I have two lists, such as:
list_columns = ['a','b','c','d','e','f','g','h','k','l','m','n']
and a list of values
list_values = [11,22,33,44,55,66,77,88,99,100, 111, 222]
I want to create a Pandas dataframe using list_columns as columns.
I tried with df = pd.DataFrame(list_values, columns=list_columns)
but it doesn't work
I get this error: ValueError: Shape of passed values is (1, 12), indices imply (12, 12)
A dataframe is a two-dimensional object. To reflect this, you need to feed a nested list. Each sublist, in this case the only sublist, represents a row.
df = pd.DataFrame([list_values], columns=list_columns)
print(df)
# a b c d e f g h k l m n
# 0 11 22 33 44 55 66 77 88 99 100 111 222
If you supply an index with length greater than 1, Pandas broadcasts for you:
df = pd.DataFrame([list_values], columns=list_columns, index=[0, 1, 2])
print(df)
# a b c d e f g h k l m n
# 0 11 22 33 44 55 66 77 88 99 100 111 222
# 1 11 22 33 44 55 66 77 88 99 100 111 222
# 2 11 22 33 44 55 66 77 88 99 100 111 222
If I understand your question correctly just wrap list_values in brackets so it's a list of lists
list_columns = ['a','b','c','d','e','f','g','h','k','l','m','n']
list_values = [[11,22,33,44,55,66,77,88,99,100, 111, 222]]
pd.DataFrame(list_values, columns=list_columns)
a b c d e f g h k l m n
0 11 22 33 44 55 66 77 88 99 100 111 222
from your list you can do like below:
df = pd.DataFrame(list_values)
df=df.T
df.columns=list_columns
>>df
a b c d e f g h k l m n
0 11 22 33 44 55 66 77 88 99 100 111 222
