I'm trying to import a large .csv file containing text and numbers using genfromtxt
in numpy. I'm only interested in two columns. I have most of the import sorted out with:
def importfile(root):
data = root.entry.get()
atw = np.genfromtxt(data, delimiter=",",
skip_header=1,
skip_footer=2,
autostrip=True,
usecols=(25,26),
dtype=("|S10"))
elem = atw[:,0]
concs = atw[:,1]
print(elem)
print(concs)
With output for elem
and concs
respectively:
['Na2O' 'MgO' 'Al2O3' 'SiO2' 'P2O5' 'SO3' 'Cl' 'K2O' 'CaO' 'TiO2' 'Cr2O3'
'MnO' 'FeO' 'NiO' 'Cu2O' 'ZnO' 'Ga2O3' 'SrO' 'Y2O3']
['3.76E+00' '1.31E+01' '1.14E+01' '4.04E+01' '1.24E+00' '5.89E-02'
'2.43E-02' '1.53E+00' '1.49E+01' '2.87E+00' '6.05E-02' '1.96E-01'
'1.17E+01' '3.69E-02' '8.73E-03' '1.39E-02' '1.93E-03' '1.88E-01'
'5.58E-03']
I have tried many different things for converting the concs
string into a float, but it doesn't seem to like the fact that the concs are in scientific notation... is there a way to turn the concs
values into a float?
We can convert a string to float in Python using the float() function. This is a built-in function used to convert an object to a floating point number. Internally, the float() function calls specified object __float__() function.
[format(x, '. 0e') for x in A] works just as well. @vaultah: Both are good solutions!!
In Python, to print 2 decimal places we will use str. format() with “{:. 2f}” as string and float as a number. Call print and it will print the float with 2 decimal places.
Summary: Use the string literal syntax f"{number:. nf}" to suppress the scientific notation of a number to its floating-point representation.
The float
function can do this:
>>> float('1.31E+01') 13.1
or for a list:
>>> map(float, ['3.76E+00', '1.31E+01', '1.14E+01']) [3.76, 13.1, 11.4]
with open( datafile,'r' ) as inData: for line in inData: j = list( map( float, filter( None , [ x for x in line.strip().split(',') ] )) )
Just mentioned generally, as it solves a similar problem that brought me to this page.
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