Converting list to array with NumPy asarray method

Question

I try get mean from csv line. I get data from csv in string list, further i convert it to array with numpy. Its work perfect when i try plot some graphics. But when i calculate mean i get some errors with my data.

If i use NumPy i get:

TypeError: cannot perform reduce with flexible type

If i use statistics library i get:

TypeError: can't convert type 'string' to numerator/denominator

If i check my array with comand 'type' on iPython i see that it numpy.ndarray type.

Whats wrong with my array? Can you explain, why convert numpy.asarray for matplotlib work perfect, but get wrong type for different operation.

import csv
import numpy as np
import statistics as stat
life_exp=[]
with open('country.csv') as csvfile:
   datareader = csv.reader(csvfile)
   for row in datareader:
    if datareader.line_num!=1:
        life_exp.append(row[1])
array_life_exp = np.asarray(life_exp) 
print(stat.mean(array_life_exp))
print(np.mean(array_life_exp))

@VladMironov Its simple example from OpenIntro Statistics book. Afghanistan,49.72,121.63,4 Albania,77.59,14.12,45. I take a second number of each row. (49.72 from first line, and 77.59 from second etc.) — Denis Savenko
– Denis Savenko, Commented Jun 18, 2015 at 8:42

user4999547 · Accepted Answer · 2015-06-18 08:46:31Z

1

Try this:

from pandas import read_csv

data = read_csv('country.csv')
print(data.iloc[:,1].mean())

This code will convert your csv to pandas dataframe with automatic type conversion and print mean of the second column.

answered Jun 18, 2015 at 8:46

user4999547

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7 Comments

Denis Savenko Over a year ago

It work for me like magic. But whats wrong with NumPy? It needs me for plotting charts. Do you not, why don't work .asarray converting for me?

user4999547 Over a year ago

data.iloc[:,1] is np.array :)

user4999547 Over a year ago

Because numpy convert all your elements to str: In [144]: np.asarray(['1',23,'4.']) Out[144]: array(['1', '23', '4.'], dtype='<U2')

Denis Savenko Over a year ago

Thank you.I promise to read the documentation on this method:)

user4999547 Over a year ago

You're welcome! Check dtype value in np.asarray

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