Using this dataframe,
```python
df = pd.DataFrame({
    'name':['john','mary','peter','jeff','bill','lisa','jose'],
    'age':[23,78,22,19,45,33,20],
    'gender':['M','F','M','M','M','F','M'],
    'state':['california','dc','california','dc','california','texas','texas'],
    'num_children':[2,0,0,3,2,1,4],
    'num_pets':[5,1,0,5,2,2,3]
})
```
To create a scatterplot of two columns,
```python
df.plot(kind='scatter',x='num_children',y='num_pets',color='red')
plt.show()
```

University of Michigan - Ann Arbor

- Scatter
- Bar Chart
- Line Plot
- Histogram
- Grouped Bar Chart

Examples of Matplotlib Plots

https://queirozf.com/entries/pandas-dataframe-plot-examples-with-matplotlib-pyplot

Matplotlib and Pandas Examples

https://matplotlib.org/stable/contents.html#

Matplotlib Documentation

Matplotlib Scatter Plot

Using this dataframe,
```python
df = pd.DataFrame({
    'name':['john','mary','peter','jeff','bill','lisa','jose'],
    'age':[23,78,22,19,45,33,20],
    'gender':['M','F','M','M','M','F','M'],
    'state':['california','dc','california','dc','california','texas','texas'],
    'num_children':[2,0,0,3,2,1,4],
    'num_pets':[5,1,0,5,2,2,3]
})
```
To create a bar chart,
```python
df.plot(kind='bar',x='name',y='age')
```

Matplotlib Bar Chart

Using this dataframe,
```python
df = pd.DataFrame({
    'name':['john','mary','peter','jeff','bill','lisa','jose'],
    'age':[23,78,22,19,45,33,20],
    'gender':['M','F','M','M','M','F','M'],
    'state':['california','dc','california','dc','california','texas','texas'],
    'num_children':[2,0,0,3,2,1,4],
    'num_pets':[5,1,0,5,2,2,3]
})
```
To create a line plot,
```python
#gca stands for get current axis
ax = plt.gca()

#the ax parameter lets you use the same axis for multiple lines
df.plot(kind='line',x='name',y='num_children',ax=ax)
df.plot(kind='line',x='name',y='num_pets', color='red', ax=ax)

plt.show()
```

Matplotlib Line Plot

Using this dataframe,
```python
df = pd.DataFrame({
    'name':['john','mary','peter','jeff','bill','lisa','jose'],
    'age':[23,78,22,19,45,33,20],
    'gender':['M','F','M','M','M','F','M'],
    'state':['california','dc','california','dc','california','texas','texas'],
    'num_children':[2,0,0,3,2,1,4],
    'num_pets':[5,1,0,5,2,2,3]
})
```
To create a histogram of the age column,
```python
#bins sets range for bins
#rwidth is relative width of bars
df[['age']].plot(kind='hist',bins=[0,20,40,60,80,100],rwidth=0.8)
plt.show()
```


Matplotlib Histogram

Using this dataframe,
```python
df = pd.DataFrame({
    'name':['john','mary','peter','jeff','bill','lisa','jose'],
    'age':[23,78,22,19,45,33,20],
    'gender':['M','F','M','M','M','F','M'],
    'state':['california','dc','california','dc','california','texas','texas'],
    'num_children':[2,0,0,3,2,1,4],
    'num_pets':[5,1,0,5,2,2,3]
})
```
To create a grouped bar chart,
```python
#Grouped by state and returns number of unique names for each state
df.groupby('state')['name'].nunique().plot(kind='bar')
plt.show()
```

Learn Before

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