Financial Data Science Financial Performance Analysis: Difference between revisions

From NovaOrdis Knowledge Base
Jump to navigation Jump to search
Line 20: Line 20:


# extract a specific time series and plot it
# extract a specific time series and plot it
fidelity_self_managed = df[''].apply(dollar_to_int)
fidelity_self_managed = df['Fidelity Self'].apply(dollar_to_int)


# graph
# graph

Revision as of 22:57, 20 October 2023

Internal

Overview

import pandas as pd
import matplotlib.pyplot as plt
import matplotlib.ticker as ptick

# load the DataFrame
df = pd.read_csv("./finances.csv", parse_dates=["Date"])

# make it a time series DataFrame
df.set_index('Date')

# declare the function that converts the dollar amount
def dollar_to_int(s: str):
    return int(s[1:].replace(',',''))

# extract a specific time series and plot it
fidelity_self_managed = df['Fidelity Self'].apply(dollar_to_int)

# graph
fig, ax = plt.subplots()
fig.autofmt_xdate()
ax.set_ylabel("amount")
ax.yaxis.set_major_formatter(mt.FormatStrFormatter('% 1.2f')) 
ax.plot(fidelity_self_managed)
plt.show()