Transpose then Join

[cfrederes1]

Hi,

I'm attempting to make a 'flat' row by the field "TN" below- I can us the crosstab function and receive the output of the highlighted fields but I can't join to bring the correlated MRC and Qty field for every USOC.

INPUT:

DESIRED OUTPUT:

[kristy236lewis]

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@cfrederes1 wrote:

Hi,

I'm attempting to make a 'flat' row by the field "TN" below- I can us the crosstab function and receive the output of the highlighted fields but I can't join to bring the correlated MRC and Qty field for every USOC.

INPUT:

DESIRED OUTPUT:

---

import pandas as pd

# Create a DataFrame
data = {'A': [1, 2], 'B': [3, 4]}
df = pd.DataFrame(data)

# Transpose the DataFrame
transposed_df = df.T

# Create another DataFrame to join
data2 = {'Key': ['A', 'B'], 'Value': ['X', 'Y']}
df2 = pd.DataFrame(data2)

# Join on the index of the transposed DataFrame
result = transposed_df.join(df2.set_index('Key'))

print(result)

[Qiu]

@cfrederes1 
It can be completed with the combination of Transpose and Cross Tab and not that The duplicated fields names are not allowed.