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Python Pandas Series - Series is a one-dimensional labeled array capable of holding data of any type (integer, string, float, python objects, etc.). The axis labels are collectively called index.

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Pandas Series is a one-dimensional labeled array capable of holding data of any type (integer, string, float, python objects, etc.). The axis labels are collectively called index.Labels need not be unique but must be a hashable type. The object supports both integer and label-based indexing and provides a host of methods for performing operations involving the index.

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The following examples show how to get a value from a pandas Series in three different scenarios. Method 1: Get Value from Pandas Series Using Index

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s.reset_index(name='list') A list 0 a 1 1 b 2 2 c 3 Series.to_frame. If you want to create a DataFrame without promoting the index to a column, use Series.to_frame, as suggested in this answer. This also supports a name parameter. s.to_frame(name='B') B A a 1 b 2 c 3 pd.DataFrame Constructor. You.

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Series.explode ( [ignore_index]) Transform each element of a list-like to a row. Series.searchsorted (value [, side, sorter]) Find indices where elements should be inserted to maintain order. Series.ravel ( [order]) Return the flattened underlying data as an ndarray or ExtensionArray.

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The contents of s is: 0 1 1 2 2 3 3 4 dtype: int64. By default is assigns an index. First it shows the index, then the element value. Create series from ndarray

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Ways to iterate through pandas/python. arr = pandas.Series ( [1, 1, 1, 2, 2, 2, 3, 3]) #Using Python range () method for i in range (len (arr)): print (arr [i]) range doesn't include the end value in the sequence. #List Comprehension print ( [arr [i] for i in range (len (arr))])

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Sets the Series name when given a scalar input. Index.name Corresponding Index property. Examples The Series name can be set initially when calling the constructor. >>> s = pd.Series( [1, 2, 3], dtype=np.int64, name='Numbers') >>> s 0 1 1 2 2 3 Name: Numbers, dtype: int64 >>> s.name = "Integers" >>> s 0 1 1 2 2 3 Name: Integers, dtype: int64

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Non-unique index values are allowed. Will default to RangeIndex (0, 1, 2,., n) if not provided. If data is dict-like and index is None, then the keys in the data are used as the index. If the index is not None, the resulting Series is reindexed with the index values. dtype str, numpy.dtype, or ExtensionDtype, optional. Data type for the.