How to create a DataFrames in Python
A Data Frame is a two-dimension collection of data. It is a data structure where data is stored in tabular form. Datasets are arranged in rows and columns; we can store multiple datasets in the data frame. We can perform various arithmetic operations, such as adding column/row selection and columns/rows in the data frame.
We can import the DataFrames from the external storage; these storages can be referred to as the SQL Database, CSV file, and an Excel file. We can also use the lists, dictionary, and from a list of dictionary, etc.
In this tutorial, we will learn to create the data frame in multiple ways. Let's understand these different ways.
An empty dataframe
We can create a basic empty Dataframe. The dataframe constructor needs to be called to create the DataFrame. Let's understand the following example.
Empty DataFrame Columns:  Index: 
Method - 2: Create a dataframe using List
We can create dataframe using a single list or list of lists. Let's understand the following example.
Method - 3: Create Dataframe from dict of ndarray/lists
The dict of ndarray/lists can be used to create a dataframe, all the ndarray must be of the same length. The index will be a range(n) by default; where n denotes the array length. Let's understand the following example.
Name Age 0 Tom 20 1 Joseph 21 2 Krish 19 3 John 18
Method - 4: Create a indexes Dataframe using arrays
Let's understand the following example to create the indexes dataframe using arrays.
Name Ratings position1 Renault 9.0 position2 Duster 8.0 position3 Maruti 5.0 position4 Honda City 3.0
In the above code, we have defined the column name with the various car names and their ratings. We used the array to create indexes.
Method - 5: Create Dataframe from list of dicts
We can pass the lists of dictionaries as input data to create the Pandas dataframe. The column names are taken as keys by default. Let's understand the following example.
A B C x y z 0 10.0 20.0 30.0 NaN NaN NaN 1 NaN NaN NaN 100.0 200.0 300.0
Let's understand another example to create the pandas dataframe from list of dictionaries with both row index as well as column index.
Example - 2:
x y first 1.0 2.0 second NaN NaN x y1 first 1.0 NaN second NaN NaN
Let's understand another example to create dataframe by passing lists of dictionary and rows.
Example - 3
x y z first 2 NaN 3 second 10 20.0 30
We have discussed the three ways to create the dataframe using the lists of dictionary.
Method - 6: Create Dataframe using the zip() function
The zip() function is used to merge the two lists. Let's understand the following example.
[('john', 95), ('krish', 63), ('arun', 54), ('juli', 47)] Name Marks 0 john 95 1 krish 63 2 arun 54 3 juli 47
Method - 7: Create Dataframe from Dicts of series
The dictionary can be passed to create a dataframe. We can use the Dicts of series where the subsequent index is the union of all the series of passed index value. Let's understand the following example.
Electronics Civil John 97 97 Abhinay 56 88 Peter 87 44 Andrew 45 96
In this tutorial, we have discussed the different ways to create the DataFrames.
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