In [1]:
import numpy as np
In [2]:
a = np.genfromtxt('data/src/sample_nan.csv', delimiter=',')
print(a)
In [3]:
a_nan = np.array([0, 1, np.nan, float('nan')])
print(a_nan)
In [4]:
print(np.nan == np.nan)
In [5]:
print(np.isnan(np.nan))
In [6]:
print(a_nan == np.nan)
In [7]:
print(np.isnan(a_nan))
In [8]:
a_fill = np.genfromtxt('data/src/sample_nan.csv', delimiter=',', filling_values=0)
print(a_fill)
In [9]:
a = np.genfromtxt('data/src/sample_nan.csv', delimiter=',')
print(np.nan_to_num(a))
In [10]:
print(a)
In [11]:
print(np.nan_to_num(a, copy=False))
In [12]:
print(a)
In [13]:
a = np.genfromtxt('data/src/sample_nan.csv', delimiter=',')
print(np.nan_to_num(a, nan=-1))
In [14]:
print(np.nanmean(a))
In [15]:
print(np.nan_to_num(a, nan=np.nanmean(a)))
In [16]:
a = np.genfromtxt('data/src/sample_nan.csv', delimiter=',')
print(np.isnan(a))
In [17]:
a[np.isnan(a)] = 0
print(a)
In [18]:
a = np.genfromtxt('data/src/sample_nan.csv', delimiter=',')
a[np.isnan(a)] = np.nanmean(a)
print(a)