reshape_for_binomials: Reshape the dataframe to make it easier to carry out binomial...
In GenderInfer: This is a Collection of Functions to Analyse Gender Differences

Description Usage Arguments Value Examples

reshape dataframe from long format to wide format.

1	reshape_for_binomials(data_df, gender_col, level)

`data_df,`	dataframe containing the columns gender and counts
`gender_col,`	the name of the column containing the gender values.
`level,`	variable to compare for the baseline.

The output is a dataframe containing more columns than the input one, such as:

level : the variable used to perform the binomials total_for_level: the total amount of each gender including unknowns total_female_male: the total amount of male and female female_percentage: the percentage of female in the total_female_male male_percentage: the percentage of male in the total_female_male

authors_df <- assign_gender(data_df = authors, first_name_col = "first_name")
female_count <- dplyr::count(authors_df, gender)

## create a new data frame to be used for the binomial calculation.
df_gender <- reshape_for_binomials(data = female_count, gender_col = "gender",
                                  level = 2020)