import matplotlib.pyplot as plt
import pandas as pd
import seaborn as sns
# Omitir warnings
import warnings
warnings.filterwarnings('ignore')
# tamaño de figura
fig = plt.figure(figsize=(12, 8))
# Lectura de csv
df = pd.read_csv('https://vincentarelbundock.github.io/Rdatasets/csv/datasets/mtcars.csv')
# Grafico
ax = sns.regplot(x="wt", y="mpg", data=df)
ax.set(xlabel='MPG', ylabel='WT')
plt.title('Peso vs mpg')

import pandas as pd
import seaborn as sns
df = pd.read_csv('https://raw.githubusercontent.com/marsja/jupyter/master/flanks.csv', 
                 index_col=0)
# Grafico
fig = plt.figure(figsize=(12, 8))
for condition in df.TrialType.unique():
    cond_data = df[(df.TrialType == condition)]
    ax = sns.distplot(cond_data.RT, kde=False, label=condition)
ax.set(xlabel='Tiempo de respuesta', ylabel='Frecuencia')
ax.legend()
ax.set_title('Histogramas Tiempo de respuesta')

import pandas as pd
import seaborn as sns
# Leer el archivo
df = pd.read_csv('https://vincentarelbundock.github.io/Rdatasets/csv/datasets/mtcars.csv', index_col=0)
# Hacer la agrupacion
df_grpd = df.groupby("cyl").count().reset_index()
# Grafico
fig = plt.figure(figsize=(12, 8))
sns.barplot(x="cyl", y="mpg", data=df_grpd)
ax.set(xlabel='Cylinders', ylabel='Number of Cars for Each Cylinder')

import pandas as pd
import seaborn as sns

df = pd.read_csv("https://raw.githubusercontent.com/rfordatascience/tidytuesday/master/data/2019/2019-02-26/full_trains.csv")

plt.figure(figsize=(12, 8))
sns.lineplot(x="month", y="total_num_trips", hue="departure_station", 
             ci=None, data=df[df.departure_station.str.contains('PARIS')])
plt.xlabel('Mes')
plt.ylabel('Numer de viajes')
plt.title('Viajes por mes')

import pandas as pd
import seaborn as sns

df = pd.read_csv('https://vincentarelbundock.github.io/Rdatasets/csv/datasets/mtcars.csv', index_col=0)

fig = plt.figure(figsize=(12, 8))
sns.boxplot(x="vs", y='wt', data=df)
plt.title('Vs vs WT')

!pip install ptitprince

import pandas as pd
import ptitprince as pt

df = pd.read_csv('https://vincentarelbundock.github.io/Rdatasets/csv/datasets/iris.csv')

ax = pt.RainCloud(x = 'Species', y = 'Sepal.Length', 
                  data = df, 
                  width_viol = .8,
                  width_box = .4,
                  orient = 'h',
                  move = .0)