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Given the following text description, write Python code to implement the functionality described below step by step
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Description:
 Notebook arguments
data_id (int)
Step1:  Processing
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Python Code:
import numpy as np
np.random.seed(data_id)
data = np.random.randn(100)
Explanation: Notebook arguments
data_id (int): Select which data file to load. Valid values: 0, 1, 2.
analysis_type (string): Which analysis type to perform. Valid valuse 'a', 'b' and 'c'
Template Notebook
<p class=lead>This notebook (pretends to) executes one of the three analysis type 
'a', 'b' or 'c', on one of the data files in a set (identified by an index).</p>
You can either run this notebook directly, or run it through the master notebook for batch processing.
Load the data
We mock loading some data. We use data_id as a seed to generate different data-sets.
In the real-world case can be the index in a list of data files.
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analysis_dict = dict(a=np.mean, b=np.max, c=np.min)
result = analysis_dict[analysis_type](data)
print('Result of analysis "%s" on dataset %d is %.3f.' % (analysis_type, data_id, result))
Explanation: Processing
End of explanation
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