Vani Nalliappan

Vani Nalliappan

122 Articles Published

Articles by Vani Nalliappan

Page 7 of 13

Write a program in Python to find the minimum rank of a particular column in a dataframe

Vani Nalliappan
Vani Nalliappan
Updated on 25-Feb-2021 392 Views

SolutionAssume, you have a dataframe and minimum rank of a particular column,  Id Name    Age    Rank 0 1 Adam    12    1.0 1 2 David   13    3.0 2 3 Michael 14    5.0 3 4 Peter   12    1.0 4 5 William 13    3.0To solve this, we will follow the steps given below −Define a dataframe.Assign df[‘Age’] column inside rank function to calculate the minimum rank for axis 0 is, df["Age"].rank(axis=0, method ='min', ascending=True)ExampleLet’s see the following code to get a better understanding −import pandas as pd data = {'Id': [1, 2, 3, ...

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Write a program in Python to create a panel from a dictionary of dataframe and print the maximum value of the first column

Vani Nalliappan
Vani Nalliappan
Updated on 25-Feb-2021 247 Views

The result for a maximum value of the first column in panel ismaximum value of first column is ; Column1    1.377292SolutionTo solve this, we will follow the below approach −Set data value as dictionary key is ‘Column1’ with value as pd.DataFrame(np.random.randn(5, 3))data = {'Column1' : pd.DataFrame(np.random.randn(5, 3))}Assign data to Panel and save it as pp = pd.Panel(data)Print the column using dict key Column1print(p['Column1'])Calculate the maximum value of first column using, minor_xs(0) ,p.minor_xs(0).max()ExampleLet’s see the following code to get a better understanding −import pandas as pd import numpy as np data = {'Column1' : pd.DataFrame(np.random.randn(5, 3))} p = pd.Panel(data) print("Panel ...

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Write a program in Python to shift a dataframe index by two periods in positive and negative direction

Vani Nalliappan
Vani Nalliappan
Updated on 25-Feb-2021 215 Views

Assume, you have a dataframe and the shift index by two periods in positive and negative direction is, shift the index by three periods in positive direction                      Id Age 2020-01-01 00:00:00 NaN NaN 2020-01-01 12:00:00 NaN NaN 2020-01-02 00:00:00 1.0 10.0 2020-01-02 12:00:00 2.0 12.0 2020-01-03 00:00:00 3.0 14.0 shift the index by three periods in negative direction                      Id Age 2020-01-01 00:00:00 3.0 14.0 2020-01-01 12:00:00 4.0 11.0 2020-01-02 00:00:00 5.0 13.0 2020-01-02 12:00:00 NaN NaN 2020-01-03 00:00:00 NaN NaNSolutionTo ...

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Write a program in Python to remove first duplicate rows in a given dataframe

Vani Nalliappan
Vani Nalliappan
Updated on 25-Feb-2021 343 Views

Assume, you have a dataframe and the result for removing first duplicate rows are,     Id Age 0    1 12 3    4 13 4    5 14 5    6 12 6    2 13 7    7 16 8    3 14 9    9 15 10  10 14SolutionTo solve this, we will follow the steps given below −Define a dataframeApply drop_duplicates function inside Id and Age column then assign keep initial value as ‘last’.df.drop_duplicates(subset=['Id', 'Age'], keep='last')Store the result inside same dataframe and print itExampleLet’s see the below implementation to get a better understanding −import pandas ...

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Write a program in Python to compute grouped data covariance and calculate grouped data covariance between two columns in a given dataframe

Vani Nalliappan
Vani Nalliappan
Updated on 25-Feb-2021 441 Views

Assume, you have a dataframe and the result for calculating covariance from grouped data and corresponding column as, Grouped data covariance is:                   mark1       mark2 subjects maths    mark1    25.0    12.500000          mark2    12.5    108.333333 science  mark1    28.0    50.000000          mark2    50.0    233.333333 Grouped data covariance between two columns: subjects maths    12.5 science  50.0 dtype: float64SolutionTo solve this, we will follow the steps given below −Define a dataframeApply groupby function inside dataframe subjects ...

