pandas change multiple column types
#Two ways to do this
df[['parks', 'playgrounds', 'sports']].apply(lambda x: x.astype('category'))
cols = ['parks', 'playgrounds', 'sports', 'roading']:
public[cols] = public[cols].astype('category')pandas change multiple column types
#Two ways to do this
df[['parks', 'playgrounds', 'sports']].apply(lambda x: x.astype('category'))
cols = ['parks', 'playgrounds', 'sports', 'roading']:
public[cols] = public[cols].astype('category')pandas change multiple column types
#Method 1:
df["Delivery Charges"] = df[["Weight", "Package Size", "Delivery Mode"]].apply(
lambda x : calculate_rate(*x), axis=1)
#Method 2:
df["Delivery Charges"] = df.apply(
lambda x : calculate_rate(x["Weight"],
x["Package Size"], x["Delivery Mode"]), axis=1)assign multiple columns pandas
import pandas as pd
df = {'col_1': [0, 1, 2, 3],
'col_2': [4, 5, 6, 7]}
df = pd.DataFrame(df)
df[[ 'column_new_1', 'column_new_2','column_new_3']] = [np.nan, 'dogs',3] #thought this woCopyright © 2021 Codeinu
Forgot your account's password or having trouble logging into your Account? Don't worry, we'll help you to get back your account. Enter your email address and we'll send you a recovery link to reset your password. If you are experiencing problems resetting your password contact us
