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pandasdataframematplotlibplotpandas-groupby
oikonomiyaki
oikonomiyaki

Reputation: 7951

Reference grouping columns as x-axis in pyplot

I have a dataframe with this structure:

custid  province    year    features... label
123     AB          2005    ...         0
124     ON          2006    ...         1
...
999     QC          2012    ...         1

The last column is the label / target.

I have a lambda function:

def churn_per_feature(x):
    d = {}
    d['churn_count'] = (x['label'] == 1).sum()
    d['cust_count'] = x['custid'].nunique()
    d['churn_rate'] = d['churn_count'] / float(d['cust_count'])
    return pd.Series(d, index = ['churn_count', 'cust_count', 'churn_rate'])

I have a grouping for two variables, province and year:

churn_per_province_year = df.groupby(['province', 'year']).apply(churn_per_feature)

I am attempting to pyplot this, a single chart with lines, where the x-axis is the years and each line represents the province (so far I am only selecting 4 province with biggest customer count, so it's not in a loop):

plt.plot(years, churn_per_province_year[churn_per_province_year['province'] == 'ON']['cust_count'])
plt.plot(years, churn_per_province_year[churn_per_province_year['province'] == 'AB']['cust_count'])
plt.plot(years, churn_per_province_year[churn_per_province_year['province'] == 'BC']['cust_count'])
plt.plot(years, churn_per_province_year[churn_per_province_year['province'] == 'QC']['cust_count'])
plt.show()

I don't know how to reference the years part.

Upvotes: 1

Views: 334

Answers (1)

Sandipan Dey
Sandipan Dey

Reputation: 23139

Do you want something like the following?

df.groupby(['year', 'province']).apply(churn_per_feature)['cust_count'].unstack().plot(legend=True)

enter image description here

With matplotlib plt.plot():

churn_per_province_year = df.groupby(['year', 'province']).apply(churn_per_feature).reset_index()
#from matplotlib import pyplot
#years = range(2005, 2019) # add the right range here
plt.plot(years, churn_per_province_year[churn_per_province_year['province'] == 'ON']['cust_count'], label='ON')
plt.plot(years, churn_per_province_year[churn_per_province_year['province'] == 'AB']['cust_count'], label='AB')
plt.plot(years, churn_per_province_year[churn_per_province_year['province'] == 'QC']['cust_count'], label='QC')
plt.legend()
plt.show()

enter image description here

Upvotes: 1

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