4.5 KiB
4.5 KiB
Exercise: Have a look at the neural data using Pandas¶
In [1]:
import pandas as pd
# Set some Pandas options: maximum number of rows/columns it's going to display
pd.set_option('display.max_rows', 1000)
pd.set_option('display.max_columns', 100)
Load electrophysiology data¶
In [2]:
df = pd.read_csv('../../data/QC_passed_2024-07-04_collected.csv')
1. How many rows/columns does the data set have?¶
In [ ]:
2. Display the first 5 rows of the DataFrame¶
In [ ]:
3. Display the names and dtypes of all the columns¶
In [ ]:
4. Display the unique values of the high K concentration and of the treatment columns¶
In [ ]:
5. Display the main statistics of the max_spikes column¶
In [ ]:
6. Show all the rows where the max number of spikes is larger than 50¶
In [ ]:
7. Display the main statistics of 'max_spikes', for the rows where high K concentration is 8 mM and 15 mM (separately)¶
Are the distributions any different?
In [ ]:
8. Display the statistics of max_spikes when high K concentration is 8 mM, and the maximum number of spikes is <= 100¶
Does that change your conclusion?
In [ ]:
9. Transform the high K concentration column into a numerical column¶
a) Discard the last three characters of the columns (' mM')
b) Use .astype(float) to convert to floating point numbers
c) Save the result in a column K (mM)
In [ ]:
In [ ]: