Encountered a problem whereby my JSON data gets printed as a scientific notation instead of a float.
import urllib2
import json
import sys
url = 'https://bittrex.com/api/v1.1/public/getmarketsummary?market=btc-quid'
json_obj = urllib2.urlopen(url)
QUID_data = json.load(json_obj)
QUID_MarketName_Trex = QUID_data["result"][0]["MarketName"][4:9]
QUID_Last_Trex = QUID_data["result"][0]["Last"]
QUID_High_Trex = QUID_data["result"][0]["High"]
QUID_Low_Trex = QUID_data["result"][0]["Low"]
QUID_Volume_Trex = QUID_data["result"][0]["Volume"]
QUID_BaseVolume_Trex = QUID_data["result"][0]["BaseVolume"]
QUID_TimeStamp_Trex = QUID_data["result"][0]["TimeStamp"]
QUID_Bid_Trex = QUID_data["result"][0]["Bid"]
QUID_Ask_Trex = QUID_data["result"][0]["Ask"]
QUID_OpenBuyOrders_Trex = QUID_data["result"][0]["OpenBuyOrders"]
QUID_OpenSellOrders_Trex = QUID_data["result"][0]["OpenSellOrders"]
QUID_PrevDay_Trex = QUID_data["result"][0]["PrevDay"]
QUID_Created_Trex = QUID_data["result"][0]["Created"]
QUID_Change_Trex = ((QUID_Last_Trex - QUID_PrevDay_Trex)/ QUID_PrevDay_Trex)*100
QUID_Change_Var = str(QUID_Change_Trex)
QUID_Change_Final = QUID_Change_Var[0:5] + '%'
print QUID_Last_Trex
It prints the following value; 1.357e-05.
I need this to be a float with 8 chars behind the decimal (0.00001370)
As you can see here --> http://i.imgur.com/FCVM1UN.jpg, my GUI displays the first row correct (using the exact same code).
You are looking at the default str() formatting of floating point numbers, where scientific notation is used for sufficiently small or large numbers.
You don't need to convert this, the value itself is a proper float. If you need to display this in a different format, format it explicitly:
>>> print(0.00001357)
1.357e-05
>>> print(format(0.00001357, 'f'))
0.000014
>>> print(format(0.00001357, '.8f'))
0.00001357
Here the f format always uses fixed point notation for the value. The default precision is 6 digits; the .8 instructs the f formatter to show 8 digits instead.
In Python 3, the default string format is essentially the same as format(fpvalue, '.16g'); the g format uses either a scientific or fixed point presentation depending on the exponent of the number. Python 2 used '.12g'.
You can use print formatting:
x = 1.357e-05
print('%f' % x)
Edit:
print('%.08f' % x)
There are some approaches:
#1 float(...) + optionally round() or .format()
x = float(1.357e-05)
round(x, 6)
"{:.8f}".format(x)
#2 with decimal class
import decimal
tmp = decimal.Decimal('1.357e-05')
print('[0]', tmp)
# [0] 0.00001357
tmp = decimal.Decimal(1.357e-05)
print('[1]', tmp)
# [1] 0.0000135700000000000005188384444299032338676624931395053863525390625
decimal.getcontext().prec = 6
tmp = decimal.getcontext().create_decimal(1.357e-05)
print('[2]', tmp)
# [2] 0.0000135700
#3 with .rstrip(...)
x = ("%.17f" % n).rstrip('0').rstrip('.')
Note: there are counterparts to %f:
%f shows standard notation
%e shows scientific notation
%g shows default (scientific if 5 or more zeroes)
Related
I'm working on a Python script that will read a file and grab a string total_time. Currently, this is what I have.
if("Total time" in data):
total_time=int(filter(str.isdigit, data))
print(total_time)
Output: 419
I'm trying to find the best way to read lots of files, grab this total time, and convert 419 into 4 hours and 19 minutes to allow me to do some statics and analytics with this.
Passing format argument to datetime in Pandas:
t="419"
a = pd.to_datetime(t, format='%H%M')
print(a.hour)
print(a.minute)
The built-in function divmod() seems appropriate here!
