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Apprendre Superficial Analysis | Analyzing Data
Analyzing and Visualizing Real-World Data
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Contenu du cours

Analyzing and Visualizing Real-World Data

Analyzing and Visualizing Real-World Data

1. Preprocessing Data: Part I
2. Preprocessing Data: Part II
3. Analyzing Data
4. Visualizing Data

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Superficial Analysis

Welcome to the third section of the course! Here, you will use the pandas library to analyze data by answering specific questions.

Let's start with some basic information. We are going to analyze and visualize data on store sales. First, we need to determine how many stores we are working with. We can use the .describe() method of pandas to show the main descriptive statistics on numerical columns. Also, we can use the .unique() method of pandas to get only unique values of a certain column.

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# Loading the library import pandas as pd # Reading the data df = pd.read_csv('https://codefinity-content-media.s3.eu-west-1.amazonaws.com/72be5dde-f3e6-4c40-8881-e1d97ae31287/shops_data3.csv') df['Date'] = pd.to_datetime(df['Date'], dayfirst = True) # Inspecting the data print(df.describe()) print(df.Store.unique())
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For the following question, feel free to edit the code above if necessary.

What is the number of unique stores in the `df` dataframe?

What is the number of unique stores in the df dataframe?

Sélectionnez la réponse correcte

Tout était clair ?

Comment pouvons-nous l'améliorer ?

Merci pour vos commentaires !

Section 3. Chapitre 1
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