Rishikesh Kumar Rishi

Rishikesh Kumar Rishi

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Articles by Rishikesh Kumar Rishi

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How to make a multi-index in Pandas?

Rishikesh Kumar Rishi
Rishikesh Kumar Rishi
Updated on 11-Mar-2026 389 Views

To make a multi-index in Pandas, we can use groupby with list of columns.StepsCreate a two-dimensional, size-mutable, potentially heterogeneous tabular data, df.Print the input DataFrame.Print the index of DataFrame count.Use groupby to get different levels of a hierarchical index and count it.Print the mulitindex set in step 4.Exampleimport pandas as pd df = pd.DataFrame(    {       "x": [5, 2, 1, 9],       "y": [4, 1, 5, 10],       "z": [4, 1, 5, 0]    } ) print "Input DataFrame is:", df print "Default index: ", df.count().index df1 = df.groupby(["x", "y"]).count() print ...

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How to reset hierarchical index in Pandas?

Rishikesh Kumar Rishi
Rishikesh Kumar Rishi
Updated on 11-Mar-2026 410 Views

To reset hierarchical index in Pandas, we can use reset_index() method.StepsCreate a two-dimensional, size-mutable, potentially heterogeneous tabular data, df.Print the input DataFrame.Use groupby to get different levels of a hierarchical index and count it.Print multi-hierarchical index DataFrame.Reset the multi-hierarchical index DataFrame, using df.reset_index().Print the new updated DataFrame.Exampleimport pandas as pd df = pd.DataFrame({"x": [5, 2, 1, 9], "y": [4, 1, 5, 10]}) print "Input DataFrame is:", df df1 = df.groupby(["x", "y"]).count() print "Hierarchical Index of input DataFrame is:", df1 df2 = df1.reset_index() print "After resetting: ", df2OutputInput DataFrame is:    x  y 0  5   4 ...

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How to check if any value is NaN in a Pandas DataFrame?

Rishikesh Kumar Rishi
Rishikesh Kumar Rishi
Updated on 11-Mar-2026 1K+ Views

To check if any value is NaN in a Pandas DataFrame, we can use isnull().values.any() method.StepsMake a series, s, one-dimensional ndarray with axis labels (including time series).Print the series, s.Check whether NaN is present or not.Create a two-dimensional, size-mutable, potentially heterogeneous tabular data, df.Print the input DataFrame.Check whether NaN is present or not.Exampleimport pandas as pd import numpy as np s = pd.Series([1, np.nan, 3, np.nan, 3, np.nan, 7, np.nan, 3]) print "Input series is:", s present = s.isnull().values.any() print "NAN is present in series: ", present df = pd.DataFrame(    {       "x": [5, np.nan, ...

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Create a DataFrame with customized index parameters in Pandas

Rishikesh Kumar Rishi
Rishikesh Kumar Rishi
Updated on 11-Mar-2026 2K+ Views

To create a DataFrame with some index, we can pass a list of values and assign them into index in DataFrame Class.StepsCreate a two-dimensional, size-mutable, potentially heterogeneous tabular data, df.Put a list of indices in the index of DataFrame class.Print the DataFrame with the customized index.Exampleimport pandas as pd df = pd.DataFrame(    {       "x": [5, 2, 1, 9],       "y": [4, 1, 5, 10],       "z": [4, 1, 5, 0]    } ) print "Input DataFrame is:", df df = pd.DataFrame(    {       "x": [5, 2, 1, 9],       "y": [4, 1, 5, 10],       "z": [4, 1, 5, 0]    },    index=["John", "Jacob", "Ally", "Simon"] ) print "With Customized Index: ", dfOutputInput DataFrame is:    x  y  z 0  5  4  4 1  2  1  1 2  1  5  5 3  9  10 0 With Customized Index:        x  y   z John   5  4   4 Jacob  2  1   1 Ally   1  5   5 Simon  9  10  0

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How to check if a column exists in Pandas?

Rishikesh Kumar Rishi
Rishikesh Kumar Rishi
Updated on 11-Mar-2026 9K+ Views

To check if a column exists in a Pandas DataFrame, we can take the following Steps −StepsCreate a two-dimensional, size-mutable, potentially heterogeneous tabular data, df.Print the input DataFrame, df.Initialize a col variable with column name.Create a user-defined function check() to check if a column exists in the DataFrame.Call check() method with valid column name.Call check() method with invalid column name.Exampleimport pandas as pd def check(col):    if col in df:       print "Column", col, "exists in the DataFrame."    else:       print "Column", col, "does not exist in the DataFrame." df = pd.DataFrame(   ...