>>> a = 5
>>> b = 3
>>> divmod(a,b) # (a // b, a % b)
(1,2)
For your specific situation:
def dataToTime(data):
''' Returns a list of (hour, minute) tuples from
a list of strings '''
total_times = filter(str.isdigit,data)
return [divmod(int(time),100) for time in total_times]
If you would like to parse the data as you are inputting it try the re module which has the method re.sub() for regex substitution
>>> import re
>>> s = '| Total time | 4:19 | | |--------------+--------+------| –'
>>> h = int(re.sub(r':.*$|[^0-9]','',s))
>>> m = int(re.sub(r'^.*:|[^0-9]','',s))
>>> print h,m
(4,19)
Given some string set as
s = '419'
you can get the upper and lower digits by converting to an integer, then using modulo and integer division. The integer conversion can be encapsulated in a try-except block catching ValueError if you have a reasonable response to invalid inputs:
n = int(s)
hours = n // 100 # Truncating integer division
minutes = n % 100 # Modulo removes the upper digits
I'm trying to modify the code shown far below, which works in Python 2.7.x, so it will also work unchanged in Python 3.x. However I'm encountering the following problem I can't solve in the first function, bin_to_float() as shown by the output below:
float_to_bin(0.000000): '0'
Traceback (most recent call last):
File "binary-to-a-float-number.py", line 36, in <module>
float = bin_to_float(binary)
File "binary-to-a-float-number.py", line 9, in bin_to_float
return struct.unpack('>d', bf)[0]
TypeError: a bytes-like object is required, not 'str'
I tried to fix that by adding a bf = bytes(bf) right before the call to struct.unpack(), but doing so produced its own TypeError:
TypeError: string argument without an encoding
So my questions are is it possible to fix this issue and achieve my goal? And if so, how? Preferably in a way that would work in both versions of Python.
Here's the code that works in Python 2:
import struct
def bin_to_float(b):
""" Convert binary string to a float. """
bf = int_to_bytes(int(b, 2), 8) # 8 bytes needed for IEEE 754 binary64
return struct.unpack('>d', bf)[0]
def int_to_bytes(n, minlen=0): # helper function
""" Int/long to byte string. """
nbits = n.bit_length() + (1 if n < 0 else 0) # plus one for any sign bit
nbytes = (nbits+7) // 8 # number of whole bytes
bytes = []
for _ in range(nbytes):
bytes.append(chr(n & 0xff))
n >>= 8
if minlen > 0 and len(bytes) < minlen: # zero pad?
bytes.extend((minlen-len(bytes)) * '0')
return ''.join(reversed(bytes)) # high bytes at beginning
# tests
def float_to_bin(f):
""" Convert a float into a binary string. """
ba = struct.pack('>d', f)
ba = bytearray(ba)
s = ''.join('{:08b}'.format(b) for b in ba)
s = s.lstrip('0') # strip leading zeros
return s if s else '0' # but leave at least one
for f in 0.0, 1.0, -14.0, 12.546, 3.141593:
binary = float_to_bin(f)
print('float_to_bin(%f): %r' % (f, binary))
float = bin_to_float(binary)
print('bin_to_float(%r): %f' % (binary, float))
print('')
To make portable code that works with bytes in both Python 2 and 3 using libraries that literally use the different data types between the two, you need to explicitly declare them using the appropriate literal mark for every string (or add from __future__ import unicode_literals to top of every module doing this). This step is to ensure your data types are correct internally in your code.
Secondly, make the decision to support Python 3 going forward, with fallbacks specific for Python 2. This means overriding str with unicode, and figure out methods/functions that do not return the same types in both Python versions should be modified and replaced to return the correct type (being the Python 3 version). Do note that bytes is a reserved word, too, so don't use that.
