I&#39;m generating a bar-chart with matplotlib. It all works well but I can&#39;t figure out how to prevent the labels of the x-axis from overlapping each other. Here an example:  
![enter image description here][1]


  [1]: http://i.stack.imgur.com/BCm0v.png  
Here is some sample SQL for a postgres 9.1 database:  

    drop table if exists mytable;
    create table mytable(id bigint, version smallint, date_from timestamp without time zone);
    insert into mytable(id, version, date_from) values
    
    (&#39;4084036&#39;, &#39;1&#39;, &#39;2006-12-22 22:46:35&#39;),
    (&#39;4084938&#39;, &#39;1&#39;, &#39;2006-12-23 16:19:13&#39;),
    (&#39;4084938&#39;, &#39;2&#39;, &#39;2006-12-23 16:20:23&#39;),
    (&#39;4084939&#39;, &#39;1&#39;, &#39;2006-12-23 16:29:14&#39;),
    (&#39;4084954&#39;, &#39;1&#39;, &#39;2006-12-23 16:28:28&#39;),
    (&#39;4250653&#39;, &#39;1&#39;, &#39;2007-02-12 21:58:53&#39;),
    (&#39;4250657&#39;, &#39;1&#39;, &#39;2007-03-12 21:58:53&#39;)
    ;  


And this is my python-script:  

    # -*- coding: utf-8 -*-
    #!/usr/bin/python2.7
    import psycopg2
    import matplotlib.pyplot as plt
    fig = plt.figure()
    
    # for savefig()
    import pylab
    
    ###
    ### Connect to database with psycopg2
    ###
    
    try:
      conn_string=&quot;dbname=&#39;x&#39; user=&#39;y&#39; host=&#39;z&#39; password=&#39;pw&#39;&quot;
      print &quot;Connecting to database\n-&gt;%s&quot; % (conn_string)
          
      conn = psycopg2.connect(conn_string)
      print &quot;Connection to database was established succesfully&quot;
    except:
      print &quot;Connection to database failed&quot;
    
    ###
    ### Execute SQL query
    ###  
      
    # New cursor method for sql
    cur = conn.cursor()
    
    # Execute SQL query. For more than one row use three &#39;&quot;&#39;
    try:
      cur.execute(&quot;&quot;&quot; 
      
    -- In which year/month have these points been created?
    -- Need &#39;yyyymm&#39; because I only need Months with years (values are summeed up). Without, query returns every day the db has an entry.

    SELECT to_char(s.day,&#39;yyyymm&#39;) AS month
          ,count(t.id)::int AS count
    FROM  (
       SELECT generate_series(min(date_from)::date
                             ,max(date_from)::date
                             ,interval &#39;1 day&#39;
              )::date AS day
       FROM   mytable t
       ) s
    LEFT   JOIN mytable t ON t.date_from::date = s.day
    GROUP  BY month
    ORDER  BY month;
    
      &quot;&quot;&quot;)
    
    # Return the results of the query. Fetchall() =  all rows, fetchone() = first row
      records = cur.fetchall()
      cur.close()
    
    except:
      print &quot;Query could not be executed&quot;
    
    # Unzip the data from the db-query. Order is the same as db-query output
    year, count = zip(*records)
    
    ###
    ### Plot (Barchart)
    ###
    
    # Count the length of the range of the count-values, y-axis-values, position of axis-labels, legend-label
    plt.bar(range(len(count)), count, align=&#39;center&#39;, label=&#39;Amount of created/edited points&#39;)
    
    # Add database-values to the plot with an offset of 10px/10px
    ax = fig.add_subplot(111)
    for i,j in zip(year,count):
        ax.annotate(str(j), xy=(i,j), xytext=(10,10), textcoords=&#39;offset points&#39;)
    
    # Rotate x-labels on the x-axis
    fig.autofmt_xdate()
    
    # Label-values for x and y axis
    plt.xticks(range(len(count)), (year))
    
    # Label x and y axis
    plt.xlabel(&#39;Year&#39;)
    plt.ylabel(&#39;Amount of created/edited points&#39;)
    
    # Locate legend on the plot (http://matplotlib.org/users/legend_guide.html#legend-location)
    plt.legend(loc=1)
    
    # Plot-title
    plt.title(&quot;Amount of created/edited points over time&quot;)
    
    # show plot
    pylab.show()




Is there a way how I can prevent the labels from overlapping each other? Ideally in an automatic way, because I can&#39;t predict the amount of bars.


matplotlib: how to prevent x-axis labels from overlapping

I have a survey file in which row are observation and column question.

