Create column from another dataframe with condition-CodePudding

I want to assign the labels in the df1 to df2 depending of df1['MinNum'] and df1['MaxMum']

df1
    Label                       MinNum  MaxNum
0   Rivière                     0       0
1   Sols minéraux bruts         1       2
2   Sols peu évolués lithiques  3       4

df2
    SOIL_ID 
0   0.0 
1   1.0
2   2.0 
4   4.0

The condition is:

if df1['MinNum'] <= df2['SOIL_ID'] <= df1['MaxNum'] assign df1['Label'] to new label column for df2

I want to have this

    SOIL_ID  label
0   0.0      Rivière                      
1   1.0      Sols minéraux bruts
2   2.0      Sols minéraux bruts
4   4.0      Sols peu évolués lithiques

CodePudding user response：

Probably not the most efficient way but I would create an intermediate DataFrame because df1 is not very easy to use.

df3 = pd.DataFrame(columns=["Sol_ID", "label"])
for i, row in df1.iterrows():
    for j in range(row["MinNum"], row["MaxNum"] 1):
        df3 = df3.append({"Sol_ID": j, "label": row["label"]}, ignore_index=True)

Which gives you a proper indexing:

    Sol_ID  label
0   0   Rivière
1   1   Sols minéraux purs
2   2   Sols minéraux purs
3   3   Sols peu évolués lithiques
4   4   Sols peu évolués lithiques

Then you can merge the 2 DataFrames:

df2.merge(df3, on="Sol_ID")

OUTPUT:

  Sol_ID  label
0   0   Rivière
1   1   Sols minéraux purs
2   2   Sols minéraux purs
3   4   Sols peu évolués lithiques