Datasciencemadesimple.com how to use, tutorial

Create or add new column to dataframe in python pandas

Details: In this tutorial we will learn how to create or add new column to dataframe in python pandas. creating a new column or variable to the already existing dataframe in python pandas is explained with example. adding a new column or variable to the already existing dataframe in python pandas with an example.

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Summary or Descriptive statistics in R - DataScience Made

Details: Descriptive Statistics of the dataframe in R can be calculated by 3 different methods. Let’s see how to calculate summary statistics of each column of dataframe in R with an example for each method. summary() function in R is used to get the summary statistics of the column

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Get number of rows and number of columns of dataframe in

Details: Get Size and Shape of the dataframe: In order to get the number of rows and number of column in pyspark we will be using functions like count() function and length() function. Dimension of the dataframe in pyspark is calculated by extracting the number of rows and number columns of the dataframe.

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Padding with ljust(),rjust() and center() function in

Details: width— This is string length in total after padding.; fillchar— This is filler character used for padding, default is a space.; Example of ljust() Function in python: ljust() function in python pads the string in the end with fillchar # ljust() function in python str = "Salute to the mother earth"; print str.ljust(50, '^')

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Rearrange or reorder column in pyspark - DataScience Made

Details: Using select() function in pyspark we can select the column in the order which we want which in turn rearranges the column according to the order that we want which is shown below. df_basket_reordered = df_basket1.select("price","Item_group","Item_name") df_basket_reordered.show() so the resultant dataframe with rearranged columns will be

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Subset or Filter data with multiple conditions in pyspark

Details: Subset or filter data with single condition in pyspark. Subset or filter data with single condition in pyspark can be done using filter() function with conditions inside the filter function. ## subset with single condition df.filter(df.mathematics_score > 50).show()

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Reorder or Rearrange column name in SAS - DataScience Made

Details: Col1, Col2, Col3 are the exact order of the columns. Rearrange Column name in SAS using Retain Statement. Rearrange the column name in SAS using retain statement takes the column names in specific order and maintains the same order in resultant table there by column name is rearranged as we mention

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Groupby function in R using Dplyr - group_by - DataScience

Details: Groupby Function in R – group_by is used to group the dataframe in R. Dplyr package in R is provided with group_by() function which groups the dataframe by multiple columns with mean, sum and other functions like count, maximum and minimum.

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subtract or Add days, months and years to timestamp in

Details: In order to subtract or add days , months and years to timestamp in pyspark we will be using date_add() function and add_months() function. add_months() Function with number of months as argument to add months to timestamp in pyspark. date_add() Function number of days as argument to add months to timestamp. add_months() Function with number of months as argument is also a roundabout method to

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CODE Function in Excel - Get the ASCII Value in Excel

Details: CODE function in Excel gets the character as an input and returns the corresponding ASCII Value. NOTE: The Returned code may vary based on the operation system. Syntax of CODE Function in Excel:

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Get the List of column names of dataframe in R

Details: To get the list of column names of dataframe in R we use functions like names() and colnames(). In this tutorial we will be looking on how to get the list of column names in the dataframe with an example

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Extract First N rows & Last N rows in pyspark (Top N

Details: Extract Last row of dataframe in pyspark – using last() function. last() Function extracts the last row of the dataframe and it is stored as a variable name “expr” and it is passed as an argument to agg() function as shown below. ##### Extract last row of the dataframe in pyspark from pyspark.sql import functions as F expr = [F.last(col).alias(col) for col in df_cars.columns] df_cars.agg

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Add Custom Labels to x-y Scatter plot in Excel

Details: Step 5: Now the ice cream flavors will appear on the labels.Click on X Value and Y Value under LABEL OPTIONS. So the resultant chart will give you scatter plot with Labels of flavors and Label of X values and Y values (x, y coordinates) as shown below

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Scaling or Normalizing the column in R - DataScience Made

Details: Scaling or Normalizing the column in R is accomplished using scale() function. Let’s see how to scale or normalize the column of a dataframe example.

