Python Pandas multiline graph

Question

I want to make a multi-lines graph from a pandas dataframe on data that are in groups based on the values of a coloumn. The data here are from a api

import pandas as pd
import numpy as np
import calendar
import requests
import json

r =  requests.get('http://data.unhcr.org/api/stats/mediterranean/monthly_arrivals_by_location.json')
js = r.json()
df = pd.DataFrame.from_records(js)

dfTop10 =  df[['location','value']].\
groupby(['location']).sum().sort_values(['value'], ascending=[0])[1:5].reset_index()

grData  =  df[['year','month','location','value']].loc[df['location'].\
isin(dfTop10.location)].groupby(['location','year','month'])['value'].sum().reset_index()

grData['time'] = pd.to_datetime(df.year*10000+df.month*100+1,format='%Y%m%d')

grData= grData[['location','time','value']]

grData.groupby('location').plot()

This code produces 10 different plots while I want to be in the same image and the group to be shown as different colours. Can anyone help?

So you want a line for each City? Where the x and y axes are time and value? — OldGeeksGuide
– OldGeeksGuide, Commented Jun 25, 2017 at 20:44

OldGeeksGuide · Accepted Answer · 2017-06-25 21:40:11Z

1

This isn't pretty, but I think it works:

in place of that last line (the groupby line) you could do this:

from matplotlib import pyplot as plt
plt.figure(figsize=(15,5))

for city in set(grData['location']):
    df  = grData[grData['location'] == city]
    plt.plot(df['time'], df['value'])

But I'm sure there is a cooler way to do it.

To add a legend to the graph, add a label= parameter to each plt.plot and then create the legend at the end:

. . .
for city in set(grData['location']):
    df  = grData[grData['location'] == city]
    plt.plot(df['time'], df['value'], label=city)

plt.legend()

edited Jun 25, 2017 at 21:40

answered Jun 25, 2017 at 20:57

OldGeeksGuide

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1 Comment

Michail N Over a year ago

It works, One more question how can I add labels based on the name of the location?

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