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Count the frequency of a value in a DataFrame column in Pandas

Rishikesh Kumar Rishi
Rishikesh Kumar Rishi
Updated on 11-Mar-2026 4K+ Views

To count the frequency of a value in a DataFrame column in Pandas, we can use df.groupby(column name).size() method.StepsCreate a two-dimensional, size-mutable, potentially heterogeneous tabular data, df.Print the input DataFrame, df.Print frequency of column, x.Print frequency of column, y.Print frequency of column, z.Exampleimport pandas as pd df = pd.DataFrame(    {       "x": [5, 2, 1, 5],       "y": [4, 10, 5, 10],       "z": [1, 1, 5, 1]    } ) print "Input DataFrame is:", df col = "x" count = df.groupby('x').size() print "Frequency of values in column ", col, "is:", ...

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How to use the apply() function for a single column in Pandas?

Rishikesh Kumar Rishi
Rishikesh Kumar Rishi
Updated on 11-Mar-2026 16K+ Views

We can use apply() function on a column of a DataFrame with lambda expression.StepsCreate a two-dimensional, size-mutable, potentially heterogeneous tabular data, df.Print input DataFrame, df.Override column x with lambda x: x*2 expression using apply() method.Print the modified DataFrame.Exampleimport pandas as pd df = pd.DataFrame(    {       "x": [5, 2, 1, 5],       "y": [4, 10, 5, 10],       "z": [1, 1, 5, 1]    } ) print "Input DataFrame is:", df df['x'] = df['x'].apply(lambda x: x * 2) print "After applying multiplication of 2 DataFrame is:", dfOutputInput DataFrame is:    x  y  z 0  5  4  1 1  2 10  1 2  1  5  5 3  5 10  1 After applying multiplication of 2 DataFrame is:     x  y   z 0  10  4   1 1   4 10   1 2   2  5   5 3  10 10   1

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How to sort multiple columns of a Pandas DataFrame?

Rishikesh Kumar Rishi
Rishikesh Kumar Rishi
Updated on 11-Mar-2026 1K+ Views

To sort multiple columns of a Pandas DataFrame, we can use the sort_values() method.StepsCreate a two-dimensional, size-mutable, potentially heterogeneous tabular data, df.Print the input DataFrame, df.Initialize a variable col to sort the column.Print the sorted DataFrame.Exampleimport pandas as pd df = pd.DataFrame(    {       "x": [5, 2, 7, 0],       "y": [4, 7, 5, 1],       "z": [9, 3, 5, 1]    } ) print "Input DataFrame is:", df col = ["x", "y"] df = df.sort_values(col, ascending=[False, True]) print "After sorting column ", col, "DataFrame is:", dfOutputInput DataFrame is:    x  y  z 0  5  4  9 1  2  7  3 2  7  5  5 3  0  1  1 After sorting column ['x', 'y'] DataFrame is:    x  y  z 2  7  5  5 0  5  4  9 1  2  7  3 3  0  1  1

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Golang Program to Read the Contents of a File

Rishikesh Kumar Rishi
Rishikesh Kumar Rishi
Updated on 11-Mar-2026 1K+ Views

pre.prettyprint{width:99%!important;} a.demo{top:12px!important; float:right!important;}To read the contents of a file, we can take following steps −We can create a file called test.txt.Clean-up using defer statement.Write the contents of string.Call ReadFile() method to read the file.ReadFile reads the file named by filename and returns the contents.Print the content of the file.Examplepackage main import (    "fmt"    "io/ioutil"    "log"    "os" ) func CreateFile() {    file, err := os.Create("test.txt")    if err != nil {       log.Fatalf("failed creating file: %s", err)    }    defer file.Close()    _, err = file.WriteString("Welcome to Tutorials Point")    if err != ...

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Golang Program to Find the Area of a Rectangle Using Classes

Rishikesh Kumar Rishi
Rishikesh Kumar Rishi
Updated on 11-Mar-2026 614 Views

To find the area of a rectangle using classes, we can take following StepsDefine a struct with rectangle properties such as breadth and length.Define a method to calculate the area of the rectangle.In the main method, instantiate an object of rectangle.Call the struct method, i.e., Area, to calculate the area of the rectangle.Print the area of the rectangle.Examplepackage main import (    "fmt" ) type Rectangle struct {    breadth int    len int } func (r *Rectangle)Area() int{    return r. len * r.breadth } func main(){    rectangle := Rectangle{       breadth: 10,       ...

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