# How to create a dataframe with different number of rows

### How do I count the number of rows in a data frame?

**Use pandas.**

**DataFrame**.**index to**

**count**the**number of rows**- df = pd.
**DataFrame**({“Letters”: [“a”, “b”, “c”], “**Numbers**“: [1, 2, 3]}) - print(df)
- index = df. index.
- number_of_rows = len(index) find length of index.
- print(number_of_rows)

### How do I merge datasets with different rows in R?

Generally speaking, you can use

**R**to**combine different**sets of data in three ways: By adding columns: If the two sets of data have an equal set of**rows**, and the order of the**rows**is identical, then adding columns makes sense. Your options for doing this are data. frame or cbind().### How do I combine two data frames with different columns in R?

**There are three main techniques we are going to look at:**

- cbind() –
**combining**the**columns**of**two data frames**side-by-side. - rbind() – stacking
**two data frames**on top of each other, appending one to the other. **merge**() –**joining two data frames**using a common**column**.

### How do I combine data frames in R studio?

**Merge**Two**Data Frames**- Description.
**Merge**two**data frames**by common columns or row names. - Usage.
**merge**(x, y, by, by.x, by.y, sort = TRUE) - Arguments. x, y.
- Details. By default the
**data frames**are**merged**on the columns with names they both have, but separate specifcations of the columns can be given by by. - Value. A
**data frame**. - See Also.
- Examples.

### How do I combine two variables in R?

You can

**merge**columns, by adding new**variables**; or you can**merge**rows, by adding observations. To add columns use the function**merge**() which requires that datasets you will**merge**to have a common**variable**. In case that datasets doesn’t have a common**variable**use the function cbind .### How do I replace NAs with 0 in R?

To

**replace NA with 0**in an**R**data frame, use is.**na**() function and then select all those values with**NA**and assign them to**0**. myDataframe is the data frame in which you would like**replace**all**NAs with 0**.### Is NaN an R?

Inf and -Inf are positive and negative infinity whereas

**NaN**means ‘Not a Number’. (These apply to numeric values and real and imaginary parts of complex values but not to values of integer vectors.) Inf and**NaN**are reserved words in the**R**language.### How do I convert character to numeric in R?

To

**convert**a**character**vector to a**numeric**vector, use as.**numeric**(). It is important to do this before using the vector in any statistical functions, since the default behavior in**R**is to**convert character**vectors to factors.### How do I replace missing values in R?

**How to Replace Missing Values**(**NA) in R**:**na**.**omit &**

**na**.**rm**

- mutate()
- Exclude
**Missing Values**(**NA**) - Impute
**Missing Values**(**NA**) with the Mean and Median.

### How do I ignore missing values in R?

We can exclude

**missing values**in a couple different ways. First, if we want to exclude**missing values**from mathematical operations use the**na**. rm = TRUE argument. If you do not exclude these**values**most functions will return an**NA**.### How do you fill missing values in R?

**How to replace NA values**in columns of an**R**data frame form the**mean**of that column?- df$x[is.
**na**(df$x)]<-**mean**(df$x,**na**. rm=TRUE) df. - df$y[is.
**na**(df$y)]<-**mean**(df$y,**na**. rm=TRUE) df. - df$z[is.
**na**(df$z)]<-**mean**(df$z,**na**. rm=TRUE) df.

### How do I find missing values in a DataFrame in R?

In

**R**the**missing values**are coded by the symbol**NA**. To**identify**missings in your dataset the function is is.**na**() . When you import dataset from other statistical applications the**missing values**might be coded with a number, for example 99 . In order to let**R**know that is a**missing value**you need to recode it.### How do you omit rows in R?

**Delete Rows**from

**R**Data Frame

You cannot actually **delete** a **row**, but you can access a data frame without some **rows** specified by negative index. This process is also called subsetting in **R** language. A Big Note: You should provide a comma after the negative index vector -c().

### How does Sapply work in R?

**sapply**() function takes list, vector or data frame as input and gives output in vector or matrix. It is useful for operations on list objects and returns a list object of same length of original set.

**sapply**() function

**does**the same job as

**lapply**() function but returns a vector.

### What percentage of missing data is acceptable?

Statistical guidance articles have stated that bias is likely in analyses with more than 10% missingness and that if more than 40%

**data**are**missing**in important variables then results should only be considered as hypothesis generating [18], [19].### How do I know if my data is missing at random?

**If**there is no significant difference between our primary variable of interest and the

**missing**and non-

**missing**values we have evidence that our

**data is missing at random**.

### Should I remove missing data?

It’s most useful when the percentage of

**missing data**is low. If the portion of**missing data**is too high, the results lack natural variation that**could**result in an effective model. The other option is to**remove data**. When dealing with**data**that is**missing**at random, related**data can**be deleted to reduce bias.### How do you find the missing value of a data set?

Checking for

**missing values**using isnull() and notnull() In order to **check missing values** in Pandas DataFrame, we use a function isnull() and notnull() . Both function help in checking whether a **value** is NaN or not. These function can also be used in Pandas Series in order to **find null values** in a series.

### What is a useful strategy to use when you are missing data in Excel?

**Some techniques for imputing**

**values**for**missing data**include:- Substituting the
**missing data**with another observation which is considered similar, either taken from another sample or from a previous study. **Using**the mean of all the non-**missing data**elements for that variable.**Using**regression techniques.

### How do you create a missing value in Excel?

**HOW TO FILL THE**

**MISSING VALUES IN EXCEL**SPREADSHEETS- Step 2: Now press Ctrl+G to open the ‘Got to’ dialog box.
- Click in the ‘Special’ button. (or)
- Step 4: Click the Blanks option and click OK.
- Step 5: Press F2 button in the keyboard (or) click the formula bar.
- Now you can enter the
**value**you want in the space provided. - Now you are done!

### How can you impute data present in a list of mobile numbers?

**Contents**

- Independent and Dependent Variables.
- 4 Ways to Deal with Missing Values. Listwise Deletion. Mean/Median/Mode
**Imputation**. Mean. Median. Mode. Last Observation Carried Forward (LOCF) Resurveying.