从 int 到 float 的 Numpy 数组

Question

I have this code to extract some data from a csv. I can extract the data with no problem but I would like to change the numpy array from a int to a float. I know that the argument to do that is dtype=np.float32 but I keep having an error message when I do include this argument: This is the code:

import numpy as np
import pandas as pd
rainfall=pd.read_csv('Seattle2014.csv')['PRCP'].values
inches=rainfall / 254
inches.shape

#...

rainy=(inches >0)
summer=(np.arange(365)-172<90) &(np.arange(365)-172>0)
print ("Mediam precipitation on rainy days in 2014  (inches):       ",np.median(inches[rainy]))
print ("Mediam precipitation on summer days in 2014 (inches):       ",np.median(inches[summer]))
print ("Maximum precipitation on summer days in 2014 (inches):      ",np.max(inches[summer]))
print ("Median precipitation on non-summer days in 2014 (inches):  ",np.median(inches[rainy & ~summer]))

This is the code with the argument:

rainy=(inches >0)
summer=(np.arange(365)-172<90) &(np.arange(365)-172>0)
print ("Mediam precipitation on rainy days in 2014  (inches):       ",np.median(inches[rainy], dtype=float))

And I do get this error message:

TypeErrorTraceback (most recent call last) <ipython-input-136-29b7a435cc0e> in <module>()
      1 rainy=(inches >0)
      2 summer=(np.arange(365)-172<90) &(np.arange(365)-172>0)
----> 3 print ("Mediam precipitation on rainy days in 2014  (inches):       ",np.median(inches[rainy], dtype=float))
      4 print ("Mediam precipitation on summer days in 2014 (inches):       ",np.median(inches[summer]))
      5 print ("Maximum precipitation on summer days in 2014 (inches):      ",np.max(inches[summer]))

TypeError: median() got an unexpected keyword argument 'dtype'

How can I solve this problem?

Answer 1

numpy.median() has no argument dtype . This is its output behaviour:

RETURNS: median : ndarray

A new array holding the result (unless out is specified, in which case that array is returned instead). If the input contains integers, or floats of smaller precision than 64, then the output data-type is float64. Otherwise, the output data-type is the same as that of the input.