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# (Python Example for Beginners)

Write a Pandas program to join (left join) the two dataframes using keys from left dataframe only.

**Test Data:**

data1: key1 key2 P Q 0 K0 K0 P0 Q0 1 K0 K1 P1 Q1 2 K1 K0 P2 Q2 3 K2 K1 P3 Q3

data2: key1 key2 R S 0 K0 K0 R0 S0 1 K1 K0 R1 S1 2 K1 K0 R2 S2 3 K2 K0 R3 S3

**Sample Solution:**

**Python Code :**

Sample Output:

Original DataFrames: key1 key2 P Q 0 K0 K0 P0 Q0 1 K0 K1 P1 Q1 2 K1 K0 P2 Q2 3 K2 K1 P3 Q3 -------------------- key1 key2 R S 0 K0 K0 R0 S0 1 K1 K0 R1 S1 2 K1 K0 R2 S2 3 K2 K0 R3 S3 Merged Data (keys from data1): key1 key2 P Q R S 0 K0 K0 P0 Q0 R0 S0 1 K0 K1 P1 Q1 NaN NaN 2 K1 K0 P2 Q2 R1 S1 3 K1 K0 P2 Q2 R2 S2 4 K2 K1 P3 Q3 NaN NaN Merged Data (keys from data2): key1 key2 R S P Q 0 K0 K0 R0 S0 P0 Q0 1 K1 K0 R1 S1 P2 Q2 2 K1 K0 R2 S2 P2 Q2 3 K2 K0 R3 S3 NaN NaN

## Pandas Example – Write a Pandas program to join (left join) the two dataframes using keys from left dataframe only

## Two Machine Learning Fields

There are two sides to machine learning:

**Practical Machine Learning:**This is about querying databases, cleaning data, writing scripts to transform data and gluing algorithm and libraries together and writing custom code to squeeze reliable answers from data to satisfy difficult and ill defined questions. It’s the mess of reality.**Theoretical Machine Learning**: This is about math and abstraction and idealized scenarios and limits and beauty and informing what is possible. It is a whole lot neater and cleaner and removed from the mess of reality.

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