Financial Data Science Financial Performance Analysis: Difference between revisions
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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()