Create Python Pandas Histograms For Specific Row Range As Well As Iterating Through Columns?

I have a set of data that I transpose to get the data groups into rows and have place holder values (for my case, series of mass values) in columns. My next goal is to draw histogr

Solution 1:

Here's a one basic approach,

df = pd.read_clipboard()
df = df.fillna(0)
print(df)

        mz  902.4  909.4  915.3
0        n    0.6    0.3    1.4
1      n.1    0.4    0.3    1.3
2      n.2    0.3    0.2    1.1
3      n.3    0.2    0.2    1.3
4      n.4    0.4    0.3    1.4
5     DCIS    0.3    1.6    0.0
6   DCIS.1    0.3    1.2    0.0
7   DCIS.2    1.1    0.0    0.0
8   DCIS.3    0.2    1.2    0.0
9   DCIS.4    0.2    1.3    0.0
10  DCIS.5    0.2    0.1    1.5
11    br_1    0.5    0.4    1.4
12  br_1.1    0.2    1.3    0.0
13  br_1.2    0.5    0.2    1.4
14  br_1.3    0.5    0.2    1.6
15  br_1.4    1.4    0.0    0.0

Making the subsets (this step can be taken in to the iteration below if the logic can be well defined),

df_n = df.loc[df['mz'].str.startswith('n')]
df_D = df.loc[df['mz'].str.startswith('D')]
df_b = df.loc[df['mz'].str.startswith('b')]

Using matplotlib's subplots()

import matplotlib.pyplot as plt

fig, ax = plt.subplots(nrows=df.shape[1]-1,ncols=1)
plt.tight_layout()

for i in range(1,df.shape[1]):
    df_n.iloc[:,i].hist(ax=ax[i-1],color = 'k', alpha=0.4) # reduced alpha because you're plotting many histograms on top of each other
    df_D.iloc[:,i].hist(ax=ax[i-1],color = 'r', alpha=0.4)
    df_b.iloc[:,i].hist(ax=ax[i-1],color = 'orange', alpha=0.4)
    ax[i-1].set_title("Histograms for " + df.columns[i])