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Typecast Integer to Decimal and Integer to float in

Details: Now let’s convert the zip column to string using cast() function with DecimalType() passed as an argument which converts the integer column to decimal column in pyspark and it is stored as a dataframe named output_df ##### Type cast an integer column to Decimal column in pyspark from pyspark.sql.types import DecimalType output_df = df_cust.withColumn("zip",df_cust["zip"].cast(DecimalType()))

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Add leading zeros to the column in pyspark - DataScience

Details: Add leading zeros to the column in pyspark using concat() function – Method 1. We will be Using lit() and concat() function to add the leading zeros to the column in pyspark. lit() function takes up ‘00’ and concatenate with ‘grad_score’ column there by adding leading zeros to the column

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Get difference between two dates in days,weeks, years

Details: Calculate difference between two dates in days in pyspark . In order to calculate the difference between two dates in days we use datediff() function. datediff() function takes two argument, both are date on which we need to find the difference between two dates. ### Calculate difference between two dates in days in pyspark from pyspark.sql.functions import datediff,col df1.withColumn("diff_in

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Get Month, Year and Monthyear from date in pandas python

Details: dt.year is the inbuilt method to get year from date in Pandas Python. strftime() function can also be used to extract year from date.month() is the inbuilt function in pandas python to get month from date.to_period() function is used to extract month year. Let’s see how to. Get the year from any given date in pandas python; Get month from any given date in pandas

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Delete or Drop rows in R with conditions - DataScience

Details: Delete or Drop rows in R with conditions done using subset function. Drop rows with missing and null values using omit(), complete.cases() and slice()

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Get List of columns and its data type in Pyspark

Details: In order to Get list of columns and its data type in pyspark we will be using dtypes function and printSchema() function . We will explain how to get list of column names of the dataframe along with its data type in pyspark with an example.

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Convert column to categorical in pandas python

Details: Data type of Is_Male column is integer . so let’s convert it into categorical. Method 1: Convert column to categorical in pandas python using categorical() function ## Typecast to Categorical column in pandas df1['Is_Male'] = pd.Categorical(df1.Is_Male) df1.dtypes

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Difference between two dates in R by days, weeks, months

Details: In Order to get difference between two dates in R by days, weeks, months and years. We will be using difftime() function. difftime() function takes days as argument to find difference between two dates in R in days.

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Index, Select and Filter dataframe in pandas python

Details: Index, Select and Filter dataframe in pandas python – In this tutorial we will learn how to index the dataframe in pandas python with example, How to select and filter the dataframe in pandas python with column name and column index using .ix(), .iloc() and .loc()

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Mean Median and Mode in SAS – Row wise and column wise

Details: In order to calculate Mean Median and Mode in SAS we will be using mean() and median() function. In order to calculate row wise mean in SAS we will be using mean() function in SAS Datastep.

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Sort the dataframe in pyspark – Sort on single column

Details: orderBy() function takes up the column name as argument and sorts the dataframe by column name. It also takes another argument ascending =False which sorts the dataframe by decreasing order of the column ## Sort dataframe in descending - sort by single column df_student_detail1 = df_student_detail.orderBy('science_score', ascending=False) df_student_detail1.show()

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Join in Pandas: Merge data frames (inner, outer, right

Details: left_df – Dataframe1 right_df– Dataframe2. on− Columns (names) to join on.Must be found in both the left and right DataFrame objects. how – type of join needs to be performed – ‘left’, ‘right’, ‘outer’, ‘inner’, Default is inner join. The data frames must have same column names on which the merging happens.

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Round up, Round down and Round off in pyspark – (Ceil

Details: Round off to decimal places using round() function. round() Function takes up the column name and 2 as argument and rounds off the column to nearest two decimal place and the resultant values are stored in the separate column as shown below ##### round off to decimal places from pyspark.sql.functions import round, col df_states.select("*", round(col('hindex_score'),2)).show()

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Drop rows in pyspark with condition - DataScience Made Simple

Details: In order to drop rows in pyspark we will be using different functions in different circumstances. Drop rows with condition in pyspark are accomplished by dropping – NA rows, dropping duplicate rows and dropping rows by specific conditions in a where clause etc.

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Concatenate two columns in pyspark - DataScience Made Simple

Details: In order to concatenate two columns in pyspark we will be using concat() Function. We look at an example on how to join or concatenate two string columns in pyspark (two or more columns) and also string and numeric column with space or any separator.

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Remove leading, trailing, all space SAS- strip(), trim

Details: Remove Leading, Trailing, all space in SAS using strip(), trim() and compress() function in SAS. STRIP function SAS removes all leading & trailing blanks

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%in% operator in R - DataScience Made Simple

Details: %in% operator in R, is used to identify if an element belongs to a vector. Example of %in% operator in R and example of %in% operator for data frame.

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Concatenate two or more columns of dataframe in pandas

Details: Concatenating two columns of the dataframe in pandas can be easily achieved by using simple ‘+’ operator. Concatenate or join of two string column in pandas python is accomplished by cat() function. we can also concatenate or join numeric and string column.

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Generate row number in pandas python - DataScience Made Simple

Details: Generate row number in pandas and insert the column on our choice: In order to generate the row number of the dataframe in python pandas we will be using arange() function. insert() function inserts the respective column on our choice as shown below. in below example we have generated the row number and inserted the column to the location 0. i.e. as the first column

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Get day of month, day of year, day of week from date in

Details: First the date column on which day of the month value has to be found is converted to timestamp and passed to date_format() function. date_format() Function with column name and “d” (lower case d) as argument extracts day from date in pyspark and stored in the column name “D_O_M” as shown below.

