Hierarchical Columns in Numpy
Question:
I’m new to Pandas and trying to recreate the following dataframe, such that values in columns A and B contain random numbers 0 through 8. However, I keep getting "ValueError: all arrays must be same length". Can someone please review my code ? Thank you!
DataFrame
df = pd.DataFrame(np.random.randint(0, high=9),index = [[1, 2, 3], ['a', 'b']],
columns = ['A', 'B'])
Answers:
Since there are two layers to the index, you have to create a multi index:
df = pd.DataFrame(
np.random.randint(9, size=(6, 2)),
index=pd.MultiIndex.from_product([[1, 2, 3], ['a', 'b']]),
columns=['A', 'B']
)
output:
A B
1 a 1 0
b 4 3
2 a 7 3
b 1 6
3 a 5 4
b 3 3
I’m new to Pandas and trying to recreate the following dataframe, such that values in columns A and B contain random numbers 0 through 8. However, I keep getting "ValueError: all arrays must be same length". Can someone please review my code ? Thank you!
DataFrame
df = pd.DataFrame(np.random.randint(0, high=9),index = [[1, 2, 3], ['a', 'b']],
columns = ['A', 'B'])
Since there are two layers to the index, you have to create a multi index:
df = pd.DataFrame(
np.random.randint(9, size=(6, 2)),
index=pd.MultiIndex.from_product([[1, 2, 3], ['a', 'b']]),
columns=['A', 'B']
)
output:
A B
1 a 1 0
b 4 3
2 a 7 3
b 1 6
3 a 5 4
b 3 3