Problem in defining multidimensional array matrix and regression

Sun Nov 19 12:55:15 EST 2017

Hello Peter,
Many thanks for your suggestion. 
Now I am using Pandas &
I already did that but now I need to make a multi-dimensional array for reading all variables (5 in this case) at one x-axis, so I can perform multiple regression analysis. 
I am not getting how to bring all variables at one axis (e.g. at x-axis)?
Thanks
Vishal
On Sunday, 19 November 2017 22:32:06 UTC+5:30, Peter Otten wrote:
> shalu.ashu50 at gmail.com wrote:
>> > Hi, All,
> > 
> > I have 6 variables in CSV file. One is rainfall (dependent, at y-axis) and
> > others are predictors (at x). I want to do multiple regression and create
> > a correlation matrix between rainfall (y) and predictors (x; n1=5). Thus I
> > want to read rainfall as a separate variable and others in separate
> > columns, so I can apply the algo. However, I am not able to make a proper
> > matrix for them.
> > 
> > Here are my data and codes?
> > Please suggest me for the same.
> > I am new to Python.
> > 
> > RF	P1	P2	P3	P4	P5
> > 120.235	0.234	-0.012	0.145	21.023	0.233
> > 200.14	0.512	-0.021	0.214	22.21	0.332
> > 185.362	0.147	-0.32	0.136	24.65	0.423
> > 201.895	0.002	-0.12	0.217	30.25	0.325
> > 165.235	0.256	0.001	0.22	31.245	0.552
> > 198.236	0.012	-0.362	0.215	32.25	0.333
> > 350.263	0.98	-0.85	0.321	38.412	0.411
> > 145.25	0.046	-0.36	0.147	39.256	0.872
> > 198.654	0.65	-0.45	0.224	40.235	0.652
> > 245.214	0.47	-0.325	0.311	26.356	0.632
> > 214.02	0.18	-0.012	0.242	22.01	0.745
> > 147.256	0.652	-0.785	0.311	18.256	0.924
> > 
> > import numpy as np
> > import statsmodels as sm
> > import statsmodels.formula as smf
> > import csv
> > 
> > with open("pcp1.csv", "r") as csvfile:
> > readCSV=csv.reader(csvfile)
> > 
> > rainfall = []
> > csvFileList = []
> > 
> > for row in readCSV:
> > Rain = row[0]
> > rainfall.append(Rain)
> > 
> > if len (row) !=0:
> > csvFileList = csvFileList + [row]
> > 
> > print(csvFileList)
> > print(rainfall)
>> You are not the first to read tabular data from a file; therefore numpy (and 
> pandas) offer highlevel function to do just that. Once you have the complete 
> table extracting a specific column is easy. For instance:
>> $ cat rainfall.txt 
> RF P1 P2 P3 P4 P5
> 120.235 0.234 -0.012 0.145 21.023 0.233
> 200.14 0.512 -0.021 0.214 22.21 0.332
> 185.362 0.147 -0.32 0.136 24.65 0.423
> 201.895 0.002 -0.12 0.217 30.25 0.325
> 165.235 0.256 0.001 0.22 31.245 0.552
> 198.236 0.012 -0.362 0.215 32.25 0.333
> 350.263 0.98 -0.85 0.321 38.412 0.411
> 145.25 0.046 -0.36 0.147 39.256 0.872
> 198.654 0.65 -0.45 0.224 40.235 0.652
> 245.214 0.47 -0.325 0.311 26.356 0.632
> 214.02 0.18 -0.012 0.242 22.01 0.745
> 147.256 0.652 -0.785 0.311 18.256 0.924
> $ python3
> Python 3.4.3 (default, Nov 17 2016, 01:08:31) 
> [GCC 4.8.4] on linux
> Type "help", "copyright", "credits" or "license" for more information.
> >>> import numpy
> >>> rf = numpy.genfromtxt("rainfall.txt", names=True)
> >>> rf["RF"]
> array([ 120.235, 200.14 , 185.362, 201.895, 165.235, 198.236,
> 350.263, 145.25 , 198.654, 245.214, 214.02 , 147.256])
> >>> rf["P3"]
> array([ 0.145, 0.214, 0.136, 0.217, 0.22 , 0.215, 0.321, 0.147,
> 0.224, 0.311, 0.242, 0.311])