pandas look for values in column with condition
# The common syntax is df.loc[], the condition is put in the bracket
#Eg, look for rows with column1 > 5 and column2 = 3
df.loc[(df['column_1'] > 5) & (df['column_2'] = 3)]
pandas look for values in column with condition
# The common syntax is df.loc[], the condition is put in the bracket
#Eg, look for rows with column1 > 5 and column2 = 3
df.loc[(df['column_1'] > 5) & (df['column_2'] = 3)]
pandas check if any of the values in one column exist in another
df["exists"] = df.drop("target", 1).isin(df["target"]).any(1)
print(df)
target A B C exists
0 cat bridge cat brush True
1 brush dog cat shoe False
2 bridge cat shoe bridge True
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