---
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  text_representation:
    extension: .md
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  display_name: Python 3 (ipykernel)
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  title: time series
---

# timeseries

```{code-cell} ipython3
import numpy as np
import pandas as pd
import matplotlib.pyplot as plt
import seaborn as sns
```

## the data

```{code-cell} ipython3
URL = "http://www-sop.inria.fr/members/Arnaud.Legout/formationPython/Exos/covid-hospit-incid-reg-2021-06-08-19h09.csv"

# we extract only 3 columns
try:
    hos = pd.read_csv(URL)
except UnicodeDecodeError as e:
    print(f"decoding exception: {e}")
```

There is a decoding error, wich means the csv is not encoded  in utf-8. This is unfortunate and the real encoding is not specified on the site. Instead of making trial and fail attempts, we will use `chardet` to detect the correct encoding.

```{code-cell} ipython3
%pip install chardet

import chardet
import urllib.request

rawdata = urllib.request.urlopen(URL).read()
chardet.detect(rawdata)
```

The encoding seems to be `ISO-8859-1` with 0.73% confidence. Let's try it

```{code-cell} ipython3
try:
    hos = pd.read_csv(URL, encoding="ISO-8859-1")
except UnicodeDecodeError as e:
    print(f"decoding exception: {e}")

hos.head(2)
```

## It works, but the csv file was not correctly parsed because the separator is a `;`

```{code-cell} ipython3
# your code
hos = ...
```

## What is the dtype of each columns?

```{code-cell} ipython3
:lines_to_next_cell: 2

# your code
```

## Convert

`jour` and `nomReg` are object. It will be better to have `jour` as a DatetimeIndex and `nomReg` as a category.

```{code-cell} ipython3
# your code
```

## Compute the sum of `incid_rea` weekly and plot using a bar plot (hint: use `resample`)

```{code-cell} ipython3
# your code
```

## It works, but the x-axis date representation is messy.

It is an issue specific to the bar plot in pandas. With a regular line plot, the x-axis is automatically optimized.

Let us see the solution together (found on stackoverflow...)

```{code-cell} ipython3
:tags: [raises-exception]

resampled_hos.plot()
```

To solve the issue with bar plots, we need to work with matplotlib

```{code-cell} ipython3
:tags: [raises-exception]
:lines_to_next_cell: 2

from matplotlib.dates import AutoDateLocator, ConciseDateFormatter, AutoDateFormatter

locator = AutoDateLocator()
# ConciseDateFormatter will infer the most compact date representation
formatter = ConciseDateFormatter(locator)

# AutoDaAutoDateFormatter gives another representation
# formatter = AutoDateFormatter(locator)
ax=plt.gca()
ax.xaxis.set_major_locator(locator)
ax.xaxis.set_major_formatter(formatter)

resampled_hos = hos.resample('w')['incid_rea'].sum()
# we need to plot directly with matplotlib otherwise dates representation will not be taken into account.
ax.bar(resampled_hos.index, resampled_hos, width=5)

# To uncomment if we use the AutoAutoDateFormatter
# fig = plt.gcf()
# fig.autofmt_xdate()
```

## Rolling

Compute now a rolling average on 14 days of `incid_rea` (hint: use `rolling`) and plot it using a line plot.

```{code-cell} ipython3
# your code
```

***