将.sav文件转换为Python中的.CSV文件

Question

我想将 *.sav文件的内容转换为python中的 *.csv文件。我编写了以下代码行，以访问 *.sav文件中的变量的详细信息。现在，我尚不清楚如何将访问的变量数据写入带标头的.csv文件

import scipy.io as spio
on2file = 'ON2_2015_112m_220415.sav'
on2data = spio.readsav(on2file, python_dict=True, verbose=True)

以下是我运行代码上述行时的结果：

IDL Save file is compressed
 -> expanding to /var/folders/z4/r3844ql123jgkq1ztdr4jxrm0000gn/T/tmpVE_Iz6.sav
--------------------------------------------------
Date: Mon Feb 15 20:41:02 2016
User: zhangy1
Host: augur
--------------------------------------------------
Format: 9
Architecture: x86_64
Operating System: linux
IDL Version: 7.0
--------------------------------------------------
Successfully read 11 records of which:
 - 7 are of type VARIABLE
 - 1 are of type TIMESTAMP
 - 1 are of type NOTICE
 - 1 are of type VERSION
--------------------------------------------------
Available variables:
 - saved_data [<class 'numpy.recarray'>]
 - on2_grid_smooth [<type 'numpy.ndarray'>]
 - d_lat [<type 'numpy.float32'>]
 - on2_grid [<type 'numpy.ndarray'>]
 - doy [<type 'str'>]
 - year [<type 'str'>]
 - d_lon [<type 'numpy.float32'>]
--------------------------------------------------

谁能向我建议我如何将所有变量数据写入.csv文件？

我想将变量（年，doy，d_lon，d_lat，on2_grid，on2_grid_smooth）写入CSV或ASCII文件，应该以以下方式查看：

longitude, latitude, on2_grid, on2_grid_smooth   # header 
0.0,0.0,0.0,0.0              
0.0,0.0,0.0,0.0 
0.0,0.0,0.0,0.0 
0.0,0.0,0.0,0.0
..... 

" ON2_GRID"one_answers" ON2_GRID_SMOOTH"变量的形状是相同的（101，202）。两者都是类型的" numpy.ndarray"。

Answer 1

对于它的价值，您可以使用pandas非常轻松地将SPSS文件导入Python：

import pandas as pd
df = pd.read_spss("input_file.sav")

然后您可以使用.to_csv()方法导出数据：

df.to_csv("output_file.csv", index=False)

如果您只需要导出某些列，也可以指定：

df[["column_a", "column_b"]].to_csv("output_file.csv", index=False)

Answer 2

使用您的代码看起来互换的提取的文件中的纬度和经度列。此外，纬度刻度的范围从0到180（不是 90 0 -90））... 0是否从顶部开始。pl。评论。

Answer 3

我知道该解决方案使用r代替python，但它确实很简单并且效果很好。

library(foreign)
write.table(read.spss("inFile.sav"), file="outFile.csv", quote = TRUE, sep = ",")

Answer 4

我可以通过更改必要的输出格式来解决我的问题，这是我的代码：

import scipy.io as spio
import numpy as np
import csv
on2file = 'ON2_2016_112m_220415.sav'   # i/p file
outfile = 'ON2_2016_112m_220415.csv'   # o/p file
# Read i/p file
s = spio.readsav(on2file, python_dict=True, verbose=True)
# Creating Grid
#d_lat = s["d_lat"]
#d_lon = s["d_lon"]
lat = np.arange(-90,90,1.78218)  # (101,)
lon = np.arange(-180,180,1.78218)     # (202,)
ylat,xlon = np.meshgrid(lat,lon)
on2grid = np.asarray(s["on2_grid"])
on2gridsmooth = np.asarray(s["on2_grid_smooth"])
nrows = len(on2grid)
ncols = len(on2grid[0])
xlon_grid = xlon.reshape(nrows*ncols,1)
ylat_grid = ylat.reshape(nrows*ncols,1)
on2grid_new = on2grid.reshape(nrows*ncols,1)
on2gridsmooth_new = on2gridsmooth.reshape(nrows*ncols,1)
# Concatenation
allgriddata = np.concatenate((xlon_grid, ylat_grid, on2grid_new, on2gridsmooth_new),axis=1)
# Writing o/p file
f_handle = file(outfile,'a')
np.savetxt(f_handle,allgriddata,delimiter=",",fmt='%0.3f',header="longitude, latitude, on2_grid, on2_grid_smooth")
f_handle.close()

Answer 5

我正在研究它，目前，这是我的"可怜"解决方案：

首先，我导入模块savreaderwriter将.sav文件转换为结构化数组第二，i导入模块将结构化数组转换为CSV：

import savReaderWriter 
import numpy as np
reader_np = savReaderWriter.SavReaderNp("infile.sav")
array = reader_np.to_structured_array("outfile.dat") 
np.savetxt("outfile2.csv", array, delimiter=",")
reader_np.close()

问题是我在转换过程中失去了名字的侵犯。我将尝试解决问题。