将Python中的.sav文件转换成.csv文件

Question

I want to convert the contents of *.sav file into a *.csv file in Python. I have written the following lines of code to access the details of variables in *.sav file. Now, I am not clear on how I can write the accessed variable data to a.csv file with headers

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

Following is the result when I run the above lines of the code:

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'>]
--------------------------------------------------

Can anyone suggest me with how I can write all the variable data to a.csv file?

I want to write the variables (year, doy, d_lon, d_lat, on2_grid, on2_grid_smooth) to a CSV or ASCII file is supposed to look in the following manner:

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
..... 

The shape of "on2_grid" and "on2_grid_smooth" variables is the same and is (101, 202). Both are of the type "numpy.ndarray".

Answer 1

For what it's worth, you can import SPSS files very easily into Python using pandas :

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

And then you can export the data with the .to_csv() method:

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

If you only need to export certain columns, you can specify that too:

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

Answer 2

The column of latitude and longitude in the extracted files using your code looks interchanged. Further the latitude scale ranges from 0 to 180 (not +90 0 -90)) ...whether the 0 starts from the top. Pl. comment.

Answer 3

I know that this solution uses R instead of python, but it is really simple and works well.

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

Answer 4

I could solve my problem by changing the requisite output format and here is my code:

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

I am working on it and, for the moment, this is my 'poor' solution:

First I import module savReaderWriter to convert .sav file into structured array Second I import module numpy to convert structured array into 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()

The problem is that I lose name atributes during conversion. I will try to solve the problem.