Putting this together, your code will look something like this:
import struct
import sys
if sys.version_info < (3, 0):
str = unicode
chr = unichr
def bin_to_float(b):
""" Convert binary string to a float. """
bf = int_to_bytes(int(b, 2), 8) # 8 bytes needed for IEEE 754 binary64
return struct.unpack(b'>d', bf)[0]
def int_to_bytes(n, minlen=0): # helper function
""" Int/long to byte string. """
nbits = n.bit_length() + (1 if n < 0 else 0) # plus one for any sign bit
nbytes = (nbits+7) // 8 # number of whole bytes
ba = bytearray(b'')
for _ in range(nbytes):
ba.append(n & 0xff)
n >>= 8
if minlen > 0 and len(ba) < minlen: # zero pad?
ba.extend((minlen-len(ba)) * b'0')
return u''.join(str(chr(b)) for b in reversed(ba)).encode('latin1') # high bytes at beginning
# tests
def float_to_bin(f):
""" Convert a float into a binary string. """
ba = struct.pack(b'>d', f)
ba = bytearray(ba)
s = u''.join(u'{:08b}'.format(b) for b in ba)
s = s.lstrip(u'0') # strip leading zeros
return (s if s else u'0').encode('latin1') # but leave at least one
for f in 0.0, 1.0, -14.0, 12.546, 3.141593:
binary = float_to_bin(f)
print(u'float_to_bin(%f): %r' % (f, binary))
float = bin_to_float(binary)
print(u'bin_to_float(%r): %f' % (binary, float))
print(u'')
I used the latin1 codec simply because that's what the byte mappings are originally defined, and it seems to work
$ python2 foo.py
float_to_bin(0.000000): '0'
bin_to_float('0'): 0.000000
float_to_bin(1.000000): '11111111110000000000000000000000000000000000000000000000000000'
bin_to_float('11111111110000000000000000000000000000000000000000000000000000'): 1.000000
float_to_bin(-14.000000): '1100000000101100000000000000000000000000000000000000000000000000'
bin_to_float('1100000000101100000000000000000000000000000000000000000000000000'): -14.000000
float_to_bin(12.546000): '100000000101001000101111000110101001111110111110011101101100100'
bin_to_float('100000000101001000101111000110101001111110111110011101101100100'): 12.546000
float_to_bin(3.141593): '100000000001001001000011111101110000010110000101011110101111111'
bin_to_float('100000000001001001000011111101110000010110000101011110101111111'): 3.141593
Again, but this time under Python 3.5)
$ python3 foo.py
float_to_bin(0.000000): b'0'
bin_to_float(b'0'): 0.000000
float_to_bin(1.000000): b'11111111110000000000000000000000000000000000000000000000000000'
bin_to_float(b'11111111110000000000000000000000000000000000000000000000000000'): 1.000000
float_to_bin(-14.000000): b'1100000000101100000000000000000000000000000000000000000000000000'
bin_to_float(b'1100000000101100000000000000000000000000000000000000000000000000'): -14.000000
float_to_bin(12.546000): b'100000000101001000101111000110101001111110111110011101101100100'
bin_to_float(b'100000000101001000101111000110101001111110111110011101101100100'): 12.546000
float_to_bin(3.141593): b'100000000001001001000011111101110000010110000101011110101111111'
bin_to_float(b'100000000001001001000011111101110000010110000101011110101111111'): 3.141593
It's a lot more work, but in Python3 you can more clearly see that the types are done as proper bytes. I also changed your bytes = [] to a bytearray to more clearly express what you were trying to do.
I had a different approach from #metatoaster's answer. I just modified int_to_bytes to use and return a bytearray:
def int_to_bytes(n, minlen=0): # helper function
""" Int/long to byte string. """
nbits = n.bit_length() + (1 if n < 0 else 0) # plus one for any sign bit
nbytes = (nbits+7) // 8 # number of whole bytes
b = bytearray()
for _ in range(nbytes):
b.append(n & 0xff)
n >>= 8
if minlen > 0 and len(b) < minlen: # zero pad?
b.extend([0] * (minlen-len(b)))
return bytearray(reversed(b)) # high bytes at beginning
This seems to work without any other modifications under both Python 2.7.11 and Python 3.5.1.
Note that I zero padded with 0 instead of '0'. I didn't do much testing, but surely that's what you meant?
In Python 3, integers have a to_bytes() method that can perform the conversion in a single call. However, since you asked for a solution that works on Python 2 and 3 unmodified, here's an alternative approach.
