test.py

import pandas as pd
import csv,sys
import matplotlib
import matplotlib.pyplot as plt

print("Reading file... ")
df = pd.read_csv('test.batch.csv')
#print(df)

# Creating a dictionary
data = {'Value':[0,0,0]}
kernel_df = pd.DataFrame(data, index=['M1','M2','M3'])
my_dict = {'dummy':kernel_df}
my_dict2 = {'dummy':kernel_df}
# dummy  ->          Value
#               M1      0
#               M2      0
#               M3      0

for name, df_group in df.groupby('Name'):
    my_dict[name] = pd.concat(
        [g.reset_index(drop=True) for _, g in df_group.groupby('ID')['Value']],
        axis=1
    )



def plot_dataframe(df, cnt, axes):
    df.columns = range(1, len(df.columns)+1)   # Ignore the column header
    row = df.iloc[0].astype(int)  # First row in the dataframe
    plt.subplot(2, 1, 1)
    print("axes=", axes)
    print("axes[0]=", axes[0])
    print("cnt=", cnt)
    print("row=", row)
    ax1 = row.plot(label=cnt, ax=axes[0], marker='o')   # Line chart
    ax1.set_ylabel( 'test', fontsize=15 )
    plt.subplot(2, 1, 2)
    df2 = row.value_counts()
    df2.reindex().plot(kind='bar', label=cnt, ax=axes[1])   # Histogram


def plot_kernels(mydict2):
    print("New dictionary for plot = ", my_dict2)
    fig,axes = plt.subplots(2,1, figsize=(20, 15))
    cnt=1
    for key in my_dict2:
        if key == 'dummy':   # skip the dummy key
            continue
        df = my_dict2[key]
        print("Key is ", key, " -> df is ", df)
        plot_dataframe(df, cnt, axes)
        cnt = cnt + 1
    for ax in axes:
        ax.legend()
    plt.show()

print("matplotlib version = ",  matplotlib.__version__)
print("pandas version = ", pd.__version__)
print("sys version", sys.version_info)




yax = 'bar'
print("Original dictionary = ", my_dict)
for k in my_dict.keys():
    if yax in k:
        # Should definitely go here
        df = my_dict[k]
        my_dict2[k] = df
        #print(df)

plot_kernels(my_dict2)