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fix: fix typos

pull/42/head
Badr Ghazlane 3 years ago
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a023af8571
  1. 2
      one_md_per_day_format/piscine/Week1/day1.md
  2. 2
      one_md_per_day_format/piscine/Week1/day2.md
  3. 4
      one_md_per_day_format/piscine/Week1/day5.md

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one_md_per_day_format/piscine/Week1/day1.md

@ -404,7 +404,7 @@ This can be done in three steps: Get the max, create a boolean mask that indicat
--- ---
## Exercise 9 Football tournament # Exercise 9 Football tournament
The goal of this exercise is to learn to use permutations, complex The goal of this exercise is to learn to use permutations, complex

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one_md_per_day_format/piscine/Week1/day2.md

@ -42,7 +42,7 @@ It contains ALL you need to know about Pandas.
- https://jakevdp.github.io/PythonDataScienceHandbook/03.04-missing-values.html - https://jakevdp.github.io/PythonDataScienceHandbook/03.04-missing-values.html
# Exercice 1 # Exercice 1 Your first DataFrame
The goal of this exercise is to learn to create basic Pandas objects. The goal of this exercise is to learn to create basic Pandas objects.

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one_md_per_day_format/piscine/Week1/day5.md

@ -32,7 +32,7 @@ Pandas website
- https://pandas.pydata.org/Pandas_Cheat_Sheet.pdf - https://pandas.pydata.org/Pandas_Cheat_Sheet.pdf
- https://www.learndatasci.com/tutorials/python-pandas-tutorial-complete-introduction-for-beginners/ - https://www.learndatasci.com/tutorials/python-pandas-tutorial-complete-introduction-for-beginners/
# Exercise 1 # Exercise 1 Series
The goal of this exercise is to learn to manipulate time series in Pandas. The goal of this exercise is to learn to manipulate time series in Pandas.
@ -80,7 +80,7 @@ The goal of this exercise is to learn to manipulate time series in Pandas.
If the `NaN` values have been dropped the solution is also accepted. The solution uses `rolling().mean()`. If the `NaN` values have been dropped the solution is also accepted. The solution uses `rolling().mean()`.
# Exercise 2 # Exercise 2 Financial data
The goal of this exercise is to learn to use Pandas on Time Series an on Financial data. The goal of this exercise is to learn to use Pandas on Time Series an on Financial data.

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