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To insert a row into a Pandas DataFrame, use the .loc method and pass the row data as a dictionary with the key values set as the column names. For example, df.loc[‘new_row’] = {‘column1’: ‘value1’, ‘column2’: ‘value2’}. This will add the new row to the DataFrame object. You can also use the .append() method to add the row to the end of the DataFrame.
You can use the following basic syntax to insert a row into a a specific location in a pandas DataFrame:
import pandas as pd import numpy as np #insert row with values [1, 7, 6] into existing DataFrame at index=4 pd.DataFrame(np.insert(df.values, 4, values=[1, 7, 6], axis=0))
The following example shows how to use this syntax in practice with the following pandas DataFrame:
import pandas as pd #create DataFrame df = pd.DataFrame({'team': ['A', 'A', 'B', 'B', 'C'], 'assists': [5, 7, 7, 9, 12], 'rebounds': [11, 8, 10, 6, 6]}) #view DataFrame df team assists rebounds 0 A 5 11 1 A 7 8 2 B 7 10 3 B 9 6 4 C 12 6
Example 1: Insert Values Into First Row of Pandas DataFrame
We can use the following syntax to insert a row of values into the first row of a pandas DataFrame:
#insert values into first row of DataFrame
df2 = pd.DataFrame(np.insert(df.values, 0, values=['A', 3, 4], axis=0))
#define column names of DataFrame
df2.columns = df.columns
#view updated DataFrame
df2
team assists rebounds
0 A 3 4
1 A 5 11
2 A 7 8
3 B 7 10
4 B 9 6
5 C 12 6
Example 2: Insert Values Into Specific Row of Pandas DataFrame
We can use the following syntax to insert a row of values into a specific row of a pandas DataFrame:
#insert values into third row (index position=2) of DataFrame
df2 = pd.DataFrame(np.insert(df.values, 2, values=['A', 3, 4], axis=0))
#define column names of DataFrame
df2.columns = df.columns
#view updated DataFrame
df2
team assists rebounds
0 A 5 11
1 A 7 8
2 A 3 4
3 B 7 10
4 B 9 6
5 C 12 6
Example 3: Insert Values Into Last Row of Pandas DataFrame
We can use the following syntax to insert a row of values into the last row of a pandas DataFrame:
#insert values into last row of DataFrame
df2 = pd.DataFrame(np.insert(df.values, len(df.index), values=['A', 3, 4], axis=0))
#define column names of DataFrame
df2.columns = df.columns
#view updated DataFrame
df2
team assists rebounds
0 A 5 11
1 A 7 8
2 B 7 10
3 B 9 6
4 C 12 6
5 A 3 4
Note: You can find the complete documentation for the NumPy insert() function .