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import pandas as pd
# create a dictionary
students = {
"name": ["Tom", "John", "Rick", "Sneha", "Johnson"],
"score": [90, 80, 98, 99, 82],
"subjects": ["Math", "Physics", "Chemistry", "english", "Data Structure"]
}
# create the dataframe from dictionary
df = pd.DataFrame(students, index=['a', 'b', 'c', 'd', 'e'])
print(df)
#change rows orders using index list
df = df.reindex(['d', 'a', 'e', 'b', 'c'])
print(df)Output
+----+---------+---------+----------------+
| | name | score | subjects |
|----+---------+---------+----------------|
| a | Tom | 90 | Math |
| b | John | 80 | Physics |
| c | Rick | 98 | Chemistry |
| d | Sneha | 99 | english |
| e | Johnson | 82 | Data Structure |
+----+---------+---------+----------------+
+----+---------+---------+----------------+
| | name | score | subjects |
|----+---------+---------+----------------|
| d | Sneha | 99 | english |
| a | Tom | 90 | Math |
| e | Johnson | 82 | Data Structure |
| b | John | 80 | Physics |
| c | Rick | 98 | Chemistry |
+----+---------+---------+----------------+If you are using the Pandas library in your Python project then you must be using DataFrames to perform specific tasks on large data. You can sort columns and rows by value using the sort() function. But sometimes it is required to change the orders of rows using the DataFrame index. We can arrange them in ascending and descending order easily but if you want to sort them using a Python List that contains the indexes of Dataframe as its items. We use DataFrame.reindex() function to reorder the rows using the index list.
1. Created a dictionary named students that contains multiple key-value pairs. We will be using keys as column names and values as rows of Dataframe. The values in the student's dictionary are in the form of a List.
2. Created a DataFrame from the above dictionary. We are also assigning custom indexes to the DataFrame. We are using the below code syntax to do that.
df = pd.DataFrame(students, index=['a', 'b', 'c', 'd', 'e'])3. Using reindex() function of Pandas Dataframe to change the order of rows.
df.reindex(['d', 'a', 'e', 'b', 'c'])
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