Plot the number of instances in first column with respect to second column in python?

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I have this table in excel which I am trying to analyze. I am not able to plot the number of S and D (in column 3) according to months (in Col4). I am plotting the number of S and D in col3 using the following. But how to plot the number of S & D according to the months. How to do that?

I would like to get two line plots showing the number of S and D respectively with the corresponding months on the X-axis.

#to plot the number of S and D in col3

df = pd.read_csv (r'C:\Users\data.csv', usecols = ['Col1','Col2','Col3','Col4'])
df['Col4'] = pd.to_datetime(df['Col4'], format="%m/%d/%Y").dt.date
df.head()

df1 = df[['Col3']].copy()
my_dict = df1['Col3'].value_counts().to_dict()  
myList = my_dict.items()
x, y = zip(*myList) 
plt.bar(x, y, color = "tomato")
plt.ylabel('Count')
plt.title('Outcome')
plt.show() 


    Col1    Col2    Col3    Col4
0   Y   MA  S   2/2/2022
1   N   YJ  D   4/25/2022
2   N   YJ  D   3/11/2022
3   N   YJ  D   4/28/2022
4   Y   YJ  D   4/21/2022
5   N   YJ  D   4/21/2022
6   Y   WE  D   5/25/2022
7   Y   WE  S   5/7/2022
8   N   WE  D   3/30/2022
9   N   PR  D   3/22/2022
10  Y   PR  S   3/22/2022

enter image description here

pandas matplotlib python
1 Answers

The following should do what the OP wants given the data frame as posted:

df = pd.DataFrame({'Col1': ['Y', 'N', 'N', 'N', 'Y', 'N', 'Y', 'Y', 'N', 'N', 'Y'],
                   'Col2': ['MA', 'YJ', 'YJ', 'YJ', 'YJ', 'YJ', 'WE', 'WE', 'WE', 'PR', 'PR'],
                   'Col3': ['S', 'D', 'D', 'D', 'D', 'D', 'D', 'S', 'D', 'D', 'S'],
                   'Col4': ['2/2/2022', '4/25/2022', '3/11/2022', '4/28/2022', '4/21/2022',
                            '4/21/2022', '5/25/2022', '5/7/2022',  '3/30/2022', '3/22/2022', '3/22/2022']})
  1. First extract the month from the dates in Col4 (and sort ascending by month):
df.loc[:, 'Month'] = pd.to_datetime(df.Col4).dt.month
df = df.sort_values('Month', ascending=True)
    Col1 Col2 Col3       Col4  Month
 0     Y   MA    S   2/2/2022      2
 2     N   YJ    D  3/11/2022      3
 8     N   WE    D  3/30/2022      3
 9     N   PR    D  3/22/2022      3
 10    Y   PR    S  3/22/2022      3
 1     N   YJ    D  4/25/2022      4
 3     N   YJ    D  4/28/2022      4
 4     Y   YJ    D  4/21/2022      4
 5     N   YJ    D  4/21/2022      4
 6     Y   WE    D  5/25/2022      5
 7     Y   WE    S   5/7/2022      5
  1. Create a pivot table with Month as the index, the values of Col3 (i.e., S and D) as columns, and counts as the cell values:
df1 = df.groupby(['Month', 'Col3'])\
        .size()\
        .unstack(fill_value=0)\
        .reset_index()
 Col3  Month  D  S
 0         2  0  1
 1         3  3  1
 2         4  4  0
 3         5  1  1
  1. Plot the results
plt.plot(df1.Month, df1.D, label='D')
plt.plot(df1.Month, df1.S, label='S')
plt.xlabel('Month')
plt.ylabel('Count')
plt.legend()
plt.show()

enter image description here

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