Shape columns record easily

Aug 6th, 2022
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How to shape columns record

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[Music] welcome to Excel magic trick number 15 31 and this video we got to see how to use dynamic arrays to convert a column of records into a proper data set now the dynamic arrays and this new excel calculation engine are only in office 365 now this task of going from a column of records to a proper data set can be done many ways I have other videos both in power query and with formulas of how to do this but if we go over to sheet 1531 this trick comes from the power query and dynamic array formula master Bill scissors now heres our task we have records and for some crazy reason theyre listed in a column these field names should really be listed across the top and the first row and then this is in one row as a single record and then the next record and so on now actually with these dynamic array formulas its going to be surprisingly easy so although we can do this with other formula methods and power query this ones gonna give us a run for our money now I first need to take the

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In Pandas data reshaping means the transformation of the structure of a table or vector (i.e. DataFrame or Series) to make it suitable for further analysis. Some of Pandas reshaping capabilities do not readily exist in other environments (e.g. SQL or bare bone R) and can be tricky for a beginner.
melt() function is used to reshape a DataFrame from a wide to a long format. It is useful to get a DataFrame where one or more columns are identifier variables, and the other columns are unpivoted to the row axis leaving only two non-identifier columns named variable and value by default.
Reshape your data either using array. reshape(-1, 1) if your data has a single feature or array. reshape(1, -1) if it contains a single sample. We could change our Series into a NumPy array and then reshape it to have two dimensions.
To reshape the dataframe from long to wide in Pandas, we can use Pandas pd. pivot() method. columns : Column to use to make new frames columns (e.g., Year Month). values : Column(s) to use for populating new frames values (e.g., Avg.
Understanding DataFrame Objects As youve seen with the nba dataset, which features 23 columns, the pandas Python library has more to offer with its DataFrame . This data structure is a sequence of Series objects that share the same index.
The process of stacking pivots a level of column labels to the row index. Unstacking performs the opposite, pivoting a level of the row index into the column index.
Count the number of rows and columns of Dataframe using len(df. axes[]) function. Lets take an example of a Dataframe that consists of data on exam results of students. To get the number of rows, and columns we can use len(df.

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