How to Create Data Frame From Dictionary of Series | Pandas Data Frame | Data Frame | Pandas

In Pandas, you can create a DataFrame from a dictionary of Series using the pd.DataFrame constructor. Here's an example:

import pandas as pd

# Create a dictionary of Series
data = {'A': pd.Series([1, 2, 3]),
'B': pd.Series([4, 5, 6]),
'C': pd.Series([7, 8, 9])}

# Create a DataFrame from the dictionary
df = pd.DataFrame(data)

# Print the DataFrame
print(df)

In this example, we first create a dictionary data with three keys 'A', 'B', and 'C', each associated with a Series of values. The Series must have the same length. We then use the pd.DataFrame constructor to create a DataFrame df from the dictionary. The resulting DataFrame has three columns labeled 'A', 'B', and 'C', and three rows containing the values from the corresponding Series.

Alternatively, you can specify the index of the DataFrame using the index parameter of the pd.DataFrame constructor, like this:

# Create a dictionary of Series with custom index
data = {'A': pd.Series([1, 2, 3], index=['x', 'y', 'z']),
'B': pd.Series([4, 5, 6], index=['x', 'y', 'z']),
'C': pd.Series([7, 8, 9], index=['x', 'y', 'z'])}

# Create a DataFrame from the dictionary with custom index
df = pd.DataFrame(data, index=['x', 'y', 'z'])

# Print the DataFrame
print(df)

In this example, we create a dictionary data with the same structure as before, but with custom index labels. We then use the pd.DataFrame constructor to create a DataFrame df from the dictionary, with the same custom index labels. The resulting DataFrame has three columns labeled 'A', 'B', and 'C', and three rows labeled 'x', 'y', and 'z', containing the values from the corresponding Series.

code snippet
- create a DataFrame from Dictionary of Series

d = {'one':pd.Series([1,2,3],index=['a','b','c']),
'two':pd.Series([1,2,3,4],index = ['a','b','c','d'])}
df = pd.DataFrame(d)
print(df)

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