<jupyter_start><jupyter_text>Example Notebook 7 Exercise Create a Notebook (using Pandas) where you, starting from a dataset of your choice, analise it, cleaning it if necessary and finally add some visualizations with matPlotLib.<jupyter_code># call libraries
import numpy as np
import pandas as pd
import matplotlib.pyplot as plt<jupyter_output><empty_output><jupyter_text>`The dataset can be downloaded from internet, read from a excel file or criated from scratch from a python dictionary, as below:`<jupyter_code># create a data dictionary
data = {
  "calories": [420, 380, 390],
  "duration": [50, 40, 45]
}<jupyter_output><empty_output><jupyter_text>`Try see from your data types, shapes and statistical info`<jupyter_code># confirm data type
type(data)
# load data into a DataFrame object:
df = pd.DataFrame(data)
type(df)
# see data shape
df.shape
df.head()
df.info()
df.describe()<jupyter_output><empty_output><jupyter_text>`Create some nice plots (vizualization) from your data`<jupyter_code>plt.plot(df.calories)
plt.title("Calories");<jupyter_output><empty_output>
StarcoderdataJupyterStructuredCleanDedup