CODEWITHSUNDEEP
pythonpandaslistdataframe
Mark K
Mark K

Reputation: 9348

Each element in list at least equal to the previous one

A list of monthly sales until November, I want to know if the sales trend is upward.

Definition of upward: each monthly sales is greater or at least equal to previous month's.

enter image description here

This question is similar to Python: Finding a trend in a set of numbers, but much simpler - only looking the list of numbers.

What I have now is, to check them one by one (in a list). If one month satisfies the condition, it adds an "ok" to a new list. When total number of "ok" equals to 10. The original list of numbers are upward.

import pandas as pd

df_a = pd.DataFrame([['Jan','Feb','Mar','Apr','May','Jun','Jul','Aug','Sep','Oct','Nov'],
[278,342,476,500,559,594,687,739,917,940,982]]).T
df_a.columns = ["Month",  "Sales"]

sales_a = df_a['Sales'].tolist()
ok_a = []

for num, a in enumerate(sales_a):
    if sales_a[num] >= sales_a[num-1]:
        ok_a.append("ok")

if ok_a.count("ok") == 10:
    print ("df_a is uptrend.")

What's the smarter way to do it? Thank you.

Upvotes: 1

Views: 248

Answers (4)

Andy L.
Andy L.

Reputation: 25239

Pandas Series has attribute is_monotonic to check on monotonic increasing. Don't need to sort or do anything fancy.

print(df_a.Sales.is_monotonic)

Out[94]: True

if df_a.Sales.is_monotonic:
    print('df_a is uptrend')

Output:
df_a is uptrend

Upvotes: 4

Raj
Raj

Reputation: 674

A simpler way would be to check 

if(sales_a == sorted(sales_a)):
    print("uptrend")

At the cost of increase in final complexity by a log factor.

Upvotes: 1

RTM
RTM

Reputation: 789

You can use the diff and period method on pandas

df_a['Sales_diff'] = df_a['Sales'].diff(periods=1)
df_a['OK'] = df_a['Sales_diff'] >= 0
df_a

enter image description here

Upvotes: 1

moys
moys

Reputation: 8033

you can do as below

if df_a['Sales'].diff().fillna(0).ge(0).all():
    print ("df_a is uptrend.")
else:
    print ("df_a is NOT a uptrend.")

Upvotes: 2

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