Here are some [fake data][1] they look like:

    People,Food,Music,People
    P1,Very Bad,Bad,Good
    P2,Good,Good,Very Bad
    P3,Good,Bad,Good
    P4,Good,Very Bad,Very Good
    P5,Bad,Good,Very Good
    P6,Bad,Good,Very Good


My aim is to create this kind of plot with `ggplot2`. 

 - I absolutely **don&#39;t care of the colors, design, etc.**
 - The plot doesn&#39;t correspond to the fake data

![enter image description here][2]


Here are my fake data:

    raw &lt;- read.csv(&quot;http://pastebin.com/raw.php?i=L8cEKcxS&quot;,sep=&quot;,&quot;)
    raw[,2]&lt;-factor(raw[,2],levels=c(&quot;Very Bad&quot;,&quot;Bad&quot;,&quot;Good&quot;,&quot;Very Good&quot;),ordered=FALSE)
    raw[,3]&lt;-factor(raw[,3],levels=c(&quot;Very Bad&quot;,&quot;Bad&quot;,&quot;Good&quot;,&quot;Very Good&quot;),ordered=FALSE)
    raw[,4]&lt;-factor(raw[,4],levels=c(&quot;Very Bad&quot;,&quot;Bad&quot;,&quot;Good&quot;,&quot;Very Good&quot;),ordered=FALSE)


But if I choose Y as count then I&#39;m facing an issue about choosing the X and the Group values... I don&#39;t know if I can succeed without using `reshape2`... I&#39;ve also tired to use reshape with melt function. But I don&#39;t understand how to use it...


  [1]: http://pastebin.com/raw.php?i=L8cEKcxS
  [2]: http://i.stack.imgur.com/yCWRc.png

Grouped bar plot in ggplot

I am generating bar plots using matplotlib and it looks like there is a bug with the stacked bar plot. The sum for each vertical stack should be 100. However, for X-AXIS ticks 65, 70, 75 and 80 we get completely arbitrary results which do not make any sense. I do not understand what the problem is. Please find the MWE below.

    import numpy as np
    import matplotlib.pyplot as plt
    import matplotlib
    header = [&#39;a&#39;,&#39;b&#39;,&#39;c&#39;,&#39;d&#39;]
    dataset= [(&#39;60.0&#39;, &#39;65.0&#39;, &#39;70.0&#39;, &#39;75.0&#39;, &#39;80.0&#39;, &#39;85.0&#39;, &#39;90.0&#39;, &#39;95.0&#39;, &#39;100.0&#39;, &#39;105.0&#39;, &#39;110.0&#39;, &#39;115.0&#39;, &#39;120.0&#39;, &#39;125.0&#39;, &#39;130.0&#39;, &#39;135.0&#39;, &#39;140.0&#39;, &#39;145.0&#39;, &#39;150.0&#39;, &#39;155.0&#39;, &#39;160.0&#39;, &#39;165.0&#39;, &#39;170.0&#39;, &#39;175.0&#39;, &#39;180.0&#39;, &#39;185.0&#39;, &#39;190.0&#39;, &#39;195.0&#39;, &#39;200.0&#39;), (0.0, 25.0, 48.93617021276596, 83.01886792452831, 66.66666666666666, 66.66666666666666, 70.96774193548387, 84.61538461538461, 93.33333333333333, 85.0, 92.85714285714286, 93.75, 95.0, 100.0, 100.0, 100.0, 100.0, 80.0, 100.0, 100.0, 100.0, 100.0, 100.0, 100.0, 100.0, 100.0, 100.0, 100.0, 100.0), (0.0, 50.0, 36.17021276595745, 11.320754716981133, 26.666666666666668, 33.33333333333333, 29.03225806451613, 15.384615384615385, 6.666666666666667, 15.0, 7.142857142857142, 6.25, 5.0, 0.0, 0.0, 0.0, 0.0, 20.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0), (0.0, 12.5, 10.638297872340425, 3.7735849056603774, 4.444444444444445, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0), (100.0, 12.5, 4.25531914893617, 1.8867924528301887, 2.2222222222222223, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0)]
    X_AXIS = dataset[0]
    
