fixed_df = pd.read_csv('bikes.csv', sep=';', encoding='latin1', parse_dates=['Date'], dayfirst=True, index_col='Date')
@@ -215,12 +215,101 @@ 1.1 Reading data from a CSV file
+1.2 Selecting a column
+
+When you read a CSV, you get a kind of object called a DataFrame, which is made up of rows and columns. You get columns out of a DataFrame the same way you get elements out of a dictionary.
+
+Here’s an example:
+
+print fixed_df['Berri 1']
+
+
+Output:
+
+Date
+2012-01-01 35
+2012-01-02 83
+2012-01-03 135
+2012-01-04 144
+2012-01-05 197
+2012-01-06 146
+2012-01-07 98
+2012-01-08 95
+2012-01-09 244
+2012-01-10 397
+2012-01-11 273
+2012-01-12 157
+2012-01-13 75
+2012-01-14 32
+2012-01-15 54
+...
+2012-10-22 3650
+2012-10-23 4177
+2012-10-24 3744
+2012-10-25 3735
+2012-10-26 4290
+2012-10-27 1857
+2012-10-28 1310
+2012-10-29 2919
+2012-10-30 2887
+2012-10-31 2634
+2012-11-01 2405
+2012-11-02 1582
+2012-11-03 844
+2012-11-04 966
+2012-11-05 2247
+Name: Berri 1, Length: 310, dtype: int64
+
+
+1.3 Plotting a column
+
+Just add .plot() to the end! How could it be easier? =)
+
+We can see that, unsurprisingly, not many people are biking in January, February, and March.
+
+import pandas as pd
+import matplotlib.pyplot as plt
+
+fixed_df = pd.read_csv('bikes.csv', sep=';', encoding='latin1', parse_dates=['Date'], dayfirst=True, index_col='Date')
+fixed_df['Berri 1'].plot()
+plt.show()
+
+
+Output:
+
+
+
+We can also plot all the columns just as easily. We’ll make it a little bigger, too. You can see that it’s more squished together, but all the bike paths behave basically the same – if it’s a bad day for cyclists, it’s a bad day everywhere.
+
+fixed_df.plot(figsize=(15, 10))
+plt.show()
+
+
+Output:
+
+
+
+
+
+1.4 Putting all that together
+
+Here’s the code we needed to write do draw that graph, all together:
+
+df = pd.read_csv('bikes.csv', sep=';', encoding='latin1', parse_dates=['Date'], dayfirst=True, index_col='Date')
+df['Berri 1'].plot()
+
+
+Output:
+
+
+
+
- Last revision: May 10, 2017
+ Last revision: May 11, 2017
diff --git a/sitemap.xml b/sitemap.xml
index 8d3b5f81..5b6364f0 100644
--- a/sitemap.xml
+++ b/sitemap.xml
@@ -3,12 +3,12 @@
http://tutswiki.com/
- 2017-05-10T00:00:00+00:00
+ 2017-05-11T00:00:00+00:00
http://tutswiki.com/pandas-cookbook/chapter1
- 2017-05-10T00:00:00+00:00
+ 2017-05-11T00:00:00+00:00
\ No newline at end of file
diff --git a/tutorials/index.xml b/tutorials/index.xml
index 24349474..d3157abb 100644
--- a/tutorials/index.xml
+++ b/tutorials/index.xml
@@ -5,13 +5,13 @@
http://tutswiki.com/tutorials/index.xml
Recent content in Tutorials-rsses on
Hugo -- gohugo.io
- Wed, 10 May 2017 00:00:00 +0000
+ Thu, 11 May 2017 00:00:00 +0000
-
Chapter 1 - Reading from a CSV
http://tutswiki.com/pandas-cookbook/chapter1
- Wed, 10 May 2017 00:00:00 +0000
+ Thu, 11 May 2017 00:00:00 +0000
http://tutswiki.com/pandas-cookbook/chapter1
@@ -42,11 +42,11 @@ print broken_df[:3]
<p>You’ll notice that this is totally broken! read_csv has a bunch of options that will let us fix that, though. Here we’ll</p>
<ul>
-<li>Change the column separator to a ;</li>
-<li>Set the encoding to ‘<em>latin1</em>’ (the default is ‘<em>utf8</em>’)</li>
-<li>Parse the dates in the ‘Date’ column</li>
