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Copy file name to clipboardExpand all lines: contrib/pandas/Pandas_Series_Vs_NumPy_ndarray.md
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## NumPy ndarray
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NumPy is short form for Numerical Python, provides a powerful array object called `ndarray`, which is the backbone of many scientific and mathematical Python libraries. ndarray is also called n-dimensional array. Indexing in ndarray is integer based indexing.
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NumPy is short form for Numerical Python, provides a powerful array object called `ndarray`, It is very important for many scientific and mathematical Python libraries. ndarray is also called n-dimensional array. Indexing in ndarray is integer based indexing (like arr[0], arr[3], etc.).
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Features of NumPy `ndarray`:
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- When you need to perform mathematical operations on numerical data.
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- When you’re working with multi-dimensional data.
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- When computational efficiency is important.
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- When you need to store data of same data type. `
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- When you need to store data of same data type.
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## Pandas Series
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Pandas is a Python library used for data manipulation and analysis, introduces the `Series` data structure, which is designed for handling labeled one-dimensional data efficiently.
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Pandas is a Python library used for data manipulation and analysis, introduces the `Series` data structure, which is designed for handling labeled one-dimensional data efficiently. Indexing in Pandas Series is Label-based. It effectively handles heterogeneous data.
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Features of Pandas `Series`:
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-**Labeled Data**: Pandas Series associates a label (or index) with each element of the array, making it easier to work with heterogeneous or labeled data.
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-**Heterogeneous Data**: Unlike NumPy arrays, Pandas Series can hold data of different types (integers, floats, strings, etc.) within the same object.
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-**Data Alignment**: One of the powerful features of Pandas Series is its ability to automatically align data based on label. This makes handling and manipulating data much more intuitive and less error-prone.
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-**Data Alignment**: One of the powerful features of Pandas Series is its ability to automatically align data based on label.
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