Trying to make scatter plots in subplots using for-loops

Question

I am trying to make subplots using for loop to go through my x variables in the dataframe. All plots would be a scatter plot.

X-variable: 'Protein', 'Fat', 'Sodium', 'Fiber', 'Carbo', 'Sugars' 
y-variable: 'Cal'

This is where I am stuck

plt.subplot(2, 3, 2)
for i in range(3):
     plt.scatter(i,sub['Cal'])

Answer 1

With this code:

import matplotlib.pyplot as plt
import pandas as pd

df = pd.read_csv('data.csv')
columns = list(df.columns)
columns.remove('Cal')

fig, ax = plt.subplots(1, len(columns), figsize = (20, 5))

for idx, col in enumerate(columns, 0):
    ax[idx].plot(df['Cal'], df[col], 'o')
    ax[idx].set_xlabel('Cal')
    ax[idx].set_title(col)

plt.show()

I get this subplot of scatter plots:

However, maybe it is a better choice to use a single scatterplot and use marker color in order to distinguish data type. See this code:

import matplotlib.pyplot as plt
import pandas as pd
import seaborn as sns
sns.set_style('darkgrid')

df = pd.read_csv('data.csv')
# df.drop(columns = ['Sodium'], inplace = True)  # <--- removes 'Sodium' column
table = df.melt('Cal', var_name = 'Type')

fig, ax = plt.subplots(1, 1, figsize = (10, 10))
sns.scatterplot(data = table,
                x = 'Cal',
                y = 'value',
                hue = 'Type',
                s = 200,
                alpha = 0.5)

plt.show()

that give this plot where all data are together:

The 'Sodium' values are different from others by far, so, if you remove this column with this line:

df.drop(columns = ['Sodium'], inplace = True)

you get a more readable plot: