Pandas: Combine many given series to create a DataFrame
Write a Pandas program to combine many given series to create a DataFrame.
Sample Solution :
Python Code :
import pandas as pd
sr1 = pd.Series(['php', 'python', 'java', 'c#', 'c++'])
sr2 = pd.Series([1, 2, 3, 4, 5])
print("Original Series:")
print(sr1)
print(sr2)
print("Combine above series to a dataframe:")
ser_df = pd.DataFrame(sr1, sr2).reset_index()
print(ser_df.head())
print("\nUsing pandas concat:")
ser_df = pd.concat([sr1, sr2], axis = 1)
print(ser_df.head())
print("\nUsing pandas DataFrame with a dictionary, gives a specific name to the columns:")
ser_df = pd.DataFrame({"col1":sr1, "col2":sr2})
print(ser_df.head(5))
Sample Output:
Original Series: 0 php 1 python 2 java 3 c# 4 c++ dtype: object 0 1 1 2 2 3 3 4 4 5 dtype: int64 Combine above series to a dataframe: index 0 0 1 python 1 2 java 2 3 c# 3 4 c++ 4 5 NaN Using pandas concat: 0 1 0 php 1 1 python 2 2 java 3 3 c# 4 4 c++ 5 Using pandas DataFrame with a dictionary, gives a specific name to the columns: col1 col2 0 php 1 1 python 2 2 java 3 3 c# 4 4 c++ 5
Python-Pandas Code Editor:
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Previous: Write a Pandas program to display memory usage of a given DataFrame and every column of the DataFrame.
Next: Write a Pandas program to create DataFrames that contains random values, contains missing values, contains datetime values and contains mixed values.
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