How to Select rows in Pandas DataFrame Based on ConditionsIn this tutorial, we will learn how a user can select rows in Pandas DataFrame based on conditions using Python. Users can select rows based on a particular column value using '>', '=', '<=', '>=', '!=' operators. Conditions:We will discuss different conditions that can be applied to the Pandas DataFrame. Condition 1:Select all the rows from the DataFrame in which 'Percentage' is greater than 70 using the basic method. Code: Output: Given DataFrame: Name_1 Age_1 Subjects_1 Percentage_1 0 Anuj 23 DBMS 88 1 Ashu 24 ADS 62 2 Yashi 21 ASPM 85 3 Mark 19 BCM 71 4 Joshua 21 MFCS 55 5 John 24 ADS 78 6 Ray 25 ASPM 70 7 Lilly 22 TOC 66 8 Rose 23 Data Mining 71 9 Rachel 22 OOPS 89 Following is the Result DataFrame: Name_1 Age_1 Subjects_1 Percentage_1 0 Anuj 23 DBMS 88 2 Yashi 21 ASPM 85 3 Mark 19 BCM 71 5 John 24 ADS 78 8 Rose 23 Data Mining 71 9 Rachel 22 OOPS 89 Condition 2:Select all the rows from the DataFrame in which 'Percentage' is greater than 70 by using the "loc[]" method. Code: Output: Given DataFrame: Name_1 Age_1 Subjects_1 Percentage_1 0 Anuj 23 DBMS 88 1 Ashu 24 ADS 62 2 Yashi 21 ASPM 85 3 Mark 19 BCM 71 4 Joshua 21 MFCS 55 5 John 24 ADS 78 6 Ray 25 ASPM 70 7 Lilly 22 TOC 66 8 Rose 23 Data Mining 71 9 Rachel 22 OOPS 89 Following is the Result DataFrame: Name_1 Age_1 Subjects_1 Percentage_1 0 Anuj 23 DBMS 88 2 Yashi 21 ASPM 85 3 Mark 19 BCM 71 5 John 24 ADS 78 8 Rose 23 Data Mining 71 9 Rachel 22 OOPS 89 Condition 3:Select all the rows from the DataFrame in which 'Percentage' is not equal to 71 using the "loc[]" method. Code: Output: Given DataFrame: Name_1 Age_1 Subjects_1 Percentage_1 0 Anuj 23 DBMS 88 1 Ashu 24 ADS 62 2 Yashi 21 ASPM 85 3 Mark 19 BCM 71 4 Joshua 21 MFCS 55 5 John 24 ADS 78 6 Ray 25 ASPM 70 7 Lilly 22 TOC 66 8 Rose 23 Data Mining 71 9 Rachel 22 OOPS 89 Following is the Result DataFrame: Name_1 Age_1 Subjects_1 Percentage_1 0 Anuj 23 DBMS 88 1 Ashu 24 ADS 62 2 Yashi 21 ASPM 85 4 Joshua 21 MFCS 55 5 John 24 ADS 78 6 Ray 25 ASPM 70 7 Lilly 22 TOC 66 9 Rachel 22 OOPS 89 Now, we will learn how to select those rows whose column value is present in the list by using the "isin()" function of the DataFrame. Condition 4:Select all the rows from the given DataFrame in which column value of "Subjects_1" is present in the "Subjects_2" list by using the basic method. Code: Output: Given DataFrame: Name_1 Age_1 Subjects_1 Percentage_1 0 Anuj 23 DBMS 88 1 Ashu 24 ADS 62 2 Yashi 21 ASPM 85 3 Mark 19 BCM 71 4 Joshua 21 MFCS 55 5 John 24 ADS 78 6 Ray 25 ASPM 70 7 Lilly 22 TOC 66 8 Rose 23 Data Mining 71 9 Rachel 22 OOPS 89 Following is the Result DataFrame: Name_1 Age_1 