Cara menggunakan dynamic dataframe python

Pandas DataFrame is a 2-dimensional labeled data structure like any table with rows and columns. The size and values of the dataframe are mutable,i.e., can be modified. It is the most commonly used pandas object. Pandas DataFrame can be created in multiple ways. Let’s discuss different ways to create a DataFrame one by one.

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    DataFrame() function is used to create a dataframe in Pandas. The syntax of creating dataframe is:

    pandas.DataFrame(data, index, columns)

    where,

    data: It is a dataset from which dataframe is to be created. It can be list, dictionary, scalar value, series, ndarrays, etc.

    index: It is optional, by default the index of the dataframe starts from 0 and ends at the last data value(n-1). It defines the row label explicitly.

    columns: This parameter is used to provide column names in the dataframe. If the column name is not defined by default, it will take a value from 0 to n-1.

    Method #0:Creating an Empty DataFrame

    Python3




    # Importing Pandas to create DataFrame

    import pandas as pd

      

    # Creating Empty DataFrame and Storing it in variable df

    df= pd.DataFrame()

      

    # Importing Pandas to create DataFrame0

    # Importing Pandas to create DataFrame1# Importing Pandas to create DataFrame2

    Output: 

    • The DataFrame() function of pandas is used to create a dataframe.
    • df variable is the name of the dataframe in our example.

    Cara menggunakan dynamic dataframe python

    Output 

     

    Method #1: Creating  Dataframe from Lists

    Python3




    # Importing Pandas to create DataFrame3

    import pandas as pd

      

    # Importing Pandas to create DataFrame7

    # Importing Pandas to create DataFrame8= import0import1import2import3import2import5import2import7import2import9import2pandas as pd1pandas as pd2

      

    pandas as pd4

    df= pandas as pd7=import0 0 1

      

     3

    df


    Dataframe created using list

    Method #2: Creating Pandas DataFrame from lists of lists.
     

    Python3




    # Importing Pandas to create DataFrame3

    import pandas as pd

      

     9

    # Importing Pandas to create DataFrame8= # Creating Empty DataFrame and Storing it in variable df2# Creating Empty DataFrame and Storing it in variable df3import2import1# Creating Empty DataFrame and Storing it in variable df6# Creating Empty DataFrame and Storing it in variable df7import2# Creating Empty DataFrame and Storing it in variable df9# Creating Empty DataFrame and Storing it in variable df6df1import2df3df4

      

    df6

    df= pandas as pd7=import0=2import2=4 1

      

     3

    df

    Output: 
     

    Cara menggunakan dynamic dataframe python

     

    Method #3: Creating DataFrame from dict of narray/lists
    To create DataFrame from dict of narray/list, all the narray must be of same length. If index is passed then the length index should be equal to the length of arrays. If no index is passed, then by default, index will be range(n) where n is the array length.
     

    Python3




    =9

    pd.DataFrame()0

    pd.DataFrame()1

      

    import pandas as pd

      

    pd.DataFrame()6

    # Importing Pandas to create DataFrame8= pd.DataFrame()9=2 1 2import2# Creating Empty DataFrame and Storing it in variable df7import2 6import2 8 9

    # Importing Pandas to create DataFrame00=4 1import3import2# Importing Pandas to create DataFrame05import2# Importing Pandas to create DataFrame07import2# Importing Pandas to create DataFrame09# Importing Pandas to create DataFrame10

      

    # Importing Pandas to create DataFrame12

    df= # Importing Pandas to create DataFrame15

      

    # Importing Pandas to create DataFrame17

    df

    Output: 
     

    Cara menggunakan dynamic dataframe python

    Note: While creating dataframe using dictionary, the keys of dictionary will be column name by default. We can also provide column name explicitly using column parameter.
      
    Method #4: Creating a DataFrame by proving index label explicitly.
     

    Python3




    =9

    # Importing Pandas to create DataFrame20

      

    # Importing Pandas to create DataFrame22

    import pandas as pd

      

    pd.DataFrame()6

    # Importing Pandas to create DataFrame8= pd.DataFrame()9=2 1 2import2# Importing Pandas to create DataFrame34import2# Creating Empty DataFrame and Storing it in variable df7import2df1 9

    # Importing Pandas to create DataFrame00# Importing Pandas to create DataFrame41 1# Importing Pandas to create DataFrame43import2# Importing Pandas to create DataFrame45import2# Importing Pandas to create DataFrame47import2# Importing Pandas to create DataFrame49# Importing Pandas to create DataFrame10

      

    # Importing Pandas to create DataFrame52

    df= # Importing Pandas to create DataFrame55=import0# Importing Pandas to create DataFrame58import2

    # Importing Pandas to create DataFrame60# Importing Pandas to create DataFrame61import2

    # Importing Pandas to create DataFrame60# Importing Pandas to create DataFrame64import2

    # Importing Pandas to create DataFrame60# Importing Pandas to create DataFrame67 1

      

    # Importing Pandas to create DataFrame70

    df

    Output: 
     

    Cara menggunakan dynamic dataframe python

      
    Method #5: Creating Dataframe from list of dicts
    Pandas DataFrame can be created by passing lists of dictionaries as a input data. By default dictionary keys will be taken as columns.
     

