Pandas provides data structures and functionality to quickly manipulate and analyze data. The key to understanding Pandas for machine learning is understanding the Series and DataFrame data structures.
Series
A series is a one-dimensional array where the rows and columns can be labeled.
import numpy as np
import pandas as pd
_array=np.array([1,2,3])
row_name=['a','b','c']
_series=pd.Series(_array,row_name)
print(_series)
DataFrame
A data frame is a multi-dimensional array where the rows and the columns can be labeled.
import numpy as np
import pandas as pd
_array=np.array([[1,2,3],[4,5,6]])
row_name=['a','b']
col_name=['1','2','3']
df=pd.DataFrame(_array,index=row_name,columns=col_name)
print(df)
