[Pandas] Pandas DataFrame | Series | Index | Basic APIs

Pandas :  a Python library used for working with data sets.

-> Pandas has functions for analyzing, cleaning, exploring, and manipulating data.

 

 

 

 

[ DataFrame ] 

DataFrame : a Pandas DataFrame is a 2 dimensional data structure, like a 2 dimensional array, or a table with rows and columns in RDB(relational database-SQL)

 

 

 

 

[ Series ]

Series : Series is a one-dimensional array holding data of any type, like a column in a table. 

 

 

 

 

 

[ Index ]

Index : the rows which it can be defined a set of labels. 

- Pandas creates index by default (index start from 0) 

how to extract index? -> DataFrame.index | Series.index 

 

 

 

 

[ Basic APIs ]

read_csv() : Load the CSV into a DataFrame

 

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import pandas as pd

df= pd.read_csv('data.csv')

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Convert DataFrame to ndarray

 

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import pandas as pd

df.values() 

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drop() 

- row : axis = 0 | column : axis = 1 

- inplace = False => keep original dataframe and assign the new dataframe to " "

 

 

loc() - indexing by label of column

 

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import pandas as pd

df.loc[row, column)

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iloc() - indexing by position 

 

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import pandas as pd

df.iloc[row, column]

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* iloc does not support boolean indexing! 

 

 

Groupby 

: groupby method returns  

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import pandas as pd

dataframe.transform(by, axis, level, as_index, sort, group_keys, observed, dropna)

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-> To change type to DataFrame, we can use aggregation methods(sum, mean, max, min,...) 

==> DataFrameGroupBy -> DataFrame

 

 

 

 

[ Processing for Missing Data ] 

 

isna()

: it returns a DataFrame object where all the values are replaced with a Boolean value True for NA (not-a -number) values, and otherwise False. 

- NaN : returns True 

 

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import pandas as pd

df.isna()

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=> To Count how many NaN values in DataFrame

DataFrame. isna().sum()

 

 

 

 

 

fillna()

: it replaces the NULL values with a specified value.

 

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import pandas as pd

df.fillna(value, method, axis, inplace, limit, downcast)

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https://www.w3schools.com/python/pandas/pandas_ref_dataframe.asp

Pandas - DataFrame Reference