Making a line chart in plotnine¶

Organizing your data¶

When you're making a time series chart (which is mostly what a line chart will be), you need to make sure your x axis column is a datetime.

In [ ]:

import pandas as pd
from plotnine import *

df = pd.read_csv('lumber-prices.csv')
df.head(2)
import pandas as pd
from plotnine import *

df = pd.read_csv('lumber-prices.csv')
df.head(2)

In this dataset, we can use df.dtypes to see it's an object, which generally means a normal boring string.

In [2]:

df.dtypes
df.dtypes

Out[2]:

open     float64
high     float64
low      float64
close    float64
date      object
dtype: object

It's simple to convert the column to a datetime using pd.to_datetime.

In [3]:

df['date'] = pd.to_datetime(df.date)
df.head(2)
df['date'] = pd.to_datetime(df.date)
df.head(2)

Out[3]:

	open	high	low	close	date
0	407.0	424.7	377.0	424.7	1996-12-09
1	426.0	450.5	395.0	411.4	1997-01-02

Making your chart¶

Now you just use geom_line() after setting your date column as the x axis.

In [6]:

(
    ggplot(df)
    + aes(x='date', y='open')
    + geom_line()
)
(
    ggplot(df)
    + aes(x='date', y='open')
    + geom_line()
)

Out[6]:

<ggplot: (310604532)>

Adding points to a line chart¶

In [20]:

(
    ggplot(df)
    + aes(x='date', y='open')
    + geom_line()
    + geom_point(size=1)
)
(
    ggplot(df)
    + aes(x='date', y='open')
    + geom_line()
    + geom_point(size=1)
)

Out[20]:

<ggplot: (311520443)>

In [ ]: