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1

$begingroup$

I have this chart

where you can see that some points are far away from the "trend" of the curve. The chart represents $5,000$ values where each value corresponds to a specific hour of a day, month and year. In this case, it goes from 01/01/18 until 05/08/18 (non-american format) and as you can see at the first lower peak, it was caused because at 12.00 the cost was $20$ USD but at 1.00 AM it went up to $51$ USD.

I've read that some people just delete those 'peaks' values but I don't know if there's a better solution. This graph shows almost a year but I have in mind on graphing $10$ years of this prices so the situation could be worse. Do you know a better strategy? I'm thinking maybe in calculating average costs for every $6$ hours but it feels like a cheap solution to me.

excel

share|improve this question

edited Aug 11 '18 at 9:37

BrunoGL

1,061222

asked Aug 7 '18 at 6:37

ZrakkZrakk

61

$endgroup$

add a comment | 

1

$begingroup$

I have this chart

where you can see that some points are far away from the "trend" of the curve. The chart represents $5,000$ values where each value corresponds to a specific hour of a day, month and year. In this case, it goes from 01/01/18 until 05/08/18 (non-american format) and as you can see at the first lower peak, it was caused because at 12.00 the cost was $20$ USD but at 1.00 AM it went up to $51$ USD.

I've read that some people just delete those 'peaks' values but I don't know if there's a better solution. This graph shows almost a year but I have in mind on graphing $10$ years of this prices so the situation could be worse. Do you know a better strategy? I'm thinking maybe in calculating average costs for every $6$ hours but it feels like a cheap solution to me.

excel

share|improve this question

edited Aug 11 '18 at 9:37

BrunoGL

1,061222

asked Aug 7 '18 at 6:37

ZrakkZrakk

61

$endgroup$

add a comment | 

$begingroup$

I have this chart

where you can see that some points are far away from the "trend" of the curve. The chart represents $5,000$ values where each value corresponds to a specific hour of a day, month and year. In this case, it goes from 01/01/18 until 05/08/18 (non-american format) and as you can see at the first lower peak, it was caused because at 12.00 the cost was $20$ USD but at 1.00 AM it went up to $51$ USD.

I've read that some people just delete those 'peaks' values but I don't know if there's a better solution. This graph shows almost a year but I have in mind on graphing $10$ years of this prices so the situation could be worse. Do you know a better strategy? I'm thinking maybe in calculating average costs for every $6$ hours but it feels like a cheap solution to me.

excel

share|improve this question

edited Aug 11 '18 at 9:37

BrunoGL

1,061222

asked Aug 7 '18 at 6:37

ZrakkZrakk

61

$endgroup$

share|improve this question

edited Aug 11 '18 at 9:37

BrunoGL

1,061222

asked Aug 7 '18 at 6:37

ZrakkZrakk

61

share|improve this question

edited Aug 11 '18 at 9:37

BrunoGL

1,061222

asked Aug 7 '18 at 6:37

ZrakkZrakk

61

edited Aug 11 '18 at 9:37

BrunoGL

1,061222

edited Aug 11 '18 at 9:37

BrunoGL

1,061222

asked Aug 7 '18 at 6:37

ZrakkZrakk

61

asked Aug 7 '18 at 6:37

ZrakkZrakk

61

1 Answer
1

active

oldest

votes

0

$begingroup$

I would say you have two options to choose from:

• Aggregate your data


• Use a low-pass-filter

---

Aggregating

Aggregating your data over long time periods is not cheap (whatever that means). It is a common way of displaying trends over long periods of time.

Take a look at how Bloomberg displays the exchange rate of EUR over USD.

You can filter by time period, and if you select 1 day, you see the hourly rate:

or you can filter by month, and see the rate aggregated by day. For them, the last rate is the important one, so that is the value you see. For you, however, will depend on your use case. You can choose to pick one of the following: mean, median, mode, max, min, first, last or anything else that makes sense for you.

---

Signal processing filtering

If you want to take a more mathematical approach to your problem, you could use a signal filtering technique to reduce high-frequencies from your signal.

What you need is a low-pass filter.

If you are using Excel, you certainly can do this.
However, I would recommend you do that in some programing language like Matlab or Python, that contain easier to use signal processing packages.

share|improve this answer

edited Aug 11 '18 at 7:45

answered Aug 7 '18 at 7:13

BrunoGLBrunoGL

1,061222

$endgroup$

add a comment | 

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0

$begingroup$

I would say you have two options to choose from:

• Aggregate your data


• Use a low-pass-filter

---

Aggregating

Aggregating your data over long time periods is not cheap (whatever that means). It is a common way of displaying trends over long periods of time.

Take a look at how Bloomberg displays the exchange rate of EUR over USD.

You can filter by time period, and if you select 1 day, you see the hourly rate:

or you can filter by month, and see the rate aggregated by day. For them, the last rate is the important one, so that is the value you see. For you, however, will depend on your use case. You can choose to pick one of the following: mean, median, mode, max, min, first, last or anything else that makes sense for you.

---

Signal processing filtering

If you want to take a more mathematical approach to your problem, you could use a signal filtering technique to reduce high-frequencies from your signal.

What you need is a low-pass filter.

If you are using Excel, you certainly can do this.
However, I would recommend you do that in some programing language like Matlab or Python, that contain easier to use signal processing packages.

share|improve this answer

edited Aug 11 '18 at 7:45

answered Aug 7 '18 at 7:13

BrunoGLBrunoGL

1,061222

$endgroup$

add a comment | 

0

$begingroup$

I would say you have two options to choose from:

• Aggregate your data


• Use a low-pass-filter

---

Aggregating

Aggregating your data over long time periods is not cheap (whatever that means). It is a common way of displaying trends over long periods of time.

Take a look at how Bloomberg displays the exchange rate of EUR over USD.

You can filter by time period, and if you select 1 day, you see the hourly rate:

or you can filter by month, and see the rate aggregated by day. For them, the last rate is the important one, so that is the value you see. For you, however, will depend on your use case. You can choose to pick one of the following: mean, median, mode, max, min, first, last or anything else that makes sense for you.

---

Signal processing filtering

If you want to take a more mathematical approach to your problem, you could use a signal filtering technique to reduce high-frequencies from your signal.

What you need is a low-pass filter.

If you are using Excel, you certainly can do this.
However, I would recommend you do that in some programing language like Matlab or Python, that contain easier to use signal processing packages.

share|improve this answer

edited Aug 11 '18 at 7:45

answered Aug 7 '18 at 7:13

BrunoGLBrunoGL

1,061222

$endgroup$

add a comment | 

$begingroup$

I would say you have two options to choose from:

• Aggregate your data


• Use a low-pass-filter

---

Aggregating

Aggregating your data over long time periods is not cheap (whatever that means). It is a common way of displaying trends over long periods of time.

Take a look at how Bloomberg displays the exchange rate of EUR over USD.

You can filter by time period, and if you select 1 day, you see the hourly rate:

or you can filter by month, and see the rate aggregated by day. For them, the last rate is the important one, so that is the value you see. For you, however, will depend on your use case. You can choose to pick one of the following: mean, median, mode, max, min, first, last or anything else that makes sense for you.

---

Signal processing filtering

If you want to take a more mathematical approach to your problem, you could use a signal filtering technique to reduce high-frequencies from your signal.

What you need is a low-pass filter.

If you are using Excel, you certainly can do this.
However, I would recommend you do that in some programing language like Matlab or Python, that contain easier to use signal processing packages.

share|improve this answer

edited Aug 11 '18 at 7:45

answered Aug 7 '18 at 7:13

BrunoGLBrunoGL

1,061222

$endgroup$

share|improve this answer

edited Aug 11 '18 at 7:45

answered Aug 7 '18 at 7:13

BrunoGLBrunoGL

1,061222

answered Aug 7 '18 at 7:13

BrunoGLBrunoGL

1,061222

answered Aug 7 '18 at 7:13

BrunoGLBrunoGL

1,061222