Python

Question 1

df[‘Column name’].map

Answer 1

apply a dictionary to a column to change it

Question 2

.astype()

Answer 2

change the type of data
use with dataframe:
df[‘Column’].astype(‘boolean’)

Question 3

.apply

Answer 3

use when calling a function on a specific column Ex:
def gender(x)…. etc

df[‘Gender’] = df[‘Gender].apply(gender)

Question 4

df.head()

Answer 4

calls the first couple rows of the dataframe

Question 5

df.info()

Answer 5

tells you about the null values and data types of the dataframe

Question 6

.sort_values()

Answer 6

allows you to sort a dataframe column

df.sort_values(by =’column’, ascending = False)

Question 7

Correlational values

Answer 7

0 - 0.25 = Very low
0.26 - 0.49 = Low
0.5 - 0.69 = Moderate
0.7 - 0.89 = High
0.90 -1.0 = Very High

this is looking at the r value (correlation coefficient)
these can also be negative

Question 8

what is the r squared value

Answer 8

r squared tells you how much of the variance in y is explained by x in a regression analysis

r squared is always positive and is a %

Question 9

what is a regression analysis (and what are the 2 main types)

Answer 9

regression analysis examines the relationship between variables to assist with prediction/forecasting

simple regression: one dependent and one independent variable

multiple regression: two or more independent variables with one dependent variable

Question 10

.rename()

df.rename(columns = {‘current name’ : ‘new name’}, inplace = True)

Answer 10

change the name of a column in a df

Question 11

what type of chart is best when comparing 2 categorical variables?

Answer 11

A. stacked bar chart (sns.countplot) - will show the composition of each category
B. grouped bar chart (sns.catplot) will show side by side comparison of categories
C. heatmap (though best for correlations)

Question 12

what is the syntax for countplot

Answer 12

sns.countplot( x = ‘category1’, hue = ‘category2’, data = df)

can do without the hue part if looking at one category only

Question 13

what are the two main types of data?

Answer 13

categorical and numerical

Question 14

what is the syntax of catplot? what is great about this tool?

Answer 14

sns.catplot( x = ‘category1’, hue = ‘category2’, kind = ‘count’, data = df)

the kind can be changed to many different plots including box, point, bar, strip (scatter), and swarm

Question 15

what is the best chart when looking at categorical data vs boolean?

Answer 15

A. stacked bar chart - shows the distribution/proportions
B. grouped bar chart - separate bars for each bool value

Question 16

what is the syntax to make a histogram

Answer 16

sns.histplot( x = ‘column’, bins = 10, data = df)

you can add hue and multiple = ‘stack’ to do a double histogram

Question 17

what are 2 ways to make a boxplot in seaborn?

Answer 17

sns.catplot(x = ‘values’, hue = ‘category’ , kind = ‘box’, data = df)
sns.boxplot(x = ‘category’, y = ‘values’, data = df

Question 18

how do you rotate or change the x axis in sns?

Answer 18

plt.xticks(rotation=45)