<jupyter_start><jupyter_text>comparacion de tiempos<jupyter_code>import time
import pandas as pd
import numpy as np
import seaborn as sns
from matplotlib import pyplot as plt



%matplotlib inline
pd.set_option('display.max_columns', 250)
pd.set_option('display.max_rows', 200)
pd.options.display.float_format = '{:20,.1f}'.format
ruta = "./../data/"
fileomp = "valoresomp.csv"
filesec = "valoressec.csv"
omp = pd.read_csv(ruta + fileomp)
sec = pd.read_csv(ruta + filesec)
omp = omp.drop(['Unnamed: 13'], axis=1)
sec = sec.drop(['Unnamed: 13'], axis=1)
omp
sec.columns
omp.describe()
omp.columns
columnas = sec.columns
catidadElementos = len(sec)
d = {'sec': [], 'omp': []}
for i in columnas:
    d["sec"].append(sec[i].mean())
    d["omp"].append(omp[i].mean())
df = pd.DataFrame(data=d)

df.head()
indices = [i for i in range(3000)]
x = pd.Series(indices)
df["id"] = sec.columns.tolist()
df["indices"] = x
sns.set(style="darkgrid")
sns.lineplot(x="indices", y="sec",
             #style="event",
             data=df)
sns.lineplot(x="indices", y="omp",
             #style="event",
             data=df)
sns.lineplot(data=df[["omp","sec"]], palette="tab10", linewidth=2.5)
df.id
df["speed"] = df["sec"]/df["omp"]
df.sample(5)
sns.set(style="darkgrid")
sns.lineplot(x="indices", y="speed",
             #style="event",
             data=df)<jupyter_output><empty_output>
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