kopia lustrzana https://github.com/animator/learn-python
Update and rename Importing_and_Exporting_Data_in_Pandas.md to import-export.md
Ankit Mahato
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# Importing_and_Exporting_Data_in_Pandas
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>Created by Krishna Kaushik
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- **Now we're able to create `Series` and `DataFrames` in pandas, but we usually do not do this , in practice we import the data which is in the form of .csv (Comma Seperated Values) , a spreadsheet file or something similar.**
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- *Good news is that pandas allows for easy importing of data like this through functions such as ``pd.read_csv()`` and ``pd.read_excel()`` for Microsoft Excel files.*
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## 1. Importing from a Google sheet to a pandas dataframe
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*Let's say that you wanted to get the information from Google Sheet document into a pandas DataFrame.*.
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*You could export it as a .csv file and then import it using ``pd.read_csv()``.*
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*In this case, the exported .csv file is called `car-sales.csv`*
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```python
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## Importing Titanic Data set
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import pandas as pd
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car_sales_df= pd.read_csv("https://raw.githubusercontent.com/kRiShNa-429407/learn-python/main/contrib/pandas/Datasets/car-sales.csv")
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print(car_sales_df)
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```
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Make Colour Odometer (KM) Doors Price
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0 Toyota White 150043 4 $4,000.00
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1 Honda Red 87899 4 $5,000.00
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2 Toyota Blue 32549 3 $7,000.00
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3 BMW Black 11179 5 $22,000.00
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4 Nissan White 213095 4 $3,500.00
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5 Toyota Green 99213 4 $4,500.00
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6 Honda Blue 45698 4 $7,500.00
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7 Honda Blue 54738 4 $7,000.00
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8 Toyota White 60000 4 $6,250.00
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9 Nissan White 31600 4 $9,700.00
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The dataset I am using here for your reference is taken from the same repository i.e ``learn-python`` (https://raw.githubusercontent.com/kRiShNa-429407/learn-python/main/contrib/pandas/Datasets/car-sales.csv) I uploaded it in the Datasets folder,you can use it from there.
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You can also place the filename with its path in `pd.read_csv()`.
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**Now we've got the same data from the Google Spreadsheet , but now available as ``pandas DataFrame`` which means we can now apply all pandas functionality over it.**
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#### Note: The quiet important thing i am telling is that ``pd.read_csv()`` takes the location of the file (which is in your current working directory) or the hyperlink of the dataset from the other source.
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#### But if you want to import the data from Github you can't directly use its link , you have to first convert it to raw by clicking on the raw button present in the repo .
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#### Also you can't use the data directly from `Kaggle` you have to use ``kaggle API``
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## 2. The Anatomy of DataFrame
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**Different functions use different labels for different things, and can get a little confusing.**
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- Rows are refer as ``axis=0``
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- columns are refer as ``axis=1``
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## 3. Exporting Data
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**OK, so after you've made a few changes to your data, you might want to export it and save it so someone else can access the changes.**
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**pandas allows you to export ``DataFrame's`` to ``.csv`` format using ``.to_csv()``, or to a spreadsheet format using .to_excel().**
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### Exporting a dataframe to a CSV
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**We haven't made any changes yet to the ``car_sales_df`` DataFrame but let's try to export it.**
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```python
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#Export the titanic_df DataFrame to csv
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car_sales_df.to_csv("exported_car_sales_df.csv")
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```
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Running this will save a file called ``exported_titanic.csv`` to the current folder.
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# Importing and Exporting Data in Pandas
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## Importing Data from a CSV
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We can create `Series` and `DataFrame` in pandas, but often we have to import the data which is in the form of `.csv` (Comma Separated Values), a spreadsheet file or similar tabular data file format.
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`pandas` allows for easy importing of this data using functions such as `read_csv()` and `read_excel()` for Microsoft Excel files.
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*Note: In case you want to get the information from a **Google Sheet** you can export it as a .csv file.*
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The `read_csv()` function can be used to import a CSV file into a pandas DataFrame. The path can be a file system path or a URL where the CSV is available.
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```python
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import pandas as pd
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car_sales_df= pd.read_csv("Datasets/car-sales.csv")
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print(car_sales_df)
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```
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```
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Make Colour Odometer (KM) Doors Price
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0 Toyota White 150043 4 $4,000.00
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1 Honda Red 87899 4 $5,000.00
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2 Toyota Blue 32549 3 $7,000.00
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3 BMW Black 11179 5 $22,000.00
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4 Nissan White 213095 4 $3,500.00
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5 Toyota Green 99213 4 $4,500.00
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6 Honda Blue 45698 4 $7,500.00
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7 Honda Blue 54738 4 $7,000.00
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8 Toyota White 60000 4 $6,250.00
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9 Nissan White 31600 4 $9,700.00
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```
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You can find the dataset used above in the `Datasets` folder.
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*Note: If you want to import the data from Github you can't directly use its link, you have to first obtain the raw file URL by clicking on the raw button present in the repo*
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## Exporting Data to a CSV
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`pandas` allows you to export `DataFrame` to `.csv` format using `.to_csv()`, or to a Excel spreadsheet using `.to_excel()`.
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```python
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car_sales_df.to_csv("exported_car_sales.csv")
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```
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Running this will save a file called ``exported_car_sales.csv`` to the current folder.
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