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import pandas as pd
import numpy as np
df = pd.read_excel("../data/excel-comp-data.xlsx")
 
df["Jan"].sum(), df["Jan"].mean(),df["Jan"].min(),df["Jan"].max()
 
sum_row=df[["Jan","Feb","Mar","total"]].sum()
sum_row
 
df_sum=pd.DataFrame(data=sum_row).T
df_sum

df_sum=df_sum.reindex(columns=df.columns)
df_sum

import pandas as pd
import numpy as np

df = pd.read_excel("../data/sample-salesv3.xlsx")

df['date'] = pd.to_datetime(df['date'])

df2 = df.set_index(['date'])
df2.head()

import pandas as pd
df = pd.read_excel("https://github.com/chris1610/pbpython/blob/master/data/sample-salesv3.xlsx?raw=True")
df["date"] = pd.to_datetime(df['date'])
df.head()
df.info()

# grouping time series and resample by month:
df.set_index('date').resample('M')["ext price"].sum()

df.set_index('date').groupby('name')["ext price"].resample("M").sum()

df.groupby(['name', pd.Grouper(key='date', freq='M')])['ext price'].sum()

# grouping time series and resample by the end of month:
df.groupby(['name', pd.Grouper(key='date', freq='A-DEC')])['ext price'].sum()

import pandas as pd
import numpy as np

df = pd.read_excel("../data/sales-funnel.xlsx")
table = pd.pivot_table(df,index=["Manager","Rep","Product"],
               values=["Price","Quantity"],
               aggfunc=[np.sum,np.mean],fill_value=0)

table.index.get_level_values(0)
table.index.get_level_values(0).unique()

table.index.get_level_values(1)
table.index.get_level_values(1).unique()

import pandas as pd
import numpy as np
 
data = {'account': ['Jones LLC', 'Alpha Co', 'Blue Inc', 'Mega Corp'], 
        'Total Sales': [150, 200, 75, 300], 
        'Country': ['US', 'UK', 'US', 'US']}
df = pd.DataFrame.from_dict(data)

indices = [True, False, True, True]
df[indices]

import xlwings as xw
import numpy as np
import pandas as pd
import datetime as dt
import time
import sys
 
# Fire up a new book in the active Excel instance
wb1 = xw.Book()
# Connects to an unsaved book (looks in all Excel instances)
wb1 = xw.Book('Book1')
sheet = wb1.sheets[0]

rng = sheet.range('A1:D5')
rng[0, 0]

rng[1]
rng[:, 3:]
rng[1:3, 1:3]
xw.books.active.close()