What does the Reshape command do in Stata?

What does the Reshape command do in Stata?

reshape converts data from wide to long form and vice versa.

Why do we need to reshape the data?

In this post, I use a few examples to illustrate the two common data forms: wide form and long form, and how to convert datasets between the two forms – here we call it “reshape” data. Reshaping is often needed when you work with datasets that contain variables with some kinds of sequences, say, time-series data.

What does reshape long do in Stata?

long tells reshape that we want to go from wide to long. faminc tells Stata that the stem of the variable to be converted from wide to long is faminc. i(famid) option tells reshape that famid is the unique identifier for records in their wide format.

What is the difference between long and wide format data?

A dataset can be written in two different formats: wide and long. A wide format contains values that do not repeat in the first column. A long format contains values that do repeat in the first column. Notice that in the wide dataset, each value in the first column is unique.

What is reshape data?

Data Reshaping in R is about changing the way data is organized into rows and columns. Most of the time data processing in R is done by taking the input data as a data frame.

Why do we do reshape (- 1 1?

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. However, as you saw above, there’s an easier way to make x a 2D object.

Is co2 tidy Why or why not?

co2 is not tidy: it is a matrix instead of a data frame. co2 is not tidy: to be tidy we would have to wrangle it to have three columns (year, month and value), then each co2 observation would have a row.

Is long or wide better?

If you are going to categorize that data in some way and add additional information then wide will usually be more efficient storage wise but long will generally be handled more efficiently.

How do you reshape data from long to wide in R?

Reshape from long to wide in R is also achieved using spread() and cast() function.

1. Reshape from wide to long using reshape(), gather() and melt() function.
2. Reshape from long to wide using reshape(), spread() and dcast() function.

Why is Destring not working Stata?

Stata: Data Analysis and Statistical Software (In some ways, the original destring command violated Stata’s philosophy because it was too easy to change much of your dataset without the safeguard of having to spell out some injunction such as , replace.)

What is reshape order?

The order keyword gives the index ordering both for fetching the values from a, and then placing the values into the output array. For example, let’s say you have an array: >>> a = np. arange(6). reshape((3, 2)) >>> a array([[0, 1], [2, 3], [4, 5]])

Is CO2 a problem?

Carbon dioxide is a problem because it acts as a “greenhouse gas.” Due to its molecular structure, CO2 absorbs and emits infrared radiation, warming the Earth’s surface and the lower levels of the atmosphere.

How do I tidy data?

To tidy the data, the basic approach is:

1. Identify what the observations and variables are.
2. Fix the dataset so the observations are in rows and variables are in columns. Typically there is one of two problems in the data. One variable might be spread across multiple columns.

When do I need reshaping in Stata?

Reshaping is often needed when you work with datasets that contain variables with some kinds of sequences, say, time-series data. It is fairly easy to transform data between wide and long forms in Stata using the -reshape- command, however you’ll want to be careful when you convert a dataset from one form…

What are some examples of reshaping data?

These examples take wide data files and reshape them into long form. These show common examples of reshaping data, but do not exhaustively demonstrate the different kinds of data reshaping that you could encounter. Consider the family income data file below. This is called a wide format since the years of data are wide.

What is the difference between reshape wide and reshape long?

Let’s look at the wide format and contrast it with the long format. The reshape wide command puts the data back into wide format. We then list out the wide file. The reshape long command puts the data back into long format. We then list out the long file. Now let’s look at the pieces of the original reshape command.

Can I reshape a wide data file to be long?

Let’s look at the wide data, and then the data reshaped to be long. It also is possible to reshape a wide data file to be long when there are character suffixes. Look at the dadmomw file below.