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Write a program in Python to shift the first column and get the value from the user, if the input is divisible by both 3 and 5 and then fill the missing value

Vani Nalliappan
Vani Nalliappan
Updated on 24-Feb-2021 127 Views

Input −Assume you have a DataFrame, and the result for shifting the first column and fill the missing values are,  one two three 0 1   10 100 1 2   20 200 2 3   30 300 enter the value 15  one two three 0 15  1   10 1 15  2   20 2 15  3   30SolutionTo solve this, we will follow the below approach.Define a DataFrameShift the first column using below code, data.shift(periods=1, axis=1)Get the value from user and verify if it is divisible by 3 and 5. If the result is true then fill missing ...

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Write a program to truncate a dataframe time series data based on index value

Vani Nalliappan
Vani Nalliappan
Updated on 24-Feb-2021 389 Views

Assume you have a dataframe with time series data and the result for truncated data is, before truncate:  Id time_series 0 1 2020-01-05 1 2 2020-01-12 2 3 2020-01-19 3 4 2020-01-26 4 5 2020-02-02 5 6 2020-02-09 6 7 2020-02-16 7 8 2020-02-23 8 9 2020-03-01 9 10 2020-03-08 after truncate:  Id time_series 1 2 2020-01-12SolutionTo solve this, we will follow the steps given below −Define a dataframe.Create date_range function inside start=’01/01/2020’, periods = 10 and assign freq = ‘W’. It will generate ten dates from given start date to next weekly start dates and store it as df[‘time_series’].df['time_series'] ...

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Write a program in Python to compute autocorrelation between series and number of lags

Vani Nalliappan
Vani Nalliappan
Updated on 24-Feb-2021 313 Views

Assume, you have series and the result for autocorrelation with lag 2 is, Series is: 0    2.0 1    10.0 2    3.0 3    4.0 4    9.0 5    10.0 6    2.0 7    NaN 8    3.0 dtype: float64 series correlation:    -0.4711538461538461 series correlation with lags:    -0.2933396642805515SolutionTo solve this, we will follow the steps given below −Define a seriesFind the series autocorrelation using the below method, series.autocorr()Calculate the autocorrelation with lag=2 as follows, series.autocorr(lag=2)ExampleLet’s see the below code to get a better understanding, import pandas as pd import numpy as np series = ...

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Write a program in Python to export a given dataframe into Pickle file format and read the content from the Pickle file

Vani Nalliappan
Vani Nalliappan
Updated on 24-Feb-2021 247 Views

Assume you have a dataframe and the result for exporting into pickle file and read the contents from file as, Export to pickle file: Read contents from pickle file:   Fruits    City 0 Apple    Shimla 1 Orange   Sydney 2 Mango    Lucknow 3 Kiwi    WellingtonSolutionTo solve this, we will follow the steps given below −Define a dataframe.Export the dataframe to pickle format and name it as ‘pandas.pickle’, df.to_pickle('pandas.pickle')Read the contents from ‘pandas.pickle’ file and store it as result, result = pd.read_pickle('pandas.pickle')ExampleLet’s see the below implementation to get better understanding, import pandas as pd df = pd.DataFrame({'Fruits': ...

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Write a program in Python to resample a given time series data and find the maximum month-end frequency

Vani Nalliappan
Vani Nalliappan
Updated on 24-Feb-2021 244 Views

Assume, you have time series and the result for maximum month-end frequency, DataFrame is:  Id time_series 0 1 2020-01-05 1 2 2020-01-12 2 3 2020-01-19 3 4 2020-01-26 4 5 2020-02-02 5 6 2020-02-09 6 7 2020-02-16 7 8 2020-02-23 8 9 2020-03-01 9 10 2020-03-08 Maximum month end frequency:               Id time_series time_series 2020-01-31    4 2020-01-26 2020-02-29    8 2020-02-23 2020-03-31    10 2020-03-08SolutionTo solve this, we will follow the steps given below −Define a dataframe with one column, d = {'Id': [1, 2, 3, 4, 5, 6, 7, 8, 9, 10]} ...

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