@ -56,7 +56,13 @@ The code of this file is divide in follow sections
1. **Filtering data Function**
Takes all data from the raw data file (`med.csv`), between b and e. It returns the filtered data for lux, temperature, humidity and power.
2. **Plotting data function**
2. **Correlation Function**
Uses the scipy library to calculate Pearson and Spearman correlations, employing two nested `for` loops that populate an empty 4x4 matrix with correlation values. This function takes four inputs; the first four values represent data, and the last indicates which correlation to calculate—`p` for Pearson correlation and `s` for Spearman correlation. Correlations for med data base are shhown below:
![](./PearsC.png)
![](./SpearsS.png)
3. **Plotting data function**
Takes values from lux, temperature, humidity and power, and builds a figure of size 4x4. The structure of these graphs is shown below:
```
@ -65,9 +71,9 @@ The code of this file is divide in follow sections
[Hum vs Lux ] [Hum vs Temp] Hum [Hum vs Pow ]
[Pow vs Lux ] [Pow vs Temp] [Pow vs Hum ] Pow
```
3. **Plotting Temperature Bar Function**
4. **Plotting Temperature Bar Function**
Generates a scatter plot with temperature bars. The input data includes coordinates for the x and y axes, limits for the x and y axes, titles for the x and y axes, and the temperature associated with each point.
4. **Plotting data**
5. **Plotting data**
First, the information from all databases is divided into lux, temperature, humidity, and power. Then, the `GenGraph` function, defined in the Plotting data function section, and the `GenGraphTemp` function, defined in the Plotting Temperature Bar Function section, are used.