How do I take multiple lists and put them as different columns in a python dataframe? I tried this solution but had some trouble.
Attempt 1:
res = zip(lst1,lst2,lst3)
Attempt 2:
percentile_list = pd.DataFrame({'lst1Tite' : [lst1],
'lst2Tite' : [lst2],
'lst3Tite' : [lst3] },
columns=['lst1Tite','lst1Tite', 'lst1Tite'])
How do I get a 100 row (length of each independent list) by 3 column (three lists) pandas dataframe?
Adding to above answers, we can create on the fly
df= pd.DataFrame()
list1 = list(range(10))
list2 = list(range(10,20))
df['list1'] = list1
df['list2'] = list2
print(df)
hope it helps !
you can simple use this following code
train_data['labels']= train_data[["LABEL1","LABEL1","LABEL2","LABEL3","LABEL4","LABEL5","LABEL6","LABEL7"]].values.tolist()
train_df = pd.DataFrame(train_data, columns=['text','labels'])
@oopsi used pd.concat()
but didn't include the column names. You could do the following, which, unlike the first solution in the accepted answer, gives you control over the column order (avoids dicts, which are unordered):
import pandas as pd
lst1 = range(100)
lst2 = range(100)
lst3 = range(100)
s1=pd.Series(lst1,name='lst1Title')
s2=pd.Series(lst2,name='lst2Title')
s3=pd.Series(lst3 ,name='lst3Title')
percentile_list = pd.concat([s1,s2,s3], axis=1)
percentile_list
Out[2]:
lst1Title lst2Title lst3Title
0 0 0 0
1 1 1 1
2 2 2 2
3 3 3 3
4 4 4 4
5 5 5 5
6 6 6 6
7 7 7 7
8 8 8 8
...
Adding one more scalable solution.
lists = [lst1, lst2, lst3, lst4]
df = pd.concat([pd.Series(x) for x in lists], axis=1)
Just adding that using the first approach it can be done as -
pd.DataFrame(list(map(list, zip(lst1,lst2,lst3))))
Adding to Aditya Guru's answer here. There is no need of using map. You can do it simply by:
pd.DataFrame(list(zip(lst1, lst2, lst3)))
This will set the column's names as 0,1,2. To set your own column names, you can pass the keyword argument columns
to the method above.
pd.DataFrame(list(zip(lst1, lst2, lst3)),
columns=['lst1_title','lst2_title', 'lst3_title'])
There are several ways to create a dataframe from multiple lists.
list1=[1,2,3,4]
list2=[5,6,7,8]
list3=[9,10,11,12]
pd.DataFrame({'list1':list1, 'list2':list2, 'list3'=list3})
pd.DataFrame(data=zip(list1,list2,list3),columns=['list1','list2','list3'])
Source: Stackoverflow.com