Financial Data Science Financial Performance Analysis: Difference between revisions
Jump to navigation
Jump to search
Line 14: | Line 14: | ||
# make it a time series DataFrame | # make it a time series DataFrame | ||
df.set_index('date') | 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[''].apply(dollar_to_int) | |||
</syntaxhighlight> | </syntaxhighlight> |
Revision as of 22:52, 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("./data.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[''].apply(dollar_to_int)