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Convert character column to numeric in pandas python

Details: In order to Convert character column to numeric in pandas python we will be using to_numeric() function. astype() function converts or Typecasts string column to integer column in pandas.

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Substring in sas - extract first n & last n character

Details: Substring in sas – extract first n character. SUBSTR() Function takes up the column name as argument followed by start and length of string and calculates the substring. We have extracted first N character in SAS using SUBSTR() function as shown below /* substring in sas - extract first n character */ data emp_det1; set emp_det; state_new =SUBSTR(state,1,6); run;

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Drop column in pandas python - DataScience Made Simple

Details: Delete or drop column in pandas by column name using drop() function Let’s see an example of how to drop a column by name in python pandas # drop a column based on name df.drop('Age',axis=1)

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Find Duplicate Rows in Postgresql - DataScience Made Simple

Details: Method 2: Find Duplicate Rows in Postgresql with partition by. We have chosen duplicate row by partition by and order by as shown below. select distinct * from ExamScore where studentid in ( select studentid from ( select studentid, ROW_NUMBER() OVER(PARTITION BY studentid ORDER BY studentid asc) AS Row FROM ExamScore ) as foo where foo.Row > 1);

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Replace the missing value of column in R - DataScience

Details: To replace the missing value of the column in R we use different methods like replacing missing value with zero, with average and median etc. In this tutorial we will be looking on how to

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Count of Missing (NaN,Na) and null values in Pyspark

Details: Count of Missing (NaN,Na) and null values in pyspark can be accomplished using isnan() function and isNull() function respectively. isnan() function returns the count of missing values of column in pyspark – (nan, na) .

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Cumulative sum in pandas python - DataScience Made Simple

Details: Cumulative sum of a column in a pandas dataframe python Cumulative sum of a column in pandas is computed using cumsum() function and stored in the new column namely “cumulative_Tax” as shown below.

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Check and Count Missing values in pandas python

Details: isnull() is the function that is used to check missing values or null values in pandas python. isna() function is also used to get the count of missing values of column and row wise count of missing values.In this tutorial we will look at how to check and count Missing values in pandas python.

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Frequency table or cross table in pyspark – 2 way cross

Details: Frequency table in pyspark: Frequency table in pyspark can be calculated in roundabout way using group by count. The dataframe is grouped by column named “Item_group” and count of occurrence is calculated which in turn calculates the frequency of “Item_group”.

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Get first n rows & last n rows - head(), tail(), slice

Details: In This tutorial we will learn about head and tail function in R. head() function in R takes argument “n” and returns the first n rows of a dataframe or matrix, by default it returns first 6 rows. tail() function in R returns last n rows of a dataframe or matrix, by default it returns last 6 rows. we can also use slice() group of functions in dplyr package like slice_sample(),slice_head

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Groupby minimum in pandas dataframe python - DataScience

Details: Groupby minimum in pandas python can be accomplished by groupby() function. Groupby minimum of multiple column and single column in pandas is accomplished by multiple ways some among them are groupby() function and aggregate() function.

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Concatenate Two Columns in SAS - DataScience Made Simple

Details: Concatenate two Columns in SAS – With Removing Space . Concatenate two columns in SAS by removing space using CATS() Function. CATS() Function takes column names as argument and removes all the spaces.

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Case when in R using case_when() Dplyr - case_when in R

Details: Create new variable using case when statement in R: Case when with multiple condition. We will be creating additional variable Price_band using mutate function and case when statement.Price_band consist of “Medium”,”High” and “Low” based on price value. so the new variables are created using multiple conditions in the case_when() function of R.

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Extract First N and Last N characters in pyspark

Details: Extract Last N characters in pyspark – Last N character from right. Extract Last N character of column in pyspark is obtained using substr() function. by passing first argument as negative value as shown below ##### Extract Last N character from right in pyspark df = df_states.withColumn("last_n_char", df_states.state_name.substr(-2,2)) df.show()

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Remove Duplicate rows in R using Dplyr – distinct

Details: Distinct function in R is used to remove duplicate rows in R using Dplyr package. Dplyr package in R is provided with distinct() function which eliminate duplicates rows with single variable or with multiple variable.

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Quantile rank, decile rank & n tile rank in pyspark - Rank

Details: Quantile Rank of the column in pyspark. Quantile rank of the “price” column is calculated by passing argument 4 to ntile() function. we will be using partitionBy(), orderBy() on “price” column.

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