    matplotlib.rc(&#39;font&#39;, serif=&#39;Helvetica Neue&#39;)
    matplotlib.rc(&#39;text&#39;, usetex=&#39;false&#39;)
    matplotlib.rcParams.update({&#39;font.size&#39;: 40})
    
    fig = matplotlib.pyplot.gcf()
    fig.set_size_inches(18.5, 10.5)
    
    configs = dataset[0]
    N = len(configs)
    ind = np.arange(N)
    width = 0.4
    
    p1 = plt.bar(ind, dataset[1], width, color=&#39;r&#39;)
    p2 = plt.bar(ind, dataset[2], width, bottom=dataset[1], color=&#39;b&#39;)
    p3 = plt.bar(ind, dataset[3], width, bottom=dataset[2], color=&#39;g&#39;)
    p4 = plt.bar(ind, dataset[4], width, bottom=dataset[3], color=&#39;c&#39;)
    
    plt.ylim([0,120])
    plt.yticks(fontsize=12)
    plt.ylabel(output, fontsize=12)
    plt.xticks(ind, X_AXIS, fontsize=12, rotation=90)
    plt.xlabel(&#39;test&#39;, fontsize=12)
    plt.legend((p1[0], p2[0], p3[0], p4[0]), (header[0], header[1], header[2], header[3]), fontsize=12, ncol=4, framealpha=0, fancybox=True)
    plt.show()

[![enter image description here][1]][1]



  [1]: https://i.stack.imgur.com/DSs2h.png


stacked bar plot using matplotlib

I am drawing a bar chart using `highchart.js`

**I do not want to show the x - axis data values.**

Can any one tell me which option does it?
&lt;br /&gt;
full config:

    var chart = new Highcharts.Chart({
                    chart: {
                        renderTo: container,
                        defaultSeriesType: &#39;bar&#39;
                    },
                    title: {
                        text: null
                    },
                    subtitle: {
                        text: null
                    },
                    xAxis: {
                        categories: [&#39;&#39;],
                        title: {
                            text: null
                        },
                        labels: {enabled:true,y : 20, rotation: -45, align: &#39;right&#39; }
    
                    },
                    yAxis: {
                        min: 0,
                        gridLineWidth: 0,
                        title: {
                            text: &#39;&#39;,
                            align: &#39;high&#39;
                        }
                    },
                    tooltip: {
                        formatter: function () {
                            return &#39;&#39;;
                        }
                    },
                    plotOptions: {
                        bar: {
                            dataLabels: {
                                enabled: true
                            },
                            pointWidth: 35,
                            color: &#39;#D9CDC1&#39;
                        }
                    },
                    legend: {
                        enabled: false
                    },
                    credits: {
                        enabled: false
                    },
                    series: [{
                        name: &#39;Year 1800&#39;,
                        data: [107]
                    }]
                });

how to hide highchart x - axis data values

I have looked through the answers in this forum but cannot seem to find an answer to this specific problem. I have the following data and want to create a bar chart where the bars are ordered from largest to smallest in terms of &quot;Value&quot;, rather than having them in alphabetical order:

    breadth_data &lt;- read.table(textConnection(&quot;Stakeholder	Value
    &#39;Grantseekers&#39;	0.90
    &#39;Donors&#39;	0.89
    &#39;Community&#39;	0.55
    &#39;Hurricane Relief Fund&#39;	0.24
    &#39;Media&#39;	0.19
    &#39;Employment Seekers&#39;	0.12
    &#39;Affiliates&#39;	0.10
    &#39;Youth&#39;	0.09
    &#39;Women&#39;	0.02
    &#39;Former Board Members&#39;	0.01&quot;), header=TRUE)

Then the basic bar chart:

    c &lt;- ggplot(breadth_data, aes(x=Stakeholder, y=Value))
    c + geom_bar(stat=&quot;identity&quot;) + coord_flip() + scale_y_continuous(&#39;&#39;) + scale_x_discrete(&#39;&#39;)


I have tried many of the different reorderings and transformations I&#39;ve seen on StackOverflow but I cannot seem to find one that works. I am sure this is fairly simple, but I would appreciate any help!

