Update README.md

Signed-off-by: David Rotermund <54365609+davrot@users.noreply.github.com>
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@ -663,6 +663,73 @@ class pandas.DataFrame(data=None, index=None, columns=None, dtype=None, copy=Non
> Data structure also contains labeled axes (rows and columns). Arithmetic operations align on both row and column labels. Can be thought of as a dict-like container for Series objects. The primary pandas data structure.
### Combining two series into one dataframe
```python
import pandas as pd
import numpy as np
index = pd.Series(["A", "B", "C", "D", "E"])
rng = np.random.default_rng()
np_data_1 = rng.random((5))
data_1 = pd.Series(np_data_1, index=index)
np_data_2 = rng.random((5))
data_2 = pd.Series(np_data_2, index=index)
data_3 = pd.concat([data_1, data_2], axis=1)
print(type(data_1)) # -> <class 'pandas.core.series.Series'>
print(type(data_2)) # -> <class 'pandas.core.series.Series'>
print(type(data_3)) # -> <class 'pandas.core.frame.DataFrame'>
print(data_3)
print()
print(data_3.columns) # -> RangeIndex(start=0, stop=2, step=1)
print(data_3.columns.values) # -> [0 1]
```
```python
0 1
A 0.942032 0.213441
B 0.379446 0.937325
C 0.645035 0.799521
D 0.546175 0.656740
E 0.564155 0.546581
```
### Renaming the columns
```python
data_3.columns = ["Alpha", "Beta"]
print(data_3)
print()
print(data_3.columns) # -> Index(['Alpha', 'Beta'], dtype='object')
print()
print(data_3[ "Beta"])
```
Output:
```python
Alpha Beta
A 0.942032 0.213441
B 0.379446 0.937325
C 0.645035 0.799521
D 0.546175 0.656740
E 0.564155 0.546581
A 0.213441
B 0.937325
C 0.799521
D 0.656740
E 0.546581
Name: Beta, dtype: float64
```
## Saving (pandas.DataFrame.to_pickle) / loading (pandas.read_pickle) data natively
Save: