Financial Data Science Financial Performance Analysis: Difference between revisions
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Line 5: | Line 5: | ||
<syntaxhighlight lang='py'> | <syntaxhighlight lang='py'> | ||
import math | |||
import pandas as pd | import pandas as pd | ||
import matplotlib.pyplot as plt | import matplotlib.pyplot as plt |
Revision as of 23:12, 20 October 2023
Internal
Overview
import math
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 = 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 = 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()