Thanks,

Greg



Ordering of bars in ggplot

I generated a bar plot, how can I display the value of the bar on each bar?

Current plot:

![enter image description here][1]


What I am trying to get:

![enter image description here][2]


My code:

    import os
    import numpy as np
    import matplotlib.pyplot as plt
            
    x = [u&#39;INFO&#39;, u&#39;CUISINE&#39;, u&#39;TYPE_OF_PLACE&#39;, u&#39;DRINK&#39;, u&#39;PLACE&#39;, u&#39;MEAL_TIME&#39;, u&#39;DISH&#39;, u&#39;NEIGHBOURHOOD&#39;]
    y = [160, 167, 137, 18, 120, 36, 155, 130]
    
    fig, ax = plt.subplots()    
    width = 0.75 # the width of the bars 
    ind = np.arange(len(y))  # the x locations for the groups
    ax.barh(ind, y, width, color=&quot;blue&quot;)
    ax.set_yticks(ind+width/2)
    ax.set_yticklabels(x, minor=False)
    plt.title(&#39;title&#39;)
    plt.xlabel(&#39;x&#39;)
    plt.ylabel(&#39;y&#39;)      
    #plt.show()
    plt.savefig(os.path.join(&#39;test.png&#39;), dpi=300, format=&#39;png&#39;, bbox_inches=&#39;tight&#39;) # use format=&#39;svg&#39; or &#39;pdf&#39; for vectorial pictures


  [1]: http://i.stack.imgur.com/8QhzO.png
  [2]: http://i.stack.imgur.com/yU7lZ.png

How to display the value of the bar on each bar with pyplot.barh()

I got stuck on something that feels like should be relatively easy. The code I bring below is a sample based on a larger project I&#39;m working on. I saw no reason to post all the details, so please accept the data structures I bring as is.

Basically, I&#39;m creating a bar chart, and I just can figure out how to add value labels on the bars (in the center of the bar, or just above it). Been looking at samples around the web but with no success implementing on my own code. I believe the solution is either with &#39;text&#39; or &#39;annotate&#39;, but I:
a) don&#39;t know which one to use (and generally speaking, haven&#39;t figured out when to use which).
b) can&#39;t see to get either to present the value labels.
Would appreciate your help, my code below.
Thanks in advance!

    import numpy as np
    import pandas as pd
    import matplotlib.pyplot as plt
    pd.set_option(&#39;display.mpl_style&#39;, &#39;default&#39;) 
    %matplotlib inline
    
    # Bring some raw data.
    frequencies = [6, 16, 75, 160, 244, 260, 145, 73, 16, 4, 1]
    
    # In my original code I create a series and run on that, 
    # so for consistency I create a series from the list.
    freq_series = pd.Series.from_array(frequencies)
    
    x_labels = [108300.0, 110540.0, 112780.0, 115020.0, 117260.0, 119500.0, 
                121740.0, 123980.0, 126220.0, 128460.0, 130700.0]
    
    # Plot the figure.
    plt.figure(figsize=(12, 8))
    fig = freq_series.plot(kind=&#39;bar&#39;)
    fig.set_title(&#39;Amount Frequency&#39;)
    fig.set_xlabel(&#39;Amount ($)&#39;)
    fig.set_ylabel(&#39;Frequency&#39;)
    fig.set_xticklabels(x_labels)

Adding value labels on a matplotlib bar chart

How can we change y axis to percent like the figure? I can change y axis range but I can&#39;t make it to percent.
![enter image description here][1]


  [1]: http://i.stack.imgur.com/wuK3a.jpg

How can I change the Y-axis figures into percentages in a barplot?

