I got this:
columns = ['a','b','c']
data = [1,2,3],[3,4],[4,5,5]
df = pandas.DataFrame({i:pandas.Series(j) for i in columns for j in data})
print(df)
Output:
a b c
0 4 4 4
1 5 5 5
2 5 5 5
I need:
a b c
0 1 3 4
1 2 4 5
2 3 5
I really don't understand why this is not working. I know I'm accessing the elements in data in the right way.
Any tips?
This should do it:
import pandas as pd
data = [[1, 2, 3], [3, 4], [4, 5, 5]]
df = pd.DataFrame(data).transpose()
df.columns = columns
Output:
a b c
0 1.0 3.0 4.0
1 2.0 4.0 5.0
2 3.0 NaN 5.0
You are overwriting values when you enter the second loop. What you are doing is:
import pandas
columns = ['a','b','c']
data = [1,2,3],[3,4],[4,5,5]
myDict = {}
for i in columns:
for j in data:
myDict[i]=j
print(pandas.DataFrame(myDict))
That's why your data is overwritten. What you want to do is clearly:
myDict = {}
for i,key in enumerate(columns):
myDict[key] = data[i]
However, this will cause:
raise ValueError('arrays must all be same length')
ValueError: arrays must all be same length
Which has a well-described solution here
