[FIXED] How do you graph multiple items in a dataframe on one graph using pandas and matplotlib.pyplot?

Issue

The dataframe I am trying to graph is below. I want to plot each fieldname as the legend item with x=year and y=value

The name of the dataframe is my_gross

                     fieldName thisType         value  year
0   diluted_shares_outstanding     unit  9.637900e+07  2015
1   diluted_shares_outstanding     unit  8.777500e+07  2016
2   diluted_shares_outstanding     unit  8.556200e+07  2017
3   diluted_shares_outstanding     unit  8.353000e+07  2018
4   diluted_shares_outstanding     unit  7.771000e+07  2019
5   diluted_shares_outstanding     unit  7.292900e+07  2020
6                          eps    gross  7.360470e+08  2015
7                          eps    gross  7.285207e+08  2016
8                          eps    gross  8.944702e+08  2017
9                          eps    gross  1.298734e+09  2018
10                         eps    gross  1.451550e+09  2019
11                         eps    gross  1.259110e+09  2020
18               sales_revenue    gross  5.817000e+09  2015
19               sales_revenue    gross  5.762000e+09  2016
20               sales_revenue    gross  6.641000e+09  2017
21               sales_revenue    gross  8.047000e+09  2018
22               sales_revenue    gross  9.351000e+09  2019
23               sales_revenue    gross  8.530000e+09  2020

The following code is what I ran to create a graph, but I get undesired results.

for item in my_gross['fieldName']:
    plt.plot(my_gross['year'], my_gross['value'],label=item)

plt.legend()
plt.xticks(rotation=45)
plt.show()

Results undesired graph

The result I am trying to get is similar to this graph desired graph

Do I need to create a dictionary for unique values and do some sort of count and then loop through that dictionary instead of the df itself?

Solution

The standard pandas and matplotlib approach is to pivot to wide-form and plot:

import pandas as pd
from matplotlib import pyplot as plt

plot_df = df.pivot(index='year',
                   columns='fieldName',
                   values='value')

plot_df.plot()
plt.tight_layout()
plt.show()

plot_df:

fieldName  diluted_shares_outstanding           eps  sales_revenue
year                                                              
2015                       96379000.0  7.360470e+08   5.817000e+09
2016                       87775000.0  7.285207e+08   5.762000e+09
2017                       85562000.0  8.944702e+08   6.641000e+09
2018                       83530000.0  1.298734e+09   8.047000e+09
2019                       77710000.0  1.451550e+09   9.351000e+09
2020                       72929000.0  1.259110e+09   8.530000e+09

---

seaborn.lineplot has built-in functionality with hue without needing to reshape:

import pandas as pd
import seaborn as sns
from matplotlib import pyplot as plt

sns.lineplot(data=df, x='year', y='value', hue='fieldName')
plt.tight_layout()
plt.show()

Answered By - Henry Ecker