How to plot multiple bars in matplotlib, when I tried to call the bar function multiple times, they overlap and as seen the below figure the highest value red can be seen only.
How can I plot the multiple bars with dates on the x-axes? 

  So far, I tried this:
  

```python
import matplotlib.pyplot as plt
import datetime
        
x = [
    datetime.datetime(2011, 1, 4, 0, 0),
    datetime.datetime(2011, 1, 5, 0, 0),
    datetime.datetime(2011, 1, 6, 0, 0)
]
y = [4, 9, 2]
z = [1, 2, 3]
k = [11, 12, 13]
      
ax = plt.subplot(111)
ax.bar(x, y, width=0.5, color=&#39;b&#39;, align=&#39;center&#39;)
ax.bar(x, z, width=0.5, color=&#39;g&#39;, align=&#39;center&#39;)
ax.bar(x, k, width=0.5, color=&#39;r&#39;, align=&#39;center&#39;)
ax.xaxis_date()
        
plt.show()
```

I got this: 

![enter image description here][2]

The results should be something like, but with the dates are on the x-axes and bars are next to each other: 

![enter image description here][1]

  [1]: http://i.stack.imgur.com/YinlC.png

  [2]: http://i.stack.imgur.com/12jnX.png


Python matplotlib multiple bars

I tried to make the title self-explanatory, but here goes - data first:

    dtf &lt;- structure(list(variable = structure(c(1L, 1L, 2L, 2L, 3L, 3L, 
    4L, 4L, 5L, 5L), .Label = c(&quot;vma&quot;, &quot;vla&quot;, &quot;ia&quot;, &quot;fma&quot;, &quot;fla&quot;), class = &quot;factor&quot;), 
        ustanova = structure(c(1L, 2L, 1L, 2L, 1L, 2L, 1L, 2L, 1L, 
        2L), .Label = c(&quot;srednja škola&quot;, &quot;fakultet&quot;), class = &quot;factor&quot;), 
        `(all)` = c(42.9542857142857, 38.7803203661327, 37.8996138996139, 
        33.7672811059908, 29.591439688716, 26.1890660592255, 27.9557692307692, 
        23.9426605504587, 33.2200772200772, 26.9493087557604)), .Names = c(&quot;variable&quot;, 
    &quot;ustanova&quot;, &quot;(all)&quot;), row.names = c(NA, 10L), class = c(&quot;cast_df&quot;, 
    &quot;data.frame&quot;), idvars = c(&quot;variable&quot;, &quot;ustanova&quot;), rdimnames = list(
        structure(list(variable = structure(c(1L, 1L, 2L, 2L, 3L, 
        3L, 4L, 4L, 5L, 5L), .Label = c(&quot;vma&quot;, &quot;vla&quot;, &quot;ia&quot;, &quot;fma&quot;, 
        &quot;fla&quot;), class = &quot;factor&quot;), ustanova = structure(c(1L, 2L, 
        1L, 2L, 1L, 2L, 1L, 2L, 1L, 2L), .Label = c(&quot;srednja škola&quot;, 
        &quot;fakultet&quot;), class = &quot;factor&quot;)), .Names = c(&quot;variable&quot;, &quot;ustanova&quot;
        ), row.names = c(&quot;vma_srednja škola&quot;, &quot;vma_fakultet&quot;, &quot;vla_srednja škola&quot;, 
        &quot;vla_fakultet&quot;, &quot;ia_srednja škola&quot;, &quot;ia_fakultet&quot;, &quot;fma_srednja škola&quot;, 
        &quot;fma_fakultet&quot;, &quot;fla_srednja škola&quot;, &quot;fla_fakultet&quot;), class = &quot;data.frame&quot;), 
        structure(list(value = structure(1L, .Label = &quot;(all)&quot;, class = &quot;factor&quot;)), .Names = &quot;value&quot;, row.names = &quot;(all)&quot;, class = &quot;data.frame&quot;)))

And I&#39;d like to create a dodged barplot, do the `coord_flip` and put some text labels inside the bars:

    ggplot(bar) + geom_bar(aes(variable, `(all)`, fill = ustanova), position = &quot;dodge&quot;) +
     geom_text(aes(variable, `(all)`, label = sprintf(&quot;%2.1f&quot;, `(all)`)), position = &quot;dodge&quot;) +
     coord_flip()

you can see output [here][1].

