```python
%matplotlib inline
import matplotlib
import numpy as np
import pandas as pd
import os
import matplotlib.pylab as plt
```


```python
files = [f for f in os.listdir("/sw/apps/nasa") if f.endswith('csv')]
```


```python
frames = []
idx = 0
for f in files:
    print(f)
    frames.append(pd.read_csv("/sw/apps/nasa/{}".format(f), header=None, names=["position","unixepoc","sdate", "stime", "metric", "val"]))
    frames[idx] = frames[idx].assign(timestamp=lambda x: x.sdate+" "+x.stime)
    frames[idx].timestamp = pd.to_datetime(frames[idx].timestamp)
    frames[idx] = frames[idx].drop(['sdate','stime','position','unixepoc','val'], axis=1)
    frames[idx] = frames[idx].set_index(['timestamp'])
    frames[idx].sort_index(inplace=True)
    idx += 1
```

    barometric pressure.csv
    humidity.csv
    solar radiation.csv
    sunrise.csv
    sunset.csv
    temperature.csv
    wind direction in degrees.csv
    wind speed.csv


## Barometric Pressure


```python
frames[0].metric.plot(figsize=(16,5))
```




    <matplotlib.axes._subplots.AxesSubplot at 0x11c9a3198>




![png](output_4_1.png)


## Humidity


```python
frames[1].metric.plot(figsize=(16,5))
```




    <matplotlib.axes._subplots.AxesSubplot at 0x1193dca90>




![png](output_6_1.png)


## Solar Radiation


```python
frames[2].metric.plot(figsize=(16,5))
```




    <matplotlib.axes._subplots.AxesSubplot at 0x1193f6278>




![png](output_8_1.png)


## Sunrise


```python
frames[3].metric.plot(figsize=(16,5))
```




    <matplotlib.axes._subplots.AxesSubplot at 0x11d7ec940>




![png](output_10_1.png)


## Sunset


```python
frames[4].metric.plot(figsize=(16,5))
```




    <matplotlib.axes._subplots.AxesSubplot at 0x11d7885f8>




![png](output_12_1.png)


## Temperature


```python
frames[5][frames[5].index.month==12].plot(figsize=(16,5))
```




    <matplotlib.axes._subplots.AxesSubplot at 0x12379cda0>




![png](output_14_1.png)



```python
frames[5][frames[5].index.month==12].metric.describe()
```




    count    8164.000000
    mean       47.608893
    std         4.994597
    min        34.000000
    25%        45.000000
    50%        47.000000
    75%        50.000000
    max        62.000000
    Name: metric, dtype: float64




```python
frames[5].metric.plot(figsize=(16,5))
```




    <matplotlib.axes._subplots.AxesSubplot at 0x11d17a550>




![png](output_16_1.png)


## Wind Direction


```python
frames[6].metric.plot(figsize=(16,5))
```




    <matplotlib.axes._subplots.AxesSubplot at 0x11d0c6cf8>




![png](output_18_1.png)


##  Wind Speed


```python
frames[7].metric.plot(figsize=(16,5))
```




    <matplotlib.axes._subplots.AxesSubplot at 0x11d7aec88>




![png](output_20_1.png)



```python

```