0, index=range(10), columns=range(10))


dataset = dataset.rename(index = lambda x: 38.1125 - 0.0083 * x ,
                          columns = lambda x: 53.7042  + 0.0083* x)

print (dataset)
         53.7042  53.7125  53.7208  53.7291  53.7374  53.7457  53.7540  \
38.1125        0        0        0        0        0        0        0   
38.1042        0        0        0        0        0        0        0   
38.0959        0        0        0        0        0        0        0   
38.0876        0        0        0        0        0        0        0   
38.0793        0        0        0        0        0        0        0   
38.0710        0        0        0        0        0        0        0   
38.0627        0        0        0        0        0        0        0   
38.0544        0        0        0        0        0        0        0   
38.0461        0        0        0        0        0        0        0   
38.0378        0        0        0        0        0        0        0   

         53.7623  53.7706  53.7789  
38.1125        0        0        0  
38.1042        0        0        0  
38.0959        0        0        0  
38.0876        0        0        0  
38.0793        0        0        0  
38.0710        0        0        0  
38.0627        0        0        0  
38.0544        0        0        0  
38.0461        0        0        0  
38.0378        0        0        0