list = [a, b, c, d, e, f, g, h]
How to write and loop the above list on a specific column in python dataframe, so that the outcome will be ...
Dataframe:
Column N (For example)
a
b
c
d
e
f
g
h
a
b
c
d
e
f
g
h
...
(many times)
...
a
b
c
d
e
f
g
h
Or, is there any other way to perform the transformation above without the need of using a list? Thank you very much.
The times variable is how many times you want to repeat. Try the following:
import pandas as pd
letters = 'abcdefgh'
times = 4
df = pd.DataFrame({'Column Name': [x for x in letters]*times})
print(df)
or this:
import pandas as pd
from string import ascii_lowercase
times = 4
df = pd.DataFrame({'Column Name': [x for x in ascii_lowercase[:8]]*times})
print(df)
ascii_lowercase returns all the letters of the alphabet.
First dont use list for variable name, because builtin (python code word), and then for repeat use numpy.tile:
import numpy as np
L = ['a', 'b', 'c', 'd', 'e', 'f', 'g', 'h']
N = 2
df = pd.DataFrame({'col': np.tile(L, N)})
print (df)
col
0 a
1 b
2 c
3 d
4 e
5 f
6 g
7 h
8 a
9 b
10 c
11 d
12 e
13 f
14 g
15 h
You can repeat list with list * n where n is the number of times it repeats. Then assign it to 'Column N' of the dataframe, for example:
import pandas as pd
list = ['a', 'b', 'c', 'd', 'e', 'f', 'g', 'h']
df = pd.DataFrame()
df['Column N'] = list * 5
print(df)
np.nan in the dataframe column, use df['Column N'].fillna(0, inplace=True) to replace nan value with 0import pandas as pd
import numpy as np
print(pd.DataFrame(columns=['column name'],data= ['1', np.nan, 'c', 'd', 'e', 'f', 'g', 'h']*5))
listitertools.cycle