How do i see rows and columns in python?

A Data frame is a two-dimensional data structure, i.e., data is aligned in a tabular fashion in rows and columns. We can perform basic operations on rows/columns like selecting, deleting, adding, and renaming. In this article, we are using nba.csv file.

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Dealing with Columns
Dealing with Rows:
How do you show rows and columns in Python?
How do you show columns in Python?
How do you check rows in Python?
How do I show rows and columns in pandas?

Dealing with Columns

In order to deal with columns, we perform basic operations on columns like selecting, deleting, adding and renaming.

Column Selection:
In Order to select a column in Pandas DataFrame, we can either access the columns by calling them by their columns name.

import pandas as pd

data = {'Name':['Jai', 'Princi', 'Gaurav', 'Anuj'],

'Age':[27, 24, 22, 32],

'Address':['Delhi', 'Kanpur', 'Allahabad', 'Kannauj'],

'Qualification':['Msc', 'MA', 'MCA', 'Phd']}

df = pd.DataFrame(data)

print(df[['Name', 'Qualification']])

Output:

For more examples refer to How to select multiple columns in a pandas dataframe

Column Addition:
In Order to add a column in Pandas DataFrame, we can declare a new list as a column and add to a existing Dataframe.

import pandas as pd

data = {'Name': ['Jai', 'Princi', 'Gaurav', 'Anuj'],

'Height': [5.1, 6.2, 5.1, 5.2],

'Qualification': ['Msc', 'MA', 'Msc', 'Msc']}

df = pd.DataFrame(data)

address = ['Delhi', 'Bangalore', 'Chennai', 'Patna']

df['Address'] = address

print(df)

Output:

For more examples refer to Adding new column to existing DataFrame in Pandas

Column Deletion:
In Order to delete a column in Pandas DataFrame, we can use the drop() method. Columns is deleted by dropping columns with column names.

import pandas as pd

data = pd.read_csv("nba.csv", index_col ="Name" )

data.drop(["Team", "Weight"], axis = 1, inplace = True)

print(data)

Output:
As shown in the output images, the new output doesn’t have the passed columns. Those values were dropped since axis was set equal to 1 and the changes were made in the original data frame since inplace was True.

Data Frame before Dropping Columns-

Data Frame after Dropping Columns-

For more examples refer to Delete columns from DataFrame using Pandas.drop()

Dealing with Rows:

In order to deal with rows, we can perform basic operations on rows like selecting, deleting, adding and renaming.

Row Selection:
Pandas provide a unique method to retrieve rows from a Data frame.DataFrame.loc[] method is used to retrieve rows from Pandas DataFrame. Rows can also be selected by passing integer location to an iloc[] function.

import pandas as pd

data = pd.read_csv("nba.csv", index_col ="Name")

first = data.loc["Avery Bradley"]

second = data.loc["R.J. Hunter"]

print(first, "\n\n\n", second)

Output:
As shown in the output image, two series were returned since there was only one parameter both of the times.

For more examples refer to Pandas Extracting rows using .loc[]

Row Addition:
In Order to add a Row in Pandas DataFrame, we can concat the old dataframe with new one.

import pandas as pd

df = pd.read_csv("nba.csv", index_col ="Name")

df.head(10)

new_row = pd.DataFrame({'Name':'Geeks', 'Team':'Boston', 'Number':3,

'Position':'PG', 'Age':33, 'Height':'6-2',

'Weight':189, 'College':'MIT', 'Salary':99999},

index =[0])

df = pd.concat([new_row, df]).reset_index(drop = True)

df.head(5)

Output:

Data Frame before Adding Row-

Data Frame after Adding Row-

For more examples refer to Add a row at top in pandas DataFrame

Row Deletion:
In Order to delete a row in Pandas DataFrame, we can use the drop() method. Rows is deleted by dropping Rows by index label.

import pandas as pd

data = pd.read_csv("nba.csv", index_col ="Name" )

data.drop(["Avery Bradley", "John Holland", "R.J. Hunter",

"R.J. Hunter"], inplace = True)

data

Output:
As shown in the output images, the new output doesn’t have the passed values. Those values were dropped and the changes were made in the original data frame since inplace was True.

Data Frame before Dropping values-

Data Frame after Dropping values-

For more examples refer to Delete rows from DataFrame using Pandas.drop()

Problem related to Columns:

How to get column names in Pandas dataframe
How to rename columns in Pandas DataFrame
How to drop one or multiple columns in Pandas Dataframe
Get unique values from a column in Pandas DataFrame
How to lowercase column names in Pandas dataframe
Apply uppercase to a column in Pandas dataframe
Capitalize first letter of a column in Pandas dataframe
Get n-largest values from a particular column in Pandas DataFrame
Get n-smallest values from a particular column in Pandas DataFrame
Convert a column to row name/index in Pandas

Problem related to Rows:

Apply function to every row in a Pandas DataFrame
How to get rows names in Pandas dataframe

How do you show rows and columns in Python?

You can try different methods to get the number of rows and columns of the dataframe:.

len(df).

len(df. index).

df. shape[0].

df[df. columns[0]]. count().

df. count().

df. size..

How do you show columns in Python?

You can use the loc and iloc functions to access columns in a Pandas DataFrame. Let's see how. If we wanted to access a certain column in our DataFrame, for example the Grades column, we could simply use the loc function and specify the name of the column in order to retrieve it.

How do you check rows in Python?

You can use len(df. index) to find the number of rows in pandas DataFrame, df.

How do I show rows and columns in pandas?

In order to display the number of rows and columns that Pandas displays by default, we can use the . get_option() function. This function takes a value and returns the provided option for that value.