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df["station"] = df["End station"].combine_first(df["Start station"])
df.drop(["End station", "Start station"], 1, inplace=True)
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# Basic syntax:
# If both columns are already string typed:
your_df["combined_col"] = your_df["column_1"] + your_df["column_2"]
# If one (or both) of the columns are not string typed:
your_df["combined_col"] = your_df["column_1"].astype(str) + your_df["column_2"]
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#suppose you have two dataframes df1 and df2, and
#you need to merge them along the column id
df_merge_col = pd.merge(df1, df2, on='id')
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import pandas as pd
T1 = pd.merge(T1, T2, on=T1.index, how='outer')
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cols = ['foo', 'bar', 'new']
df['combined'] = df[cols].apply(lambda row: '_'.join(row.values.astype(str)), axis=1)
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# First dataframe with three columns
dlist=["vx","vy","vz"]
df=pd.DataFrame(columns=dlist)
df["vx"]=df1["v2x"]
df["vy"]=df1["v2y"]
df["vz"]=df1["v2z"]
# second dataframe with three columns
dlist=["vx","vy","vz"]
df0=pd.DataFrame(columns=dlist)
df0["vx"]=df2["v1x"]
df0["vy"]=df2["v1y"]
df0["vz"]=df2["v1z"]
# Here with concat we can create new dataframe with garther both in one
# YOU CAN PUT SOME VALUES IN EACH AND CHECK IT
# WHAT INSIDE THE CONCAT MUST BE A LIST OF DATAFRAME
v = pd.concat([df,df0])