Question: I have 1000 files in which the data is stored in comma separation.
The description of a file is given below:

The values are comma separated, `-9999` values should be ignored and
if it can be read, all the values of row and column should be stored in numbers,
as it has to used in plotting.
The shape of file is [**104 rows x 15 columns**].

The few lines of the files are as follows:

```
0,   9.8597e+00, 129.944,   1.071, 6.7433e-06, 1.0911e-05,      -9999,      -9999, 3.7134e-07, 3.5245e-05,      -9999,      -9999,  26.295,   -86.822,  -123.017

0,   8.7012e+00, 130.908,   0.966, 1.9842e-06, 1.0799e-05,      -9999,      -9999, 3.5888e-07, 7.8133e-05,      -9999,      -9999,  27.140,   -86.818,  -122.322

```

After reading into numeric values, I need to plot it into subplot also.
Like COl1 vs Col2 , Col3 vs col5 and so on....

Any idea how to achieve it?

```
import numpy as np
import pandas as pd 
import matplotlib.pyplot as plt

df1=pd.read_csv("small_file_106.txt",header=1)
print(df1)

```

Answer: 
I never used plot ,but following would be useful for the first question
input the list of values to na\_values and those will be considered as NA by pandas

```
pd.read_csv(File, sep=',',na_values=['-9999'],keep_default_na=False)

```

Also [pd.to\_numeric](http://pandas.pydata.org/pandas-docs/stable/generated/pandas.to_numeric.html) is available to convert data to numeric

```
df.apply(lambda x: pd.to_numeric(x, errors='ignore'))

```
Once you've read the data in (Shijo's method looks good) the [Seaborn library's pairplot](https://stanford.edu/~mwaskom/software/seaborn/generated/seaborn.pairplot.html) should generate the plot you want.