Pandas Data Series: Convert the first column of a DataFrame as a Series
Write a Pandas program to convert the first column of a DataFrame as a Series.
Sample Solution :
Python Code :
import pandas as pd
d = {'col1': [1, 2, 3, 4, 7, 11], 'col2': [4, 5, 6, 9, 5, 0], 'col3': [7, 5, 8, 12, 1, 11]}
df = pd.DataFrame(data=d)
print("Original DataFrame")
print(df)
# Using iloc
s1 = df.iloc[:, 0]
# Alternatively, you can directly reference the column by name
#s1 = df['col1']
print("\n1st column as a Series:")
print(s1)
print(type(s1))
Sample Output:
Original DataFrame col1 col2 col3 0 1 4 7 1 2 5 5 2 3 6 8 3 4 9 12 4 7 5 1 5 11 0 11 1st column as a Series: 0 1 1 2 2 3 3 4 4 7 5 11 Name: col1, dtype: int64 <class 'pandas.core.series.Series'>
Explanation:
Here is the breakdown of the above exercise:
- Import Pandas Library:
import pandas as pd
This line imports the Pandas library and assigns it the alias "pd" for easier reference. - Create a DataFrame:
d = {'col1': [1, 2, 3, 4, 7, 11], 'col2': [4, 5, 6, 9, 5, 0], 'col3': [7, 5, 8, 12, 1, 11]} df = pd.DataFrame(data=d)
This code creates a DataFrame (df) using a dictionary (d). Each key-value pair in the dictionary represents a column in the DataFrame. - Print Original DataFrame:
print("Original DataFrame") print(df)
This prints the original DataFrame (df) to the console. - Extract the First Column as a Series:
s1 = df.iloc[:, 0] or alternatively: # s1 = df['col1']
This line extracts the first column from the DataFrame as a Series (s1). The iloc[:, 0] indexer is used to select all rows (:) from the first column (0). Alternatively, you can directly reference the column by name (df['col1']). - Print the Result:
print("\n1st column as a Series:") print(s1)
This prints the extracted Series (s1) to the console. - Print the Type of the Series:
print(type(s1))
This prints the type of the Series (s1). The result will show that s1 is a Pandas Series.
Python-Pandas Code Editor:
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