+<li>Change the column separator to a <code>;</code></li>
+<li>Set the encoding to <code>'_latin1_'</code> (the default is <code>'_utf8_'</code>)</li>
+<li>Parse the dates in the <code>'Date'</code> column</li>
<li>Tell it that our dates have the date first instead of the month first</li>
-<li>Set the index to be the ‘Date’ column</li>
+<li>Set the index to be the <code>'Date'</code> column</li>
</ul>
<pre><code class="language-python">fixed_df = pd.read_csv('bikes.csv', sep=';', encoding='latin1', parse_dates=['Date'], dayfirst=True, index_col='Date')
@@ -112,6 +112,95 @@ print fixed_df[:3]
</tr>
</tbody>
</table>
+
+<h2 id="1-2-selecting-a-column">1.2 Selecting a column</h2>
+
+<p>When you read a CSV, you get a kind of object called a <a href="http://pandas.pydata.org/pandas-docs/stable/generated/pandas.DataFrame.html">DataFrame</a>, which is made up of rows and columns. You get columns out of a DataFrame the same way you get elements out of a dictionary.</p>
+
+<p>Here’s an example:</p>
+
+<pre><code class="language-python">print fixed_df['Berri 1']
+</code></pre>
+
+<p>Output:</p>
+
+<pre><code class="language-bash">Date
+2012-01-01 35
+2012-01-02 83
+2012-01-03 135
+2012-01-04 144
+2012-01-05 197
+2012-01-06 146
+2012-01-07 98
+2012-01-08 95
+2012-01-09 244
+2012-01-10 397
+2012-01-11 273
+2012-01-12 157
+2012-01-13 75
+2012-01-14 32
+2012-01-15 54
+...
+2012-10-22 3650
+2012-10-23 4177
+2012-10-24 3744
+2012-10-25 3735
+2012-10-26 4290
+2012-10-27 1857
+2012-10-28 1310
+2012-10-29 2919
+2012-10-30 2887
+2012-10-31 2634
+2012-11-01 2405
+2012-11-02 1582
+2012-11-03 844
+2012-11-04 966
+2012-11-05 2247
+Name: Berri 1, Length: 310, dtype: int64
+</code></pre>
+
+<h2 id="1-3-plotting-a-column">1.3 Plotting a column</h2>
+
+<p>Just add <code>.plot()</code> to the end! How could it be easier? =)</p>
+
+<p>We can see that, unsurprisingly, not many people are biking in January, February, and March.</p>
+
+<pre><code class="language-python">import pandas as pd
+import matplotlib.pyplot as plt
+
+fixed_df = pd.read_csv('bikes.csv', sep=';', encoding='latin1', parse_dates=['Date'], dayfirst=True, index_col='Date')
+fixed_df['Berri 1'].plot()
+plt.show()
+</code></pre>
+
+<p>Output:
+<div>
+<img src="http://tutswiki.com/img/plot_single_column.png" alt="Plotting CSV column with Matplotlib" />
+</div>
+We can also plot all the columns just as easily. We’ll make it a little bigger, too. You can see that it’s more squished together, but all the bike paths behave basically the same – if it’s a bad day for cyclists, it’s a bad day everywhere.</p>
+
+<pre><code class="language-python">fixed_df.plot(figsize=(15, 10))
+plt.show()
+</code></pre>
+
+<p>Output:</p>
+
+<div>
+<img src="http://tutswiki.com/img/plot_dataframe.png" alt="Plotting Dataframe with Matplotlib" />
+</div>
+
+<h2 id="1-4-putting-all-that-together">1.4 Putting all that together</h2>
+
+<p>Here’s the code we needed to write do draw that graph, all together:</p>
+
+<pre><code class="language-python">df = pd.read_csv('bikes.csv', sep=';', encoding='latin1', parse_dates=['Date'], dayfirst=True, index_col='Date')
+df['Berri 1'].plot()
+</code></pre>
+
+<p>Output:
+<div>
+<img src="http://tutswiki.com/img/plot_single_column.png" alt="Plotting CSV column with Matplotlib" />
+</div></p>