plots

Question 1

basic bar chart

Answer 1

plt.bar(x, y)
# x is list of categoryNames
# y is list of quantity to visualize

Question 2

basic pie chart

Answer 2

plt.pie(y, labels = x)
# x is list of categoryNames
# y is list of quantity to visualize

Question 3

Pareto chart assuming df.col1 on x axis, [‘col1_quantity’], and [‘cumpercentage’]

Answer 3

from matplotlib.ticker import PercentFormatter
fig, ax = plt.subplots(figsize=(20,10))
ax.bar(df[‘col1’], df[“col1_quantity”], color=”C0”)
ax2 = ax.twinx()
ax2.plot(df[‘col1’], df[“cumpercentage”], color=”C1”, marker=”D”, ms=7)
ax2.yaxis.set_major_formatter(PercentFormatter())
ax.tick_params(axis=”y”, colors=”C0”)
ax2.tick_params(axis=”y”, colors=”C1”)
plt.title(‘pareto chart’)
plt.show()

Question 4

histogram with relative frequency for an array

Answer 4

plt. hist(arr, bins=10, density=True)
plt. ylabel(‘Relative Frequency’)
plt. xticks(intervals)

Question 5

histogram with absolute frequency for an array

Answer 5

plt. figure(figsize = (20,10))
plt. hist(arr, bins=10)
plt. ylabel(‘Absolute Frequency’)
plt. xticks(intervals)

Question 6

create side by side bar chart for two level variables. Specify what you need to do with df first.
eg, col1 is gender, col2 is country, and col3 is the quantity to visualize

Answer 6

g = sns.catplot(x='col1', y='col3', hue='col2', data=df, kind='bar')
g.fig.set_size_inches(20,10)
# need to melt df first

Question 7

adjust seaboard settings

Answer 7

sns.set_context(“notebook”, rc={“font.size”:16,”axes.titlesize”:20,”axes.labelsize”:16})

Question 8

basic scatter plot for arr1 and arr2

Answer 8

plt. scatter(arr1, arr2)
plt. title(“arr1 vs arr2”)
plt. show()

Question 9

basic box plot for one array. Add optional argument to make it vertical

Answer 9

sns.boxplot(arr1, orient=’v’ )

Question 10

basic violin plot for one array

Answer 10

sns.violinplot(arr1)

Question 11

basic structure to create two subplots side by side

Answer 11

f, axes = plt.subplots(1, 2)

sns. boxplot(arr1, ax=axes[0] )
sns. boxplot(arr2, ax=axes[1])

Question 12

name the x-axis using appropriate font size

Answer 12

plt.xlabel(‘TEXT’, fontsize = 20)

Question 13

line graph with thickness of line, name of line, and color

Answer 13

plt.plot(x, yhat, lw=4, c=’orange’, label =’regression line’)

Question 14

imports to make plots in seaboard

Answer 14

import seaborn as sns

sns.set()

Question 15

scatter plot with regression line. independent variable is x1, dependent variable is yhat.

Answer 15

plt.scatter(x1,y)
fig = plt.plot(x1,yhat, lw=4, c=’orange’, label =’regression line’)
plt.show()