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How to convert a string array to float array?

I basically first converted a multidimensional array to a string array in order to set the values as my dictionary key, and now I need to convert the string array back to a regular float array. For example, what I have is:
str_array = ['[0.25 0.2916666666666667]', '[0.5833333333333334 0.2916666666666667]',
'[0.5555555555555555 0.3333333333333332]']
And I literally just need it back as a regular array
array = [[0.25 0.2916666666666667], [0.5833333333333334 0.2916666666666667],
[0.5555555555555555 0.3333333333333332]]
I have tried all the following : (*independently)
for i in str_arr:
i.strip("'")
np.array(i)
float(i)
Yet none of them work. They either cannot convert str --> float or they still keep the type as a str. Please help.

Use ast.literal_eval to convert str to another data type
import ast
str_array = ['[0.25 0.2916666666666667]', '[0.5833333333333334 0.2916666666666667]',
'[0.5555555555555555 0.3333333333333332]']
result = [ast.literal_eval(i.replace(" ", ",")) for i in str_array]
print(result) # [[0.25, 0.2916666666666667], [0.5833333333333334, 0.2916666666666667], [0.5555555555555555, 0.3333333333333332]]

You can also use the basic function eval.
[eval(x.replace(" ",",")) for x in str_array]

How do I change the CSV data to a float?

I have a piece of code that is meant to read a CSV file that has data in it. I get this error message when I run the program, "ValueError: could not convert string to float:" How can I make my strings into floats?
,b,c,d,e,f,g,h,i,j,k,l,m,n,o,p,q,r = np.loadtxt('car.txt', delimiter = '\s', unpack = True)
plt.plot(o,r, label='Loaded from file!')
plt.xlabel('o')
plt.ylabel('r')
plt.title('Interesting Graph\nCheck it out')
plt.legend()
plt.show()
ValueError: could not convert string to float:

Python use float() function to convert a string into a float. The ValueError happens when Python doesn't know how to do so
for example
float("1.234") # return 1.234
float("1.45 ") # return 1.45
but if you do
float("abc")
This will cause a ValueErrror since Python doesn't know how to convert it.
Back to your question, maybe try to print your variable and check if it is valid to be converted to float.

if all your data are float, maybe:
1,the first rou are names not float
2,maybe there are 'backspace' in your data, they will be recognize as '/t', find a spack in your data,press ctrl+r,change backspace to space

Increasing efficiency of a string filter

I have a long text file containing a number of strings. Here is the part of the file:
tyh89= 13
kb2= 0
78%= yes
###bb1= 7634.0
iih54= 121
fgddd= no
#aa1= 0
#aa2= 1
#$ac3= 0
yt##hh= 0
#j= 12.1
##hf= no
So, basically all elements have a common structure of: header= value. My goal is to search for elements, whose headers contain specific string parts and read out those elements' values.
A the moment I do it with a rather straight approach: open/read the whole file as a string, differentiate it into list of elements and run if/elif conditions over all elements using a for loop. I provide my code below.
Is it the most efficient way to do it? Or is there a more efficient way to do it with not implementing the loop?
def main():
print(list(import_param()))
def import_param():
fl = open('filename','r')
cn = fl.read()
cn = cn.split('\n')
fl.close()
for st in cn:
if 'fgddd' in st:
el = st.split(' ')
yield float(el[1])
elif '#j' in st:
el = st.split(' ')
yield float(el[1])
if __name__ == '__main__': main()

yes, there is. You have to avoid testing if string contains a string, but rather focus on string equality.
Once you settle for equality, it means that you can create a set with the known keywords, split according to = and test if the set contains your value (using O(1) lookup):
key_set = {"fgddd","#j"}
for st in cn:
if '=' in st:
key,value = st.split("=",1)
if key in key_set:
el = value.strip()
yield float(el)
if you have different types, use a dictionary to convert to the proper type according to the key
key_set = {"fgddd":float ,"#j": float, "whatever":int , "something":str}
for st in cn:
if '=' in st:
key,value = st.split("=",1)
if key in key_set:
el = value.strip()
yield key_set[key](el) # apply type conversion
note that if you don't want any conversion, str will do the job as it returns itself when passed a string.
final note: if you have a say on the input format, suggest to use json instead of a custom format. Parsing becomes trivial using json module, and filtering can be achieved by the same way I've shown.

redis get the value from the result set

I have result returned as from ZrangebyScore function as [b'101']. I would like to extract only 101 value and discard other additional characters. It is in byte form. How to convert it in Integer format using Python.

If you are using Py3 try this:
mylist = [b'101']
val = int(mylist[0].decode())

Python: Extract multiple float numbers from string

Forgive me, I'm new to Python.
Given a string that starts with a float of indeterminate length and ends with the same, how can I extract both of them into an array, or if there is just one float, just the one.
Example:
"38.00,SALE ,15.20"
"69.99"
I'd like to return:
[38.00, 15.20]
[69.99]

You could also use regex to do this
import re
s = "38.00,SALE ,15.20"
p = re.compile(r'\d+\.\d+') # Compile a pattern to capture float values
floats = [float(i) for i in p.findall(s)] # Convert strings to float
print floats
Output:
[38.0, 15.2]

def extract_nums(text):
for item in text.split(','):
try:
yield float(item)
except ValueError:
pass
print list(extract_nums("38.00,SALE ,15.20"))
print list(extract_nums("69.99"))
[38.0, 15.2]
[69.99]
However by using float conversion you are losing precision, If you want to keep the precision you can use decimal:
import decimal
def extract_nums(text):
for item in text.split(','):
try:
yield decimal.Decimal(item)
except decimal.InvalidOperation:
pass
print list(extract_nums("38.00,SALE ,15.20"))
print list(extract_nums("69.99"))
[Decimal('38.00'), Decimal('15.20')]
[Decimal('69.99')]

You said you're only interested in floats at the start and end of the string, so assuming it's comma-delimited:
items = the_string.split(',')
try:
first = float(items[0])
except (ValueError, IndexError):
pass
try:
second = float(items[-1])
except (ValueError, IndexError):
pass
We have to wrap the operations in exception handlers since the value might not be a valid float (ValueError) or the index might not exist in the list (an IndexError).
This will handle all cases including if one or both of the floats is omitted.

You can try something like
the_string = "38.00,SALE ,15.20"
floats = []
for possible_float in the_string.split(','):
try:
floats.append (float (possible_float.strip())
except:
pass
print floats

Try a list comprehension:
just_floats = [i for i in your_list.split(',') if i.count('.') == 1]
first you split the string where the commas are, then you filter through the string and get rid of values that don't have a decimal place

import re
map(float, filter(lambda x: re.match("\s*\d+.?\d+\s*", x) , input.split(","))
Input : input = '38.00,SALE ,15.20' Output: [38.0, 15.2]
Input : input = '38.00,SALE ,15.20, 15, 34.' Output: [38.0, 15.2, 15.0, 34.0]
Explanation:
Idea is to split the string : list_to_filter = input.split(",") splits on ,
Then using regex filter strings which are real numbers: filtered_list = filter(<lambda>, list_to_filter) , here item is included in output of filter if lamda expression is true. So when re.match("\s*\d+.?\d+\s*", x) matches for string x filter keeps it.
And finally convert into float. map(float, filtered_list). What it does is apply float() function to each element of the list

Split the input, check if each element is numeric when the period is removed, convert to float if it is.
def to_float(input):
return [float(x) for x in input.split(",") if unicode(x).replace(".", "").isdecimal()]