CODEWITHSUNDEEP
pythondataframematplotlibunique
Alenson Toh
Alenson Toh

Reputation: 21

How do I plot bar graphs for unique entries in a dataframe column in Python?

I have a dataframe here with two unique time window in df_mo4['time_window'], 2018-09-26 11:30:00 to 2018-09-26 11:32:30 and 2018-09-26 11:32:30 to 2018-09-26 11:35:00. I would like to plot 2 sets of bar graph (not subplot), where the first bar graph depicts the mean, max and min time of individual ID at one time window, and the next bar graph depicting same data at another time window, how can I do about that? Also, I would like the title to be like Duration (time_window). Thank you!

df.plot(kind='bar')
plt.title('Duration \n {}'.format(df['time_window']))
plt.ylabel('Time (s)')
plt.xlabel('ID')
plt.legend(['Mean Time (s)', 'Minimum Time (s)', 'Maximum Time (s)'], loc='upper right')
plt.xticks(np.arange(len(df['ID'])), df['ID'], fontsize=5)
plt.show()

Sample data: 

       ID  time_window                         mean_time   min_time    max_time 
0  8027  2018-09-26 11:30:00 to 2018-09-26 11:32:30  0.101679 0.056412 0.340988
1  8027  2018-09-26 11:32:30 to 2018-09-26 11:35:00  0.090957 0.052196 0.323442
2  8028  2018-09-26 11:30:00 to 2018-09-26 11:32:30  0.199167 0.076872 0.614797       
3  8028  2018-09-26 11:32:30 to 2018-09-26 11:35:00  0.239885 0.062660 0.590710     
4  8029  2018-09-26 11:30:00 to 2018-09-26 11:32:30  0.243241 0.098516 0.5713      
5  8030  2018-09-26 11:30:00 to 2018-09-26 11:32:30  0.083064 0.055656 0.27892       
6  8031  2018-09-26 11:32:30 to 2018-09-26 11:35:00  0.134786 0.058290 0.51279

Upvotes: 1

Views: 49

Answers (1)

DataBach
DataBach

Reputation: 1645

This is the code that I can suggest you:

#Read your Dataframe
df = pd.read_csv('Test.csv', index_col=None, header='infer', encoding="utf-8-sig")

#split the time_window column into two columns, so you can calculate Duration
df['start_time'], df['end_time'] = df['time_window'].str.split('to', 1).str

#convert start and ending time columns to datetime and ID to numeric
df[['start_time','end_time']] = df[['start_time','end_time']].apply(pd.to_datetime, format='%Y-%m-%d %H:%M:%S')
df["ID"] = pd.to_numeric(df["ID"])

#Calculate the duration of a time window and convert into seconds
df['Duration'] = df['start_time'] - df['end_time']
df['Duration']=df['Duration']/np.timedelta64(1,'s')

#plot 
ax = df.plot(x="ID", y=["min_time", "max_time", "mean_time"], kind="bar", rot=25)
ax.set_xlabel("Instances (ID)")
ax.set_ylabel("Duraction(s)")
ax.set_title("Visualization")

rects = ax.patches
labels = df['Duration']

for rect, label in zip(rects, labels):
     height = rect.get_height()
     ax.text(rect.get_x() + rect.get_width(), height+0.3, label,
             ha='center', va='bottom')

This will yield the following dataframe and plot.

enter image description here

enter image description here

Is this what you are looking for? You say you don't want subplots, but it also sounds like you would like an individual graph for each ID?

Upvotes: 1

Related Questions