I would like to merge the data frames "members_regression" with "members" in order to have the column "age" in "members_regression". However, since I changed the dtype of "expedition_id" in "members_regression" I don't really understand how to do it as the "expedition_id" columns are not really the same in both dataframes. Can you help me?
import pandas as pd
members = pd.read_csv("https://raw.githubusercontent.com/rfordatascience/tidytuesday/master/data/2020/2020-09-22/members.csv")
expeditions = pd.read_csv("https://raw.githubusercontent.com/rfordatascience/tidytuesday/master/data/2020/2020-09-22/expeditions.csv", parse_dates=['basecamp_date','highpoint_date','termination_date'])
peaks = pd.read_csv("https://raw.githubusercontent.com/rfordatascience/tidytuesday/master/data/2020/2020-09-22/peaks.csv")
members_sk = members
members_sk2 = pd.merge(members_sk, expeditions[["expedition_id", "nbre_total_membres"]], on = "expedition_id", how="inner")
members_sk3 = pd.merge(members_sk2, peaks[["peak_id", "height_metres"]], on = "peak_id", how="inner")
from sklearn.preprocessing import OneHotEncoder
members_sk3 = members_sk3.select_dtypes(include=[object])
members_sk3
from sklearn import preprocessing
le = preprocessing.LabelEncoder()
members_regression = members_sk3.apply(le.fit_transform)
members_regression.head()
members_regression2 = pd.merge ??