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# Making DataFrames
### Provide a list or numpy array
The column and row labels will simply use the numerical index
```
import pandas as pd
import numpy as np
```
```
z = np.array([[1,2,3,4,5],[6,7,8,9,10]])
z
```
```
pd.DataFrame(z) #note the difference to a numpy array z above
```
```
my_list = [['a', 'b', 'c'], [10,5,2.5], [3,2,1]]
print(my_list)
df = pd.DataFrame(my_list)
df #note the output here
```
\[\['a', 'b', 'c'], \[10, 5, 2.5], \[3, 2, 1]]
```
df.shape
```
(3, 3)
### Provide a dictionary
```
dictionary = {'a':[10,3], 'b':[5,2], 'c':[2.5,1]}
df = pd.DataFrame(dictionary)
df #note the difference with the prior dataframe you made
```
```
df.shape #note the new shape
```
(2, 3)
```
df.columns #this is how to get a list of the column headers
```
Index(\['a', 'b', 'c'], dtype='object')
```
dictionary = {'a':{'row1':3, 'row2':2}, 'b':{'row1':5,'row2':2}, 'c':{'row1':2.5,'row2':1}}
df = pd.DataFrame(dictionary)
df #note the new index!
```
```
df.index #this is how you get a list of the row labels
```
Index(\['row1', 'row2'], dtype='object')
```
dictionary2 = {'a':{'row1':3, 'row2':2}, 'b':{'row3':5,'row4':2}, 'c':{'row5':2.5,'row6':1}}
df2 = pd.DataFrame(dictionary2)
df2
```
#### Read a CSV file
```
#pandas has some great methods to read .csv files
pd.read_csv?
```
```
ms=pd.read_csv("C:\\Users\duan\Desktop\PythonDataProcessingVisualization\mass_spec.csv")
ms
```
#### Read an Excel file
```
#pandas has read_excel method to read excel files
pd.read_excel?
```
```
excelf=pd.read_excel("C:\\Users\duan\Desktop\PythonDataProcessingVisualization\excelfile.csv")
excelf
```
---
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