I have two Dataframes ( 'x' and 'y'), that define a grid (or coordinates) and a third Dataframe with the respective values ('z'). They are a result of an 2D interpolation.
import pandas as pd
df_x = pd.DataFrame(["a", "b", "c"])
df_y = pd.DataFrame(["alpha", "beta", "gamma"])
df_z = pd.DataFrame([1, 2, 3, 4, 5, 6,...9])
To continue, I would like to merge all the data in one Dataframe with the following (more like a database-like) structure:
df_new = pd.DataFrame({'x': ["a", "a", "a", "b", "b", "b", "c", "c", "c"], 'y': ["alpha", "beta", "gamma", "alpha", "beta", "gamma", "alpha", "beta", "gamma"], 'z': [1,2,3,4,5,6,7,8,9]})
| x | y | z |
|---|---|---|
| a | alpha | 1 |
| a | beta | 2 |
| a | gamma | 3 |
| b | alpha | 4 |
| b | beta | 5 |
| b | gamma | 6 |
| c | alpha | 7 |
| c | beta | 8 |
| c | gamma | 9 |
There must be an easy way to rearrange the Dataframes, right? And what would be a good tag for this kind of question (without, searching is not very rewarding)?
Thank you very much :)
Ps.: I found some answers for R, but none for Python, yet.
CodePudding user response：
Check with merge
out = df_x.merge(df_y,how='cross').join(df_z)