Subjects_1 Percentage_1 1 Ashu 24 ADS 62 2 Yashi 21 ASPM 85 5 John 24 ADS 78 6 Ray 25 ASPM 70 7 Lilly 22 TOC 66 Condition 5:Select all the rows from the given DataFrame in which column value of "Subjects_1" is present in the "Subjects_2" list by using the "loc[]" method. Code: Output: Given DataFrame: Name_1 Age_1 Subjects_1 Percentage_1 0 Anuj 23 DBMS 88 1 Ashu 24 ADS 62 2 Yashi 21 ASPM 85 3 Mark 19 BCM 71 4 Joshua 21 MFCS 55 5 John 24 ADS 78 6 Ray 25 ASPM 70 7 Lilly 22 TOC 66 8 Rose 23 Data Mining 71 9 Rachel 22 OOPS 89 Following is the Result DataFrame: Name_1 Age_1 Subjects_1 Percentage_1 1 Ashu 24 ADS 62 2 Yashi 21 ASPM 85 5 John 24 ADS 78 6 Ray 25 ASPM 70 7 Lilly 22 TOC 66 Condition 6:Select all the rows from the given DataFrame in which column value of "Subjects_1" is not present in the "Subjects_2" list by using the "loc[]" method. Code: Output: Given DataFrame: Name_1 Age_1 Subjects_1 Percentage_1 0 Anuj 23 DBMS 88 1 Ashu 24 ADS 62 2 Yashi 21 ASPM 85 3 Mark 19 BCM 71 4 Joshua 21 MFCS 55 5 John 24 ADS 78 6 Ray 25 ASPM 70 7 Lilly 22 TOC 66 8 Rose 23 Data Mining 71 9 Rachel 22 OOPS 89 Following is the Result DataFrame: Name_1 Age_1 Subjects_1 Percentage_1 0 Anuj 23 DBMS 88 3 Mark 19 BCM 71 4 Joshua 21 MFCS 55 8 Rose 23 Data Mining 71 9 Rachel 22 OOPS 89 Now, we will learn how to select rows based on multiple column conditions by using the "&" operator. Condition 7:Select all the rows from the given DataFrame in which "Percentage_1" is equal to "71" and "Subject_1" is present in the "Subject_2" list by using the basic method. Code: Output: Given DataFrame: Name_1 Age_1 Subjects_1 Percentage_1 0 Anuj 23 DBMS 88 1 Ashu 21 ADS 71 2 Yashi 21 ASPM 71 3 Mark 19 BCM 82 4 Joshua 21 MFCS 55 5 John 24 ADS 78 6 Ray 25 ASPM 70 7 Lilly 22 TOC 66 8 Rose 23 Data Mining 71 9 Rachel 22 OOPS 89 Following is the Result DataFrame: Name_1 Age_1 Subjects_1 Percentage_1 1 Ashu 21 ADS 71 2 Yashi 21 ASPM 71 Condition 8:Select all the rows from the given DataFrame in which "Percentage_1" is equal to "71" and "Subject_1" is present in the "Subject_2" list by using the "loc[]" method. Code: Output: Given DataFrame: Name_1 Age_1 Subjects_1 Percentage_1 0 Anuj 23 DBMS 88 1 Ashu 21 ADS 71 2 Yashi 21 ASPM 71 3 Mark 19 BCM 82 4 Joshua 21 MFCS 55 5 John 24 ADS 78 6 Ray 25 ASPM 70 7 Lilly 22 TOC 66 8 Rose 23 Data Mining 71 9 Rachel 22 OOPS 89 Following is the Result DataFrame: Name_1 Age_1 Subjects_1 Percentage_1 1 Ashu 21 ADS 71 2 Yashi 21 ASPM 71 ConclusionIn this tutorial, we have discussed how to select different rows of Pandas DataFrame based on various conditions. Next TopicTypecasting in Python |
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