File tree Expand file tree Collapse file tree 1 file changed +51
-0
lines changed Expand file tree Collapse file tree 1 file changed +51
-0
lines changed Original file line number Diff line number Diff line change @@ -24,5 +24,56 @@ This project demonstrates a complete data analysis workflow using Python. The st
24
24
` ` ` bash
25
25
pip install pandas matplotlib scikit-learn
26
26
```
27
+ 4. Prepare Data
28
+
29
+ Place your CSV file in the project directory. Ensure it is named data.csv or update the script accordingly.
30
+
31
+ # ## Running the Analysis
32
+
33
+ 1. Place your CSV file
34
+
35
+ Make sure the ` data.csv` file is located in the same directory as data_analysis.py.
36
+
37
+ 2. Run the script
38
+ ` ` ` bash
39
+ python3 data_analysis.py
40
+ ` ` `
41
+
42
+ 3. Output
43
+
44
+ The script will display the contents of the CSV file, a statistical summary of the data, and data types.
45
+
46
+ # ## Script Details
47
+
48
+ data_analysis.py: Reads data.csv, prints the data, shows statistical summaries, and displays data types.
49
+
50
+ ` ` ` bash
51
+ import pandas as pd
52
+
53
+ # Load data
54
+ data = pd.read_csv(' data.csv' )
55
+
56
+ # Display data
57
+ print(" Data:" )
58
+ print(data)
59
+
60
+ # Display statistical summary
61
+ print(" \nStatistical Summary:" )
62
+ print(data.describe ())
63
+
64
+ # Display data types
65
+ print(" \nData Types:" )
66
+ print(data.dtypes)
67
+ ` ` `
68
+
69
+
70
+ # #Acknowledgements
71
+
72
+ The ` pandas` library for data manipulation and analysis.
73
+
74
+
75
+
76
+
77
+ Feel free to modify any section to better fit your project' s specifics or personal preferences!
27
78
28
79
You can’t perform that action at this time.
0 commit comments