Tutorial by Examples

For instance, two tables are given, T1 id x y 8 42 1.9 9 30 1.9 T2 id signal 8 55 8 56 8 59 9 57 9 58 9 60 The goal is to get the new table T3: id x y s1 s2 s3 8 42 1.9 55 ...

In [1]: df1 = pd.DataFrame({'x': [1, 2, 3], 'y': ['a', 'b', 'c']}) In [2]: df2 = pd.DataFrame({'y': ['b', 'c', 'd'], 'z': [4, 5, 6]}) In [3]: df1 Out[3]: x y 0 1 a 1 2 b 2 3 c In [4]: df2 Out[4]: y z 0 b 4 1 c 5 2 d 6 Inner join: Uses the intersection ...

generate sample data frames: In [57]: df3 = pd.DataFrame({'col1':[211,212,213], 'col2': [221,222,223]}) In [58]: df1 = pd.DataFrame({'col1':[11,12,13], 'col2': [21,22,23]}) In [59]: df2 = pd.DataFrame({'col1':[111,112,113], 'col2': [121,122,123]}) In [60]: df3 = pd.DataFrame({'col1':[211,2...

Merging key names are same pd.merge(df1, df2, on='key') Merging key names are different pd.merge(df1, df2, left_on='l_key', right_on='r_key') Different types of joining pd.merge(df1, df2, on='key', how='left') Merging on multiple keys pd.merge(df1, df2, on=['key1', 'key2']) Treatment...

Consider the dataframes left and right left = pd.DataFrame([['a', 1], ['b', 2]], list('XY'), list('AB')) left A B X a 1 Y b 2 right = pd.DataFrame([['a', 3], ['b', 4]], list('XY'), list('AC')) right A C X a 3 Y b 4 join Think of join as wanting to combine to dat...