![enter image description here][2]

I reckon I&#39;m asking for something trivial. I want the text labels to &quot;follow&quot; stacked bars. Labels are placed correctly on the y-axis, but how to position them correctly on x-axis?


  [1]: http://imgur.com/adBht
  [2]: http://i.stack.imgur.com/bC5w8.png

Position geom_text on dodged barplot

I am trying to get the x axis labels to be rotated 45 degrees on a barplot with no luck. This is the code I have below:

    barplot(((data1[,1] - average)/average) * 100,
            srt       = 45,
            adj       = 1,
            xpd       = TRUE,
            names.arg = data1[,2],
            col       = c(&quot;#3CA0D0&quot;),
            main      = &quot;Best Lift Time to Vertical Drop Ratios of North American Resorts&quot;,
            ylab      = &quot;Normalized Difference&quot;,
            yaxt      = &#39;n&#39;,
            cex.names = 0.65,
            cex.lab   = 0.65)



Rotating x axis labels in R for barplot

I&#39;ve found this, https://stackoverflow.com/questions/6455088/how-to-put-labels-over-geom-bar-in-r-with-ggplot2, but it just put labels(numbers) over only one bar. 

Here is, let&#39;s say, two bars for each x-axis, how to do the same thing? 

My data and code look like this:

    dat &lt;- read.table(text = &quot;sample Types Number
    sample1 A   3641
    sample2 A   3119
    sample1 B   15815
    sample2 B   12334
    sample1 C   2706
    sample2 C   3147&quot;, header=TRUE)
    
    library(ggplot2)
    bar &lt;- ggplot(data=dat, aes(x=Types, y=Number, fill=sample)) + 
      geom_bar(position = &#39;dodge&#39;) + geom_text(aes(label=Number))

Then, we&#39;ll get:
![enter image description here][1]


  [1]: http://i.stack.imgur.com/fwAww.png

It seems that the number texts are also positioned in the &quot;dodge&quot; pattern.
I&#39;ve searched [geom_text manual](http://ggplot2.tidyverse.org/reference/geom_text.html) to find some information, but cannot make it work. 

Suggestions? 

 

How to put labels over geom_bar for each bar in R with ggplot2

How do you plot bar charts in gnuplot with text labels?

How do you plot bar charts in gnuplot?

Supposely, I have the bar chart as below:

![BarPlot][1]


  [1]: http://i.stack.imgur.com/wy1lP.png

Any ideas on how to set different colors for each carrier? As for example, AK would be Red, GA would be Green, etc?

I am using Pandas and matplotlib in Python

    &gt;&gt;&gt; f=plt.figure()
    &gt;&gt;&gt; ax=f.add_subplot(1,1,1)
    &gt;&gt;&gt; ax.bar([1,2,3,4], [1,2,3,4])
    &lt;Container object of 4 artists&gt;
    &gt;&gt;&gt; ax.get_children()
    [&lt;matplotlib.axis.XAxis object at 0x6529850&gt;, &lt;matplotlib.axis.YAxis object at 0x78460d0&gt;,  &lt;matplotlib.patches.Rectangle object at 0x733cc50&gt;, &lt;matplotlib.patches.Rectangle object at 0x733cdd0&gt;, &lt;matplotlib.patches.Rectangle object at 0x777f290&gt;, &lt;matplotlib.patches.Rectangle object at 0x777f710&gt;, &lt;matplotlib.text.Text object at 0x7836450&gt;, &lt;matplotlib.patches.Rectangle object at 0x7836390&gt;, &lt;matplotlib.spines.Spine object at 0x6529950&gt;, &lt;matplotlib.spines.Spine object at 0x69aef50&gt;, &lt;matplotlib.spines.Spine object at 0x69ae310&gt;, &lt;matplotlib.spines.Spine object at 0x69aea50&gt;]
    &gt;&gt;&gt; ax.get_children()[2].set_color(&#39;r&#39;) #You can also try to locate the first patches.Rectangle object instead of direct calling the index.

