How do I drop the right index on a left merge from the results?

Question

In the below example, I can get the merge to run correctly, but how do I not have the second index print as well? Do I have to add a separate line of code:

df_merge = df_merge.drop(columns='cities')  

Can't I choose which columns I want to merge into the left dataset? What if df2 had 30 columns and I only want 10 of them?

import pandas as pd

df1 = pd.DataFrame({
    "city": ['new york','chicago', 'orlando','ottawa'],
    "humidity": [35,69,79,99]
})


df2 = pd.DataFrame({
    "cities": ['new york', 'chicago', 'toronto'],
    "temp": [1, 6, -35]
})

df_merge = df1.merge(df2, left_on='city', right_on='cities', how='left')
print(df_merge)

**output**

   index      city  humidity    cities  temp
0      0  new york        35  new york   1.0
1      1   chicago        69   chicago   6.0
2      2   orlando        79       NaN   NaN
3      3    ottawa        99       NaN   NaN

Answer 1

merge

Change the name of the column first

df1.merge(df2.rename(columns={'cities': 'city'}), 'left')

       city  humidity  temp
0  new york        35   1.0
1   chicago        69   6.0
2   orlando        79   NaN
3    ottawa        99   NaN

---

If you need to explicitly state what you're merging on:

df1.merge(df2.rename(columns={'cities': 'city'}), how='left', on='city')

---

join

set the index of the right side first
'left' is default.

df1.join(df2.set_index('cities'), 'city')

       city  humidity  temp
0  new york        35   1.0
1   chicago        69   6.0
2   orlando        79   NaN
3    ottawa        99   NaN

---

map

Make a dictionary.

df1.assign(temp=df1.city.map(dict(df2.values)))

       city  humidity  temp
0  new york        35   1.0
1   chicago        69   6.0
2   orlando        79   NaN
3    ottawa        99   NaN

---

Less cute, more explicit

df1.assign(temp=df1.city.map(dict(df2.set_index('cities').temp)))