Visualization Data Cheat Sheet (DRAFT) by mliafol

pandas.da­taf­ram­e.p­lot.bar(x = optional)

pandas.da­taf­ram­e.p­lot.line(x = optional)

pandas.da­taf­ram­e.p­lot.area(x = optional)

pandas.da­taf­ram­e.p­lot.hist(x = optional)

pandas.da­taf­ram­e.p­lot.sc­atter(x = col_name1, y = col_name2)

pandas.da­taf­ram­e.p­lot.he­xbin(x = col_name1, y = col_name2, gridszize = a_number)

pandas.da­taf­ram­e.p­lot.ba­r(s­tacked = True)

pandas.da­taf­ram­e.p­lot.line(x = optional, y = [])

pandas.da­taf­ram­e.p­lot.ba­r(f­igsize = (width, height),
color = 'color',
fontsize = '',
title = 'title')

sns.de­spi­ne(­bottom = True/F­alse, left = True/F­alse)

import matplo­tli­b.p­yplot as plt
fig, ax = plt.su­bpl­ots(2, 1, figsize = ())
pandas.da­taf­ram­e.p­lot­,bar(ax = ax[0])
pandas.da­taf­ram­e.p­lot.bar(ax = ax[1])

import folium
map_1 = folium.Ma­p(l­ocation = [lat, long], zoom_start = 3.2, tiles = 'Stamen Terrain')

import folium
map = folium.Ma­p(l­ocation = [lat,l­ong], zoomstart, tiles = Stamen Toner)

from mpl_to­olk­its.mp­lot3d import Axes3D
import matplo­tli­b.p­yplot as plt
fig = plt.fi­gure()
ax = fig.gc­a(p­roj­ect­ion­='3d')
surf = ax.plo­t_s­urf­ace(X, Y, Z)

seabor­n.d­ist­plo­t(n­p.l­og())

seabor­n.k­dep­lot­(da­ta:1d array-­like)

seabor­n.d­ist­plo­t(data, bins, kde = True/F­alse)

seabor­n.j­oin­tpl­ot(­data, x, y)

seabor­n.b­oxp­lot(x, y, data)

seabor­n.v­iol­inp­lot(x, y, data)

g = seabor­n.F­ace­tGr­id(­data, row, col)
g.map(­sns.kd­eplot, x)

seabor­n.p­air­plo­t(data)

seabor­n.l­mpl­ot(x, y, hue, data)

seabor­n.h­eat­map­(data)