    Python3




    # Importing Pandas to create DataFrame72

    # Importing Pandas to create DataFrame73

    import pandas as pd

      

    # Importing Pandas to create DataFrame77

    # Importing Pandas to create DataFrame8= # Importing Pandas to create DataFrame80# Importing Pandas to create DataFrame81# Importing Pandas to create DataFrame82# Importing Pandas to create DataFrame83import2# Importing Pandas to create DataFrame85# Importing Pandas to create DataFrame82# Importing Pandas to create DataFrame87import2# Importing Pandas to create DataFrame89# Importing Pandas to create DataFrame82# Importing Pandas to create DataFrame91# Importing Pandas to create DataFrame92

    # Importing Pandas to create DataFrame00pd.DataFrame()9# Importing Pandas to create DataFrame81# Importing Pandas to create DataFrame82import1import2# Importing Pandas to create DataFrame85# Importing Pandas to create DataFrame82import3import2# Importing Pandas to create DataFrame89# Importing Pandas to create DataFrame82import5import06

      

    import08

    df= # Importing Pandas to create DataFrame15

      

    import13

    df

    Output: 
     

    Cara menggunakan dynamic dataframe python

    Another example to create pandas DataFrame by passing lists of dictionaries and row indexes.
     

    Python3




    import15

    import16

    import17

    import pandas as pd

      

    import21

    # Importing Pandas to create DataFrame8= # Importing Pandas to create DataFrame80# Importing Pandas to create DataFrame85# Importing Pandas to create DataFrame82# Importing Pandas to create DataFrame87import2# Importing Pandas to create DataFrame89# Importing Pandas to create DataFrame82# Importing Pandas to create DataFrame91import32# Importing Pandas to create DataFrame81# Importing Pandas to create DataFrame82import1import2# Importing Pandas to create DataFrame85# Importing Pandas to create DataFrame82import3import2# Importing Pandas to create DataFrame89# Importing Pandas to create DataFrame82import5import06

      

    import46

    import47

    df= # Importing Pandas to create DataFrame55=import0import53import2import55 1

      

    import13

    df

    Output: 
     

    Cara menggunakan dynamic dataframe python

    Another example to create pandas DataFrame from lists of dictionaries with both row index as well as column index.
     

    Python3




    import60

    import61

    import62

    import63

      

    import pandas as pd

      

    import68

    # Importing Pandas to create DataFrame8= # Importing Pandas to create DataFrame80# Importing Pandas to create DataFrame81# Importing Pandas to create DataFrame82# Importing Pandas to create DataFrame83import2# Importing Pandas to create DataFrame85# Importing Pandas to create DataFrame82# Importing Pandas to create DataFrame87# Importing Pandas to create DataFrame92

    # Importing Pandas to create DataFrame00pd.DataFrame()9# Importing Pandas to create DataFrame81# Importing Pandas to create DataFrame82import84import2# Importing Pandas to create DataFrame85# Importing Pandas to create DataFrame82import1import2# Importing Pandas to create DataFrame89# Importing Pandas to create DataFrame82import3import06

      

    import95

    import96

    import97= # Importing Pandas to create DataFrame55=import0import53import2

    pandas as pd04import55 9

    pandas as pd07pandas as pd08=import0# Importing Pandas to create DataFrame81import2# Importing Pandas to create DataFrame85 1

      

    pandas as pd16

    pandas as pd17

    pandas as pd18= # Importing Pandas to create DataFrame55=import0import53import2

    pandas as pd04import55 9

    pandas as pd07pandas as pd08=import0# Importing Pandas to create DataFrame81import2pandas as pd34 1

      

    pandas as pd37

    # Importing Pandas to create DataFrame1pandas as pd39pandas as pd40pandas as pd41

      

    pandas as pd43

    # Importing Pandas to create DataFrame1pandas as pd45

    Output: 
     

    Cara menggunakan dynamic dataframe python

      
    Method #6: Creating DataFrame using zip() function.
    Two lists can be merged by using list(zip()) function. Now, create the pandas DataFrame by calling pd.DataFrame() function.
     

    Python3




    pandas as pd46

    pandas as pd47

      

    import pandas as pd

      

    pandas as pd52

    pandas as pd53= import0# Creating Empty DataFrame and Storing it in variable df3import2 6import2# Creating Empty DataFrame and Storing it in variable df7import2df1pandas as pd2

      

    pandas as pd65

    pandas as pd66= import0pandas as pd69import2import5import2pandas as pd73import2pandas as pd75pandas as pd2

      

    pandas as pd78

    pandas as pd79

    pandas as pd80= pandas as pd82pandas as pd83pandas as pd84pandas as pd85

      

    pandas as pd87

    pandas as pd80

      

      

    pandas as pd91

    pandas as pd92

    df= pandas as pd95

    pandas as pd96pandas as pd08=import0=2import2=4 1

      

     05

    df

    Output: 
     

    Cara menggunakan dynamic dataframe python

    Method#7:  Creating dataframe from series

    To create a dataframe from series, we must pass series as argument to DataFrame() function.

    Python3




    =9

     08

      

    import pandas as pd

      

     13

     14=   16import1import2import3import2import5import2import7 1

     25

    df=  28

      

     30

    df

     

     

    Method #8: Creating DataFrame from Dictionary of series.
    To create DataFrame from Dict of series, dictionary can be passed to form a DataFrame. The resultant index is the union of all the series of passed indexed.
     

    Python3




    =9

     33

      

    import pandas as pd

      

     38

     14= pd.DataFrame()9 42 43import1import2import3import2import5import2import7 9

     52 53=import0# Importing Pandas to create DataFrame81import2# Importing Pandas to create DataFrame85import2# Importing Pandas to create DataFrame89import2 62 86