If you take a detour via hexadecimal representation, the function int_to_bytes() becomes very simple:
import codecs
def int_to_bytes(n, minlen=0):
hex_str = format(n, "0{}x".format(2 * minlen))
return codecs.decode(hex_str, "hex")
You might need some special case handling to deal with the case when the hex string gets an odd number of characters.
Note that I'm not sure this works with all versions of Python 3. I remember that pseudo-encodings weren't supported in some 3.x version, but I don't remember the details. I tested the code with Python 3.5.
(update)
Here's the actual problem I'm seeing. Note that round() doesn't seem to be doing the trick.
Here's my code:
t0=time.time()
# stuff
t1=time.time()
perfdat={'et1' : round(t1-t0,6), 'et2': '%.6f'%(t1-t0)}
And the dict and json output, respectively:
{'et2': '0.010214', 'et1': 0.010214000000000001}
{"et2":"0.010214","et1":0.010214000000000001}
(end update)
I've got a floating point value that has a lot of extra digits of precision that I don't need. Is there a way to truncate those digits when formatting a json string?
I can get the truncation I need if I format the value as a string, but I would like to transmit the value as a (truncated) number.
import json
v=2.030000002
json.dumps({'x':v}) # would like to just have 2.030
'{"x": 2.030000002}'
s= '%.3f' % (v) # like this, but not as a string
json.dumps({'x' : s})
'{"x": "2.030"}'
Wrap the number into a float:
>>> s = float('%.3f' % (v))
>>> json.dumps({'x' : s})
{"x": 2.03}
Builtin function round can help
In [16]: v=2.030000002
In [17]: json.dumps({'x': round(v, 3)})
Out[17]: '{"x": 2.03}'
This is something I found from from the Python Standard library:
"Unlike hardware based binary floating point, the decimal module has a user alterable precision (defaulting to 28 places) which can be as large as needed for a given problem:
>>> from decimal import *
>>> getcontext().prec = 6
>>> Decimal(1) / Decimal(7)
Decimal('0.142857')
>>> getcontext().prec = 28
>>> Decimal(1) / Decimal(7)
Decimal('0.1428571428571428571428571429')
"
A better import statement would be:
from decimal import getcontext, Decimal
Then you could apply those same functions to specify an arbitrary precision. Hope this helps! I haven't actually used this before.
For your case: (still has the trailing zero issue)
getcontext().prec = 3
s = '2.030'
var = float(Decimal(s))
var returns 2.03
This following approach seems promising:
import json
v = 2.030000002
result = []
for part in json.JSONEncoder().iterencode({'x': v}):
try:
tmp = round(float(part), 3)
except ValueError:
pass
else:
part = '{:.3f}'.format(tmp)
result.append(part)
result = ''.join(result)
print result # -> {"x": 2.030}
I have a program that is a converter for times in minutes and seconds and returns a float value with a decimal, for example:
6.57312
I would like to extract the .57312 part in order to convert it to seconds.
How can I get python to take only the value after the decimal point and put it into a variable that I can then use for the conversion?
You can do just a simple operation
dec = 6.57312 % 1
math.modf does that. It also has the advantage that you get the whole part in the same operation.
import math
f,i = math.modf(6.57312)
# f == .57312, i==6.0
Example program:
import math
def dec_to_ms(value):
frac,whole = math.modf(value)
return "%d:%02d"%(whole, frac*60)
print dec_to_ms(6.57312)
You can do this also
num = 6.57312
dec = num - int(num)
For a project in one of my classes we have to output numbers up to five decimal places.It is possible that the output will be a complex number and I am unable to figure out how to output a complex number with five decimal places. For floats I know it is just:
print "%0.5f"%variable_name
Is there something similar for complex numbers?
