Pandas Series and DataFrame Structures A pandas Series is a one-dimensional data structure in Python that represents a contiguous range of values. It is...
Pandas Series and DataFrame Structures
A pandas Series is a one-dimensional data structure in Python that represents a contiguous range of values. It is similar to a list but has additional functionalities and methods for data manipulation.
Example:
python
series = pd.Series([1, 2, 3, 4, 5])
print(series)
Output:
0 1 2 3 4
DataFrame is a two-dimensional data structure in pandas that represents a table-like data. It is similar to a NumPy array but is specifically designed for data manipulation and analysis.
Example:
python
data = {'Name': ['John', 'Mary', 'Bob'], 'Age': [25, 30, 35]}
df = pd.DataFrame(data)
print(df)
Output:
| Name | Age |
|---|---|
| John | 25 |
| Mary | 30 |
| Bob | 35 |
Key Differences:
Shape: A pandas Series is one-dimensional, while a DataFrame is two-dimensional.
Data Type: Series elements are of the same data type, while DataFrame elements can have different data types.
Indexing and Selection: Series indices run from 0 to the length of the series, while DataFrame indices run from 0 to the length of the DataFrame.
Data Manipulation Methods: Series provides methods for basic data manipulation, while DataFrame offers advanced features for data wrangling, aggregation, and analysis