I am trying to create a pandas
series.
One column of the series should contain n sequential numbers. [1, 2, 3, ..., n]
One colu
import pandas
n = 30
k = 40
pandas.DataFrame([(i, random.randint(k, k+100), chr(random.randint(ord('A'), ord('Z')))) for i in xrange(0, n)
If you want you specify the column names otherwise it is set to 0,1,2
There can be a lot of solutions. In the comments of the code block (#
) you will find a few links for more information:
import pandas as pd
import numpy as np
import random
import string
k = 5
N = 10
#http://docs.scipy.org/doc/numpy/reference/generated/numpy.random.randint.html
#http://stackoverflow.com/a/2257449/2901002
df = pd.DataFrame({ 'A' : range(1, N + 1 ,1),
'B' : np.random.randint(k, k + 100 , size=N),
'C' : pd.Series(random.choice(string.ascii_uppercase) for _ in range(N)) })
print df
# A B C
#0 1 60 O
#1 2 94 L
#2 3 10 W
#3 4 94 X
#4 5 60 O
#5 6 20 K
#6 7 58 Y
#7 8 40 I
#8 9 49 X
#9 10 65 S
Numpy solution:
import pandas as pd
import numpy as np
k = 5
N = 10
alphabet = list('ABCDEFGHIJKLMNOPQRSTUVWXYZ')
#http://docs.scipy.org/doc/numpy/reference/generated/numpy.random.choice.html
df = pd.DataFrame({ 'A' : range(1, N + 1 ,1),
'B' : np.random.randint(k, k + 100 , size=N),
'C' : np.random.choice(np.array(alphabet, dtype="|S1"), N) })
print df
# A B C
#0 1 16 U
#1 2 76 X
#2 3 101 N
#3 4 61 F
#4 5 52 J
#5 6 62 A
#6 7 99 L
#7 8 23 N
#8 9 75 D
#9 10 16 Q