For the suggestions above, how do exactly we could enumerate ax.get_children() and check if the object type is rectangle? So if the object is rectangle, we would assign different random color?

Setting Different Bar color in matplotlib Python

I am getting this error while plotting a bar graph and I am not able to get rid of it, I have tried both qplot and ggplot but still the same error.

Following is my code:

     library(dplyr)
     library(ggplot2)

     #Investigate data further to build a machine learning model
     data_country = data %&gt;%
               group_by(country) %&gt;%
               summarise(conversion_rate = mean(converted))
      #Ist method
      qplot(country, conversion_rate, data = data_country,geom = &quot;bar&quot;, stat =&quot;identity&quot;, fill =   country)
      #2nd method
      ggplot(data_country)+aes(x=country,y = conversion_rate)+geom_bar()

Error:
      
      stat_count() must not be used with a y aesthetic

Data in data_country:

        country conversion_rate
        &lt;fctr&gt;           &lt;dbl&gt;
      1   China     0.001331558
      2 Germany     0.062428188
      3      UK     0.052612025
      4      US     0.037800687

The error is coming in bar chart and not in the dotted chart.


R ggplot2: stat_count() must not be used with a y aesthetic error in Bar graph

After performing a `groupby.sum()` on a `DataFrame` I&#39;m having some trouble trying to create my intended plot.

![grouped dataframe with multi-index][1]


```python
import pandas as pd
import numpy as np

np.random.seed(365)
rows = 100
data = {&#39;Month&#39;: np.random.choice([&#39;2014-01&#39;, &#39;2014-02&#39;, &#39;2014-03&#39;, &#39;2014-04&#39;], size=rows),
        &#39;Code&#39;: np.random.choice([&#39;A&#39;, &#39;B&#39;, &#39;C&#39;], size=rows),
        &#39;ColA&#39;: np.random.randint(5, 125, size=rows),
        &#39;ColB&#39;: np.random.randint(0, 51, size=rows),}
df = pd.DataFrame(data)

     Month Code  ColA  ColB
0  2014-03    C    59    47
1  2014-01    A    24     9
2  2014-02    C    77    50

dfg = df.groupby([&#39;Code&#39;, &#39;Month&#39;]).sum()

              ColA  ColB
Code Month              
A    2014-01   124   102
     2014-02   398   282
     2014-03   474   198
     2014-04   830   237
B    2014-01   477   300
     2014-02   591   167
     2014-03   522   192
     2014-04   367   169
C    2014-01   412   180
     2014-02   275   205
     2014-03   795   291
     2014-04   901   309
```


How can I create a subplot (`kind=&#39;bar&#39;`) for each `Code`, where the x-axis is the `Month` and the bars are `ColA` and `ColB`?

  [1]: http://i.stack.imgur.com/y9L5u.png

Pandas Plotting with Multi-Index

I&#39;m using matplotlib to generate a (vertical) barchart. The problem is my labels are rather long. Is there any way to display them vertically, either in the bar or above it or below it?


Barchart with vertical labels in python/matplotlib

I&#39;m looking to see how to do two things in Seaborn with using a bar chart to display values that are in the dataframe, but not in the graph

1) I&#39;m looking to display the values of one field in a dataframe while graphing another.  For example, below, I&#39;m graphing &#39;tip&#39;, but I would like to place the value of &#39;total_bill&#39; centered above each of the bars (i.e.325.88 above Friday, 
1778.40 above Saturday, etc.)

2) Is there a way to scale the colors of the bars, with the lowest value of &#39;total_bill&#39; having the lightest color (in this case Friday) and the highest value of &#39;total_bill&#39; having the darkest.  Obviously, I&#39;d stick with one color (i.e. blue) when I do the scaling.

Thanks! I&#39;m sure this is easy, but i&#39;m missing it..