You could do it as is shown below using the str.format() method:
>>> n = 3.4+2.3j
>>> n
(3.4+2.3j)
>>> '({0.real:.2f} + {0.imag:.2f}i)'.format(n)
'(3.40 + 2.30i)'
>>> '({c.real:.2f} + {c.imag:.2f}i)'.format(c=n)
'(3.40 + 2.30i)'
To make it handle both positive and negative imaginary portions properly, you would need a (even more) complicated formatting operation:
>>> n = 3.4-2.3j
>>> n
(3.4-2.3j)
>>> '({0:.2f} {1} {2:.2f}i)'.format(n.real, '+-'[n.imag < 0], abs(n.imag))
'(3.40 - 2.30i)'
Update - Easier Way
Although you cannot use f as a presentation type for complex numbers using the string formatting operator %:
n1 = 3.4+2.3j
n2 = 3.4-2.3j
try:
print('test: %.2f' % n1)
except Exception as exc:
print('{}: {}'.format(type(exc).__name__, exc))
Output:
TypeError: float argument required, not complex
You can however use it with complex numbers via the str.format() method. This isn't explicitly documented, but is implied by the Format Specification Mini-Language documentation which just says:
'f' Fixed point. Displays the number as a fixed-point number. The default precision is 6.
. . .so it's easy to overlook.
In concrete terms, the following works in both Python 2.7.14 and 3.4.6:
print('n1: {:.2f}'.format(n1))
print('n2: {:.2f}'.format(n2))
Output:
n1: 3.10+4.20j
n2: 3.10-4.20j
This doesn't give you quite the control the code in my original answer does, but it's certainly much more concise (and handles both positive and negative imaginary parts automatically).
Update 2 - f-strings
Formatted string literals (aka f-strings) were added in Python 3.6, which means it could also be done like this in that version or later:
print(f'n1: {n1:.2f}') # -> n1: 3.40+2.30j
print(f'n2: {n2:.3f}') # -> n2: 3.400-2.300j
In Python 3.8.0, support for an = specifier was added to f-strings, allowing you to write:
print(f'{n1=:.2f}') # -> n1=3.40+2.30j
print(f'{n2=:.3f}') # -> n2=3.400-2.300j
Neither String Formatting Operations - i.e. the modulo (%) operator) -
nor the newer str.format() Format String Syntax support complex types.
However it is possible to call the __format__ method of all built in numeric types directly.
Here is an example:
>>> i = -3 # int
>>> l = -33L # long (only Python 2.X)
>>> f = -10./3 # float
>>> c = - 1./9 - 2.j/9 # complex
>>> [ x.__format__('.3f') for x in (i, l, f, c)]
['-3.000', '-33.000', '-3.333', '-0.111-0.222j']
Note, that this works well with negative imaginary parts too.
For questions like this, the Python documentation should be your first stop. Specifically, have a look at the section on string formatting. It lists all the string format codes; there isn't one for complex numbers.
What you can do is format the real and imaginary parts of the number separately, using x.real and x.imag, and print it out in a + bi form.
>>> n = 3.4 + 2.3j
>>> print '%05f %05fi' % (n.real, n.imag)
3.400000 2.300000i
As of Python 2.6 you can define how objects of your own classes respond to format strings. So, you can define a subclass of complex that can be formatted. Here's an example:
>>> class Complex_formatted(complex):
... def __format__(self, fmt):
... cfmt = "({:" + fmt + "}{:+" + fmt + "}j)"
... return cfmt.format(self.real, self.imag)
...
>>> z1 = Complex_formatted(.123456789 + 123.456789j)
>>> z2 = Complex_formatted(.123456789 - 123.456789j)
>>> "My complex numbers are {:0.5f} and {:0.5f}.".format(z1, z2)
'My complex numbers are (0.12346+123.45679j) and (0.12346-123.45679j).'
>>> "My complex numbers are {:0.6f} and {:0.6f}.".format(z1, z2)
'My complex numbers are (0.123457+123.456789j) and (0.123457-123.456789j).'
Objects of this class behave exactly like complex numbers except they take more space and operate more slowly; reader beware.
Check this out:
np.set_printoptions(precision=2) # Rounds up to 2 decimals all float expressions
I've successfully printed my complexfloat's expressions:
# Show poles and zeros
print( "zeros = ", zeros_H , "\n")
print( "poles = ", poles_H )
out before:
zeros = [-0.8 +0.6j -0.8 -0.6j -0.66666667+0.j ]
poles = [-0.81542318+0.60991027j -0.81542318-0.60991027j -0.8358203 +0.j ]
out after:
zeros = [-0.8 +0.6j -0.8 -0.6j -0.67+0.j ]
poles = [-0.82+0.61j -0.82-0.61j -0.84+0.j ]