Coloured multi line chart with x-axis df.index?

[brezn1]

I guess its more a question than a feature request:

The data:

data1 = np.random.normal(0, 0.1, 1000)
data2 = np.random.normal(1, 0.4, 1000) + np.linspace(0, 1, 1000)
data3 = 2 + np.random.random(1000) * np.linspace(1, 5, 1000)
data4 = np.random.normal(3, 0.2, 1000) + 0.3 * np.sin(np.linspace(0, 20, 1000))

data = np.vstack([data1, data2, data3, data4]).transpose()

df = pd.DataFrame(data, columns=['data1', 'data2', 'data3', 'data4'])
df.head()

	data1	data2	data3	data4
0	-0.216306	0.769149	2.614268	3.022906
1	0.091122	2.037440	2.135203	3.127771
2	0.076178	0.983550	2.278488	2.970982
3	-0.023629	1.859270	2.005969	2.986248
4	0.076633	1.453625	2.120465	2.805301

now, plotting in Pandas is done like that:

df.plot(title='Line plot')

The unnamed dataframe-index is automatically used for the x-axis.

Question: Would it be possible to have a similar behaviour in chartify?

ch = chartify.Chart(blank_labels=True, x_axis_type='linear')
ch.plot.line(
   # Data must be sorted by x column
   data_frame=df,
   x_column= "index", # internally do a df.index.get_values() or just the fixed term "index"? 
   y_column="value",
   color_column="variable")

According to the tidy data paradigm, this solution works. But it seeems like a lot of extra miles to get the same result like in pandas:

melted_data = pd.melt(df.reset_index(), 
                      id_vars='index',  
                      value_vars=df.columns)

ch = chartify.Chart(blank_labels=True, x_axis_type='linear')
ch.plot.line(
    data_frame=melted_data,
    x_column= "index",   
    y_column="value",
    color_column="variable")

I have the feeling i won't be the last person to ask exactly this queston about grabbing the index-data. ;-)

[cphalpert]

Agree it would be helpful to have plotting methods straight from pivoted data for convenience.

In addition to #9 we could probably also solve for line, scatter, text, etc. Some of the functionality would have to be limited -- e.g. it would be hard to provide control over both scatter size and x-y coordinates from pivoted data.

[brezn1]

Thanks, sounds good.

I have seen this problem across other visualization libs, too. Some do it in the re-index/melt manner like chartify. Plotnine does allow it that way: x_column= "df.index"