**While I see that others think that this is a duplicate of another problem (or two), I am missing the part of how I use a value that is not in the graph as the basis for the label or the shading.  How do I say, use total_bill as the basis.  I&#39;m sorry, but I just can&#39;t figure it out based on those answers.**

Starting with the following code,

    import pandas as pd
    import seaborn as sns
    %matplotlib inline
    df=pd.read_csv(&quot;https://raw.githubusercontent.com/wesm/pydata-    book/master/ch08/tips.csv&quot;, sep=&#39;,&#39;)
    groupedvalues=df.groupby(&#39;day&#39;).sum().reset_index()
    g=sns.barplot(x=&#39;day&#39;,y=&#39;tip&#39;,data=groupedvalues)

I get the following result:

[![enter image description here][1]][1]

Interim Solution:


    for index, row in groupedvalues.iterrows():
        g.text(row.name,row.tip, round(row.total_bill,2), color=&#39;black&#39;, ha=&quot;center&quot;)

[![enter image description here][2]][2]

On the ***shading***, using the example below, I tried the following:

    import pandas as pd
    import seaborn as sns
    %matplotlib inline
    df=pd.read_csv(&quot;https://raw.githubusercontent.com/wesm/pydata-book/master/ch08/tips.csv&quot;, sep=&#39;,&#39;)
    groupedvalues=df.groupby(&#39;day&#39;).sum().reset_index()

    pal = sns.color_palette(&quot;Greens_d&quot;, len(data))
    rank = groupedvalues.argsort().argsort() 
    g=sns.barplot(x=&#39;day&#39;,y=&#39;tip&#39;,data=groupedvalues)

    for index, row in groupedvalues.iterrows():
        g.text(row.name,row.tip, round(row.total_bill,2), color=&#39;black&#39;, ha=&quot;center&quot;)
    
But that gave me the following error:

**AttributeError: &#39;DataFrame&#39; object has no attribute &#39;argsort&#39;**

So I tried a modification:

    import pandas as pd
    import seaborn as sns
    %matplotlib inline
    df=pd.read_csv(&quot;https://raw.githubusercontent.com/wesm/pydata-book/master/ch08/tips.csv&quot;, sep=&#39;,&#39;)
    groupedvalues=df.groupby(&#39;day&#39;).sum().reset_index()

    pal = sns.color_palette(&quot;Greens_d&quot;, len(data))
    rank=groupedvalues[&#39;total_bill&#39;].rank(ascending=True)
    g=sns.barplot(x=&#39;day&#39;,y=&#39;tip&#39;,data=groupedvalues,palette=np.array(pal[::-1])[rank])

and that leaves me with 

**IndexError: index 4 is out of bounds for axis 0 with size 4**
  [1]: https://i.stack.imgur.com/0GmTW.png
  [2]: https://i.stack.imgur.com/LGily.png

Seaborn Barplot - Displaying Values

I am using the following code to plot a bar-chart:

    import matplotlib.pyplot as pls 
    my_df.plot(x=&#39;my_timestampe&#39;, y=&#39;col_A&#39;, kind=&#39;bar&#39;) 
    plt.show()

The plot works fine. However, I want to improve the graph by having 3 columns: &#39;col_A&#39;, &#39;col_B&#39;, and &#39;col_C&#39; all on the plot. Like in the example figure below:

[![enter image description here][1]][1]

  [1]: https://i.stack.imgur.com/34kIU.png

I would like the `col_A` displayed in blue above x-axis, `col_B` in red below x-axis, and `col_C` in green above x-axis. Is this something possible in matplotlib? How do I make changes to plot all the three columns? Thanks!


matplotlib: plot multiple columns of pandas data frame on the bar chart

I know that [`seaborn.countplot`](https://seaborn.pydata.org/generated/seaborn.countplot.html) has the attribute `order` which can be set to determine the order of the categories. But what I would like to do is have the categories be in order of descending count. I know that I can accomplish this by computing the count manually (using a `groupby` operation on the original dataframe, etc.) but I am wondering if this functionality exists with `seaborn.countplot`. Surprisingly, I cannot find an answer to this question anywhere.

All Bar Chart Solutions on Gang of Coders

Total of 20 Bar Chart Solutions