Better solution or optimising for loop python

Question

My dataset is like this :

[{'Date': '22-Aug-2019', 'Open': 10905.3, 'High': 10908.25, 'Low': 10718.3, 'Close': 10741.35, 'Shares Traded': 668193449, 'Turnover (Rs. Cr)': 18764.38},
{'Date': '23-Aug-2019', 'Open': 10699.6, 'High': 10862.55, 'Low': 10637.15, 'Close': 10829.35, 'Shares Traded': 667079625, 'Turnover (Rs. Cr)': 20983.75}, {'Date': '26-Aug-2019', 'Open': 11000.3, 'High': 11070.3, 'Low': 10756.55, 'Close': 11057.85, 'Shares Traded': 684141923, 'Turnover (Rs. Cr)': 22375.99}]

I want daywise average,Min,Max from this dataset as my output which i did.

for share in dataset:
    day_name = datetime.datetime.strptime(share['Date'], "%d-%b-%Y").strftime('%A')
    if day_name not in day_wise.keys():
        day_wise[day_name] = {'avg':0, 'min':9999999999, 'max':0}

        if share['Turnover (Rs. Cr)'] > day_wise[day_name]['max']:
            day_wise[day_name]['max'] = share['Turnover (Rs. Cr)']
        if share['Turnover (Rs. Cr)'] < day_wise[day_name]['min']:
            day_wise[day_name]['min'] = share['Turnover (Rs. Cr)']
        day_wise[day_name]['avg'] += share['Turnover (Rs. Cr)']

    else:
        if share['Turnover (Rs. Cr)'] > day_wise[day_name]['max']:
            day_wise[day_name]['max'] = share['Turnover (Rs. Cr)']
        if share['Turnover (Rs. Cr)'] < day_wise[day_name]['min']:
            day_wise[day_name]['min'] = share['Turnover (Rs. Cr)']
        day_wise[day_name]['avg'] += share['Turnover (Rs. Cr)']         
return Response(day_wise)

But i want to optimize it , Like less number of lines of code and more fast performance.

Is for share in dataset: is looping through your input dataset ? — pyOliv
– pyOliv, Commented May 28, 2020 at 4:17
@pyOliv its looping through dataset which i mentioned at top. — Pravin Mishra
– Pravin Mishra, Commented May 28, 2020 at 4:18

sushanth · Accepted Answer · 2020-05-28 05:00:58Z

If u can use pandas, try this.

Load the dict to pandas dataframe, apply groupby on Date & aggregate on the numeric column then use to_dict to convert dataframe back to dict.

import pandas as pd

>>> df = pd.DataFrame(data)

          Date     Open      High       Low     Close  Shares Traded  Turnover (Rs. Cr)
0  22-Aug-2019  10905.3  10908.25  10718.30  10741.35      668193449           18764.38
1  23-Aug-2019  10699.6  10862.55  10637.15  10829.35      667079625           20983.75
2  26-Aug-2019  11000.3  11070.30  10756.55  11057.85      684141923           22375.99

>>> df['Day'] = pd.to_datetime(df['Date'], format="%d-%b-%Y").dt.strftime("%A")

>>> df_g = df.groupby('Day')['Turnover (Rs. Cr)'].agg(['min','max','mean'])

               min       max      mean
Day                                   
Friday    20983.75  20983.75  20983.75
Monday    22375.99  22375.99  22375.99
Thursday  18764.38  18764.38  18764.38

>>> df_g.to_dict(orient='index')

{'Friday': {'max': 20983.75, 'mean': 20983.75, 'min': 20983.75},
 'Monday': {'max': 22375.99, 'mean': 22375.99, 'min': 22375.99},
 'Thursday': {'max': 18764.38, 'mean': 18764.38, 'min': 18764.38}}

Christian Gomes · Accepted Answer · 2020-05-28 14:30:23Z

1

One simple e elegant way to reduce your code is using DataFrame. Like this:

import pandas as pd
import calendar

df_data = pd.DataFrame(dataset)

# Convert to day week name
df_data["Date"] = pd.to_datetime(df_data["Date"])
df_data["Date"] = df_data["Date"].apply(lambda x: calendar.day_name[x.weekday()])

day_wise = {}
for name, group in df_data.groupby('Date'):
    day_wise[name] = {
        "avg": group["Turnover (Rs. Cr)"].sum(),
        "min": group["Turnover (Rs. Cr)"].min(),
        "max": group["Turnover (Rs. Cr)"].max()
    }

>> day_wise
{'Friday': {'avg': 20983.75, 'min': 20983.75, 'max': 20983.75},
 'Monday': {'avg': 22375.99, 'min': 22375.99, 'max': 22375.99},
 'Thursday': {'avg': 18764.38, 'min': 18764.38, 'max': 18764.38}}

Note that, i use sum() instead of avg(), since your example only performs the sum. If you want the mean (i.e., avg), just change the sum() for mean() in the code.

edited May 28, 2020 at 14:30

answered May 28, 2020 at 4:27

Christian Gomes

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2 Comments

Pravin Mishra Over a year ago

Christian it showing year i want to show day of the week name

Christian Gomes Over a year ago

@PravinMishra Sorry for that, i change the code... now it's right with your example.

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