Groups Counts
1 0-9 38
3 10-19 41
5 20-29 77
7 30-39 73
9 40-49 34
I want to create a bar graph using matplotlib.pyplot library with groups on x-axis and Counts on y-axis. I tried it out using following code
ax = plt.subplots()
rects1 = ax.bar(survived_df["Groups"], survived_df["Counts"], color='r')
plt.show()
but I'm getting following error
invalid literal for float(): 0-9
The first array given to the plt.bar function must be numbers corresponding to the x coordinates of the left sides of the bars. In your case, [0-9, 10-19, ...] is not recognized as valid argument.
You can however make the bar plot using the index of your DataFrame, then defining the position of your x-ticks (where you want your label to be positioned on the x axis) and then changing the labels of your x ticks with your Groups name.
fig,ax = plt.subplots()
ax.bar(survived_df.index, survived_df.Counts, width=0.8, color='r')
ax.set_xticks(survived_df.index+0.4) # set the x ticks to be at the middle of each bar since the width of each bar is 0.8
ax.set_xticklabels(survived_df.Groups) #replace the name of the x ticks with your Groups name
plt.show()
Note that you can also use the Pandas plotting capabilities directly with a one liner:
survived_df.plot('Groups', 'Counts', kind='bar', color='r')
survived_df. Do you use Pandas? then add it to the tags!