added example of using pandas.series (#30534)
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Christopher McCormack
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@ -29,6 +29,24 @@ A data frame consists of a number of rows and columns. Each column represents a
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## Series
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## Series
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Series is the basic data-type in pandas. A Series is very similar to an array (NumPy array) (in fact it is built on top of the NumPy array object). A Series can have axis labels, as it can be indexed by a label with no number indexing for the location of data. It can hold any valid Python Object like List, Dictionary, etc.
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Series is the basic data-type in pandas. A Series is very similar to an array (NumPy array) (in fact it is built on top of the NumPy array object). A Series can have axis labels, as it can be indexed by a label with no number indexing for the location of data. It can hold any valid Python Object like List, Dictionary, etc.
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```python
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pd.Series([1,2,3])
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```
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output:
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```output
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0 1
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1 2
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2 3
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dtype: int64
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```
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```python
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np.array([1,2,3])
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```
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output:
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```output
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array([1, 2, 3])
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```
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## Loading Data from a CSV File
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## Loading Data from a CSV File
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A `.csv` file is a *comma separated value* file. A very common way to store data. To load such data into a pandas data frame use the `read_csv` method:
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A `.csv` file is a *comma separated value* file. A very common way to store data. To load such data into a pandas data frame use the `read_csv` method:
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```python
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```python
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