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# Create heatmap
sns.heatmap(minutes_df.groupby([minutes_df['Business Date'].dt.date, minutes_df['Business Date'].dt.strftime('%H:00')])
   ['Orders'].mean()
   .rename_axis(index=['Date','Hour'])
   .unstack(level=0),
    cmap='coolwarm'
)

# Add title
plt.title('Customers in Queue Over Time')

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# Initialize date ranges list
date_ranges_list = []

# Loop through all the orders placed on the source file
for i, row in df.iterrows():

    # Get Start/End Time
    enter_t = row["OrderCreatedLocalDateTime"].replace(second=0, microsecond=0)
    exit_t = row["TimeOutOfQueue"].replace(second=0, microsecond=0)

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# Calculate timeframe from input file on a minute basis
# If the timespan from the source file is less than a day
if (pd.to_datetime(df.iloc[-1,0]) - pd.to_datetime(df.iloc[0,0])).days == 0:
    timeframe = pd.date_range(
        df.iloc[0,0], 
        periods=60*24, 
        freq='1min'
    )
# If the timespan from the source file is more than a day
else:

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# Import libraries and dependencies
import datetime
import pandas as pd
import matplotlib.pyplot as plt
import seaborn as sns

# Read csv file
df = pd.read_csv('orders.csv')

# Convert OrderCreatedLocalDateTime column to datetime type

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# Build seaborn replot
g = sns.relplot(
    data=data,
    x="Replicate",
    y="Value",
    hue="Operator",
    style="Operator",
    col="Part",
    col_wrap=5,
    aspect=0.7

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# Add Replicate column
data["Replicate"] = list(np.arange(1, data["Part"].value_counts()[1]+1))*(int(len(data["Part"])/data["Part"].value_counts()[1]))

# Display top rows
data.head()

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# Import libraries and dependencies
import numpy as np
import pandas as pd
import seaborn as sns
import matplotlib.pyplot as plt
%matplotlib inline

# Open Excel file
data = pd.read_excel("msa_2_crossed.xlsx")

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First name: Roberto
Last name: Salazar
Email address: [email protected]
Universities: ['Northwestern University', 'State University of New York at Binghamton']

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# Print results
print(f"First name: {myResume.firstName}")
print(f"Last name: {myResume.lastName}")
print(f"Email address: {myResume.emailAddress}")
print(f"Universities: {myResume.universities}")

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# Instantiate myResume variable
myResume = Resume(text)

# Obtain resume information
myResume.get_first_name()
myResume.get_last_name()
myResume.get_email()
myResume.get_univerisities()